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About this book

These proceedings gather selected papers from the 9th International Conference on Green Intelligent Transportation Systems and Safety, held in Guilin, China on July 1-3, 2018. They feature cutting-edge studies on Green Intelligent Mobility Systems, the guiding motto being to achieve “green, intelligent, and safe transportation systems.” The contributions presented here can help promote the development of green mobility and intelligent transportation technologies to improve interconnectivity, resource sharing, flexibility and efficiency. Given its scope, the book will benefit researchers and engineers in the fields of Transportation Technology and Traffic Engineering, Automotive and Mechanical Engineering, Industrial and System Engineering, and Electrical Engineering alike.

Table of Contents


Ordinal Logistic Regression Modeling Research on Decreasing Perceived Metro Transfer Time

This study newly develops two Ordinal Logistic Regression (OLR) models to explore effective ways to save Perceived Transfer Time (PTT) of metro passengers, in view of the difficulty of improving the infrastructure of a metro station. It is found that the PTT will be effectively decreased if the transfer walking congestion is released to be acceptable. Moreover, the congestion on the platform should be eliminated for reducing the PTT. In addition, decreasing the actual transfer waiting time to less than 5.00 min will evidently decrease the PTT. In future works, the effectiveness of the newly developed OLR models needs to be validated in a further and improved by applying them to study the PTT of metro passengers in different cities.

Xuesong Feng, Weixin Hua, Xuejun Niu

Research on the Site Selection of Distribution Center Based on Centroid Method and Fuzzy Evaluation Method

In order to help logistics enterprise to improve the distribution condition, reduce the waste caused when a vehicle is fragmented transporting commodity, optimize logistics system, reduce costs, improve service levels, is conducive to the strategic development of the enterprise. This paper uses the Centroid Method to get some alternative logistics distribution center address, at the same time, considering the various factors influencing the site selection, mainly includes land condition, natural conditions, traffic conditions, operation conditions and the influence of the policies and regulations, uses Fuzzy Evaluation Method to decide the best distribution center. Finally, the effectiveness of the algorithm was verified by the 27 Eurasian supermarket chains in Changchun city, and the address of the best logistics distribution center was obtained.

Mingtao Chen, Chun Bao, Hua Yang, Zhiyuan Wang

A Bayesian Recognition Method for Highway Ambiguity Path Identification Based on Digraph

With the rapid development of the highway, the layout of road network is gradually transformed from the tree structure to the reticular structure. In order to develop a fair charging strategy, it is necessary to split the route of vehicles accurately. In this paper, a directed graph based method for ambiguous path of highway identification with Bayesian recognition algorithm is studied. Firstly, the highway network should be modeled into a digraph structure, and the 5.8G identification point or video image identification point would be mapped to the directed graph. Then a Bayesian recognition algorithm would be used to determine the actual path of the vehicle. The algorithm uses a two-stage structure, which could provide a rapid calculation at the exit lane. The method has been applied in the highway of Jiangxi Province and has achieved valuable results.

Xu-jin Yu, Jun Xu, Fan Zhang

Time-Varying Characteristics and Forecasting Model of Parking Berth Demand in Urban Residential Areas

In order to improve the micro analysis and prediction of real-time forecasting method of dynamic parking demand, we selected three typical residential areas in Yangzhou City as an example to analyze the time-varying characteristics of motor vehicles’ arrival and departure. Considering the obvious difference between the arrival and departure characteristics of motor vehicle in residential areas on weekdays and weekends, the different time series models were used to forecast the berth occupancy of three residential areas on weekdays and weekends. Due to the higher proportion of commute travel on weekdays and the higher proportion of flexible travel on weekends, the variation tendency of berth occupancy on weekends is not as stable as that on weekdays. The result shows that the prediction accuracy of real-time numbers of berth on weekdays is usually higher than that on weekends. On weekdays, the berth occupancy rate of three residential areas is regular, which can be forecasted by ARIMA (Autoregressive Integrated Moving Average) model, and can reach more than 98% of the prediction accuracy. Oppositely, the weekends’ time-varying regularity of berth occupancy is not obvious, thus using ARMA (Autoregressive Moving Average) model, and the accuracy can reach over 95%. Overall, time series model has good adaptability to the residential area, and the higher accuracy can be achieved by selecting the appropriate model.

Jun Chen, Yi-fan Yue, Jingheng Zheng, Dong-ping Li

Risk Evaluation Model of Unsignalized Intersection Based on Traffic Conflict Line Theory

In order to analyze unsignalized intersections safety performance objectively and systematically, given that the traditional traffic conflict research focuses on the two-vehicle conflict, a risk evaluation model based on “traffic flow conflict line” theory was developed. Firstly the characteristics of crossing, diverging and merging conflicts were analyzed. Due to different types of traffic conflicts caused different potential treats and collision severities, the research estimated the weighted values of crossing, merging and diverging conflicts through analyzing the leading vehicle conflict potential probability, collision severities and transmission length of traffic conflicts. Finally the research combined all results for establishing useful index of intersection safety called expected values of conflicts. Compared with the traditional method, the results show that the leading vehicle conflict probability model is closer to the real process of traffic conflicts based on the critical conflict distance. The model takes into account the speed, angle, acceleration and reaction time between two vehicles. Based on physics collision theory, analyzing the angle change, deceleration relation of the vehicle and the kinetic energy loss, three traffic conflicts weights were discussed when accident occurred (crossing conflict: diverging conflict: merging conflict = 12.7051:1:1). Based on the mathematical expectation method, the total equivalent expected conflict model was developed through analyzing the potential probability of conflict, traffic volume and vehicle position, so this model can more accurately describe the actual traffic flow conflict behavior.

Li Yuan, Yi-hang Sun, Xuan Zhang, Juan He

Understanding the Impacts of Leisure Purpose and Environmental Factors on the Elders Leisure Activities and Travel Behavior: A Case Study in Kunming, China

In this study, authors use a structural equation modeling approach to test the impacts of leisure purpose and environmental factors on the elders’ leisure features, location choice, and related travel behavior. The results showed that leisure purpose had significant direct impacts on leisure features and locations but had no direct effects on leisure related travel behavior. Environmental factors had only direct effects on leisure locations and indirect effects on leisure related travel behavior. The results suggest that community parks and neighborhood green fields were more important to the elders’ leisure activities than large city parks due to high proximity and thus should be deliberately planned to improve the elders’ well-being in urban land use development.

Ren Dong, Shengyi Gao, Baohong He

Multi-scenarios Behavior Choice Model of Shared Parking in Residential Area

With the development of economics, the parking contradiction has become more serious in residential area. For optimization of the distribution of parking resource in residential area with limited land resources, the strategy of shared parking has been studied and adopted by more and more countries. The aim of this research is to determine the influence factors of selecting shared parking facilities in residential area and to increase the probability of choosing shared parking can increase with changing the characteristics of people or parking facilities. It will help to relieve parking contradiction and optimize parking resources in residential area. In order to acquire people’s parking behavior characteristics, the paper designed questionnaire with three scenarios which contain shared parking and non-shared parking facilities. By questionnaire data introduced, the discrete choice modeling was set up to investigate the variability of probability of choosing shared parking across individual characteristics, socioeconomic attributes, trip and parking attributes, desire of accepting or providing shared parking and parking attributes in scenarios. For simulating the nonlinear effects of variables on the target variable more accurately, the BP neural network was used to filter redundant attributes. According to the model estimation results, charging had a significant impact on the selecting shared parking facilities. It found that people prefer selecting shared parking, which is same as the analysis of questionnaire. This indicates that the BP neural network is used to filter factors optimally. Finally, for appealing to people parking in shared parking facilities, it is suggested that the strategy of decreasing charging in shared parking facilities should be adopted. And the paper explored details areas for future research.

Jun Chen, Zexingjian Du, Jingheng Zheng

Pedestrian Arrival and Release Characteristics at Signalized Crosswalk

The paper applied the shock wave theory to analyze the characteristics of pedestrian arrival and release, considering different related factors (i.e., crosswalk width, length, and signal timing). Then pedestrian release model with two constraints was established on the strength of above study. At last, correlation parameters were calibrated with the practical pedestrian data, and the lateral distance between pedestrians is shown as 0.8 m. The proposed model can be used in following two ways: the optimization of crosswalk width and the evaluation of crosswalk capacity to accommodate the demand. The result could offer some references to protect the safety of pedestrians and improve the crosswalk capacity.

Xianmin Song, Di Liang, Lili Li, Qiujie Yang, Qiaowen Bai

Design and Operation Recommendations for Shared BRT Stops with No Overtaking

In some BRT systems, certain sections of the operating infrastructure are shared with conventional buses. With increases in arrival rates and the occurrence of a phenomenon known as in-stop queueing, service quality and space utilization may decrease at shared BRT stops. This study analyzes the mixed operating characteristics at shared BRT stops and provides some suggestions for shared BRT stop design and operation to maintain service quality and space utilization. A wasted passageway calculation model is established to determine the space utilization. Relationships among service time, effective number of berths, stop capacity and expected number of wasted passageways are analyzed and corresponding design and operation recommendations are proposed.

Jiao Ye, Jun Chen, Hua Bai, Dongping Li

Sensitivity of Simulated Conflicts to VISSIM Driver Behavior Parameter Modification

The impact of driver behavior parameters in a widely used microscopic simulation package, i.e., VISSIM, on the simulated traffic conflict counts is presented in this study. More specifically, 31 driving behavior-related parameters is investigated with different parameter value. By modifying the parameter value, VISSIM produces different vehicle trajectory files, and a surrogate safety assessment model (SSAM) package is applied to output the conflicts. It shows that, in the present model, the numbers of parameters sensitive to the count of total conflict, rear-end conflict and lane-change conflict were 10, 12, and 4, respectively. The study partly demonstrated the impacts of different human behavior parameters provided in the VISSIM on the simulated conflicts. Future studies were to be conducted to sensitive analysis of multi-parameters and the evaluation countermeasures for the impacts of these parameters on simulated conflicts.

Qi-yu Liang, Qian Wan, Lu Bai, Hao Yu, Liu-xuan Lv, Dong-ping Li

Research on the Analysis of Campus’ Accessibility Based on Individual Activity Type

The previous accessibility model is fundamental but neglects activity type on transportation analysis and planning. It fails to comprehensively evaluate individuals’ travel behaviors and their utilizable spatial-temporal resources under different activity types. This paper applies time geography method and classifies the activity types according to the characteristics and the elastic degree of individual activities. And then, the spatial temporal accessibility model and extended model based on the characteristics of different activity types are constructed. Moreover, a case study of campus trip data is given to verify the rationality of the models. The results show that when considering the type of activities, the accessibility does not follow the characteristics of scatter diagram and a “core to periphery” layer structure which is from high to low. Instead, it is determined by the type of activity. The stronger the mandatory activities are, the higher the accessibility of the region will be. Furthermore, when there are only one kind of facilities, the travel distance and time are major factors affecting the value of accessibility, and the personal selection of facilities follows the principle of proximity. The results are more consistent with the real life, therefore the proposed models are more rational. The results of this study provides great reference to the quantification of urban accessibility and theoretical support to the allocation of public urban facilities.

Baohong He, Xiang Zhang, Xuefeng Li

Dynamic Programming Approaches for Solving Shortest Path Problem in Transportation: Comparison and Application

This paper seeks to investigate the performance of two different dynamic programming approaches for shortest path problem of transportation road network in different context, including the Bellman’s dynamic programming approach and the Dijkstra’s algorithm. The procedures to implement the two algorithms are discussed in detail in this study. The application of the Bellman’s approach shows that it is computationally expensive due to a lot of repetitive calculations. In comparison, the Dijkstra’s algorithm can effectively improve the computational efficiency of the backward dynamic programming approach. According to whether the shortest path from the node to the original node has been found, the Dijkstra’s algorithm marked the node with permanent label and temporal label. In each step, it simultaneously updates both the permanent label and temporal label to avoid the repetitive calculations in the backward dynamic programming approach. In addition, we also presented an algorithm using dynamic programming theory to solve the K shortest path problem. The K shortest path algorithm is particular useful to find the possible paths for travelers in real-world. The computational performance of the three approaches in large network is explored. This study will be useful for transportation engineers to choose the approaches to solve the shortest path problem for different needs.

Xuan Li, Xiaofei Ye, Lili Lu

Understanding of Day-to-Day Route Choice Behavior: Experiments and Simulations

Dissension arises on whether the day-to-day route choice behavior will cause an equilibrium distribution of traffic flow on the road network, and the travelers’ decision-making mechanism of route choice behavior is still in the exploratory stage. This paper focuses on the ‘equilibrium dissension’ and the ‘decision making mechanism’ under the condition of historical experience and traffic information by conducting human-computer interaction experiments and multi-agent simulations. The results of experiments support the conclusion that ‘no convergence to equilibrium had been found’. Moreover, the simulations with the existing mechanism that perceptions of travel time being the criterion of cognition and the logit discrete choice model being the criterion of route selection support the conclusion as well, it is also found through the simulations that dissension may due to exact treatment of treatment on the probability of discrete choice model. At the same time, comparisons between experiments and simulations found that the existing mechanism was not sufficient to reflect the fact that travelers tend to choose the shorter route more, and the shorter the more when difference of routes’ length exist, The modified mechanism proposed by this paper reflect the fact better. This study is beneficial for understanding the traveler’s route choice behavior and the causes of traffic congestion.

Lingmin Yang, Rihui She, Jingyi An, Hong Wang, Shunying Zhu

Intersection Traffic Signal Optimization Considering Lane-Changing Behavior Caused Nearby Bus Bay Stop Upstream

Transit-oriented traveling mode is recognized as one of the most effective strategies for improving traveling service level and decreasing travel times, stops and delay. However, the transit system will also bring some new bottlenecks. The influence caused by bus bay stop upstream should be considered for traffic signal optimization. This paper proposes a traffic signal optimization model for intersection and bus bay stop upstream unit, which targets for minimizing traveling time and considering the effects caused by bus bay stop upstream. First, the equivalent volume method is addressed for quantified the influences generating by transits’ lane-changing. Then, the influences are taken into account when solving the traffic signal optimization algorithm. Finally, the proposed optimization model is evaluated using a VISSIM model calibrated with field traffic volume and traffic signal data of the intersection of Qingliangmen Boulevard and Nenjiang Road in Nanjing, China. The evaluation results illustrate that analytical and simulation calculation results have similar performance in reducing traveling delay. Therefore, the proposed traffic signal optimization method performs well at the intersection with bus bay stops upstream.

Rui Li, Xin Xue, Linchao Li, Changjiang Zheng, Jinxing Shen

Resilience Analysis for Comprehensive Transportation Network

Based on resilience theory, considering the security capability, structure capability, operation capability, emergency capability and management level of comprehensive transportation network, from the aspects of security capability, management and service capability of network, the resilience evaluation metrics of comprehensive transportation network is constructed. Meanwhile, the computing method for every index is proposed. Based on the characteristic of qualitative and quantitative combination of resilience metrics, the resilience evaluation method of comprehensive transportation network, which combines the AHP (Analytic Hierarchy Process) and TOPSIS (Technique Order Preference Ideal Solution) is proposed. The result of resilience can provide technical support for improving the reliability and preventing and control the risk of the comprehensive transportation network.

Shuyun Niu, Ji-sheng Zhang, Fan Zhang, Jian Gao

The Edge Importance Evaluation of Compound Network Formed by Comprehensive Transportation Network

On the basis of complex network theory, the edge importance evaluation method of compound network formed by comprehensive transportation network is studied. First, combining the characteristic of comprehensive transportation network, the different network topology extraction methods are analyzed. Then the extraction method of compound network topology is determined, and the compound network of comprehensive transportation network is proposed. Second, considering different transportation ways’ factors of network size, running speed and turnover volume of passenger and goods etc., the weight computation formula of every sub-network topology edge is constructed. Third, dual weighted node degree and weighted node betweenness are chosen as evaluation index which are used to evaluate the edge importance of compound network. Finally, Jing-Jin-Ji region comprehensive transportation network is chosen as empirical study. The result proves that the method proposed in this paper is feasible and effective, and the assessment results are in line with the actual situation.

Shuyun Niu, Jian Gao, Honghai Li

Economic Benefit Optimization Model of Urban Rail Station Based on C-D Function

In order to study the optimal investment plan for urban rail stations under a certain amount of investment, the safe investment is regarded as a production process, “safe value-reduced output” and “safe value-added output” after the reduction of accidents are as benefits and the Cobb-Douglas function have been improved. Employee safe training investment, safe equipment maintenance investment, safe publicity and guidance logo investment, emergency evacuation drilling investment, and security staff salary input have been taken as independent variables to build safe investment in the stations to optimize the model. Taking an example in Shenzhen to verify the type by use of Matlab. The results show that the model is a good reflection of the relationship between the safe investment sub-items of urban rail stations and the economic losses of accidents during the ten years, and the benefits of the optimized investment plan are obvious.

Hua-lan Wang, Jia-ying Xu, Zun-jie Hu, Man Li

Recognition of Fatigue Driving Based on Steering Operation Using Wearable Smart Watch

Given the growing popularity of wearable smart watch with the capability to detect human hand movements, this paper studies the potential to recognize fatigue driving based on steering operation by using a wearable smart watch. The sensor data used includes acceleration and angular velocity data related to drivers’ operation behavior. We analyze the sensors’ data features of smart watch under drivers’ fatigue and normal states, and select 13 principal characteristic parameters by using the method of principal component analysis (PCA). Then the recognition model of fatigue driving based on support vector machine (SVM) is established. The results show that the proposed method recognizes the drivers’ fatigue or normal state more effectively than other methods and its accuracy can reach 83.29%.

Dihua Sun, Yong Huang, Min Zhao, Dong Chen, Weijian Han

Uncertainty in Lanzhou-Xinjiang Railway Track Longitudinal Level Irregularity Degradation

The state of track deterioration is a key factor affecting traffic safety. In order to better study the deterioration of the track state, it is necessary to analyze firstly the uncertainty of track degradation. This paper analyzes the geometric deterioration of railway track and the uncertainty related to the degradation phenomenon based on a series of data collected from the track sections of K820–K840 railway section of Lanzhou-Xinjiang railway line. Firstly, the degradation parameters of the track irregularity are selected as the research object of this paper, and the evolution trend is studied. The linear relationship between the standard deviation of longitudinal level irregularity and the operation time is proved, and the initial standard deviation and deterioration rate are obtained; then, proper probabilistic distributions are fitted using K-S goodness-of-fit test. The lognormal distribution was selected to establish the relevant deterioration parameter model. The uncertainty of the track geometric degradation was also explored.

Ye Yang, Fu-tian Wang

Functional Areas Layout in Logistics Park Combining Traffic Organization by Genetic Algorithm and Fuzzy Clustering

The functional areas layout and the organization of the traffic will influence with each other in logistics park. In this paper, the author studies the method to combine the layout of the functional areas with organization of the traffic so as to make the layout more practical. Firstly, the model for functional areas layout design is established, which is based on traffic organization. Secondly, the solution algorithm is proposed, which includes three parts. The first part is fuzzy clustering analysis which is used to cluster functional areas so as to determine the traffic network factors. The second part is genetic algorithm for layout problem at the functional areas, the author uses three parts of codes to construct the chromosome encoding, which are code for the area, cutting code and sequence code. The third part is traffic organization, compared with genetic algorithm and CPLEX, the author selects shortest path distance for calculation to speed the calculation speed. And CPLEX would be used to calculate the actual distance after the final layout is obtained. Finally, the model and algorithm are applied in the Lianyungang Port Logistics Park to verify the feasibility. Compared with the base layout, the truck distance can be reduced by 13.8%.

Qin Xiang

Route Choice Optimization for Urban Joint Distribution Based on the Two-Phase Algorithm

With the city’s economic development, people have already put forward higher requirement for the city logistics, so joint distribution will attract increasing concern. In the daily operation, route choice is very important for the joint distribution, it will be related to the cost reduction and mitigation of congestion in urban transport. In order to solve the problem about the route choice in urban joint distribution network, the route choice model was established. Because normal algorithm would cost a lot of time, what’ more, it also cannot get the optimal solution. Therefore, this paper provided the two-phase algorithm, which uses greedy algorithm to form the groups and apply ant colony algorithm for optimization. In order to verify the model and algorithm, through the case study, it shows that the unreasonable routes have already been adjusted, and the average line length has declined steadily. Compared with the result before, it decreases by 1.1%.

Qin Xiang

An Integrated Energy-Efficient Scheduling and Train Control Model with Regenerative Braking for Metro System

Rising energy cost and environmental awareness make energy-efficient operation a key issue for metro management. The speed profile and timetable optimization are two significant ways to reduce total energy consumption for metro systems. This paper proposes an integrated speed profile and timetable optimization model to reduce the net energy consumption while incorporating with complex track conditions like undulate gradients, curves and tunnels. The net energy consumption is minimized by force coefficients and coast control for single train movement and accelerating and braking synchronization for multiple trains. An efficient hybrid particle swarm method based on the particle swarm optimization and genetic algorithm is designed to obtain a satisfactory solution. Finally, numerical case studies based on one metro line in Beijing are conducted to validate the energy-efficient performance of integrated model and the results show that the integrated model can achieve a better tradeoff between traction energy consumption and reused braking energy on comparison with individual speed profile and timetable optimization.

Xinchen Ran, Shaokuan Chen, Lei Chen

A Review of the Research on the Entrance Control Method of Urban Expressway

Expressway control is an important measure to solve the congestion of urban expressway nodes and ensures the smooth and efficient operation of expressway lines through the management and regulation of traffic volume. In order to further study the control of expressway, it is necessary to classify and summarize the existing entrance control model. According to the control method, control range, control effect and control complexity, the application model of urban expressway entrance control is classified and summarized according to static, dynamic single- point, multi-ramp coordinated control, internal integrated control and integrated control of expressway and auxiliary road intersection. Then, bases on existing research theories and practices, clears model application optimization technology and modeling ideas, analyzes the advantages and disadvantages of various basic models and improves models. Finally, the urban expressway control is prospected.

Yan Xing, Jin-ling Wang, Wei-dong Liu, Xing-quan Guan, Yang Liu

Numerical Study on the Effect of Driving Distance on the Diffusion of PM2.5 in the Street

The influence of inter-vehicle distance on the diffusion process of PM2.5 in the underlay surface of urban streets is studied. Firstly, the diffusion process of tracer gas PM2.5 is simulated using CFD, and the emission factors of PM2.5 under different vehicle types and speeds is analyzed and summarized. Then, using the improved MIRA vehicle model, a PM2.5 diffusion model of the traveling vehicle at different intervals was established. In the end, POST post-processing was applied to the model, and the PM2.5 concentration field cloud map and the velocity field cloud map around the vehicle body were compared and analyzed to obtain the diffusion rule of PM2.5 emission from the vehicle exhaust gas.

Peng Xu, Mengru Wang, Xi Lu, Junru Han, Qin Gu, Chen Ma

Study on the Speed Limit of Vehicle Stability Under Rainy Environment

The study on the lower limit of adverse weather conditions in China’s current expressways is mostly considered in terms of road conditions and traffic flow, it is mostly based on the parking distance based on speed control research and does not take into account the stability of the vehicle in bad weather. This paper studies the stability of vehicle driving under rainfall conditions and obtains safe driving speed through ADAMS/Car simulation simulation, it provides a reference for the system’s comprehensive establishment of the highest safe driving speed of the highway in the rainy environment.

Peng Xu, Kai Jiang, Xi Lu, Junru Han, Chen Ma, Xinran Xu

Optimization Method of Comb-Shaped Speed Reduction Marking Spacing Based on Variable Space-Time Frequencies

In view of the practical matters that drivers often have traffic accidents on the freeway curves because of speeding, it is essential to improve the traffic security level and reduce the traffic accident rate of highway. And the key aspects are to keep a safe running speed or let the speed down by setting up reduction measures like speed reduction marking. This paper presents a more scientific design scheme of speed reduction markings. Taking comb-shaped speed reduction marking for example, it’s spacing were optimized for further research. First, this paper gives explanations on mechanism of the space-time frequency influence on the drivers’ perception of vehicle speed from the angle of body sensing (mainly visual sense). Second, a mathematical model to describe the relationship between spatial frequency and spacing of speed reduction marking was established. After defining comfortable acceleration, maximum safe speed, etc. aiming at different freeway curves, the model can obtain specific value of speed reduction marking’s spacing. At last, to explore the practical effects on drivers’ speed perceptions, this study simulates highway scenes by 3Dmax. Those road surfaces are patterned with speed reduction markings set in different space-time frequencies. And then evaluates the deceleration effects of those speed reduction markings by comparative analyzing experimentalists’ reactions recorded. The experimental results shows that the deceleration effect can be improved effectively by decreasing the spacing of speed reduction markings, namely increasing the frequency. In addition, variable space-time frequencies give drivers illusions that the running speed keeps changing. In general, speed reduction markings set in variable space-time frequencies have better effects on speed reduction.

Liangjie Xu, Zhijun Wang, Ruonan Zhou, Hua Fan

Summary of Research on Exit Control of Urban Expressway

With the rapid development of urban expressway, the ramp congestion of expressway is frequent, and the ramp control of expressway exit has been widely concerned. There have been more research and application on the control of expressway exit in China, and the control mode is mainly focused on the adjustment of the adjacent auxiliary road intersection on the ramp. In order to continue to find ways to solve the problem of congestion on exportation of expressways, and provide reference for the research of expressway exit control, the existing control methods are summarized. Although most of the exportation control is adopted to adjust the signal of the auxiliary road at present, the object of the control is not the same. Therefore, the object different according to the control means can be divided into three kinds: the priority of the ramp, the dynamic adjustment of the auxiliary road and the cooperative control of the multi system. This article will summarize and analyze the existing research results, and put forward some views on the future research and development.

Yan Xing, Shuai Bian, Wei-dong Liu, Xing-quan Guan, Yang Liu

Study on Community Detection of Shipping Network Based on Modularity

Shipping network is a kind of typical complex network, the network structure is one of its important features. This paper takes the research of community structure of shipping network as the object, constructs the Newman fast algorithm based on modularity, and choose “The twenty-first Century Maritime Silk Road” shipping network as the case, which is unweighted and undirected shipping network, and composed of 453 ports and 3444 edges. From the perspective of shipping network connectivity, the Newman fast algorithm is used to calculate “The twenty-first Century Maritime Silk Road” shipping network. The structural properties of this shipping network can be obtained. There is only one core community in this shipping network, which is leader community, and consists of 173 ports. Their degree follows the power-law distribution. Others are non-core communities. It shows that the “The twenty-first Century Maritime Silk Road” container shipping network owns huge community structure with core nodes. The conclusion of the research is a reference to the relationship between “The twenty-first Century Maritime Silk Road” shipping network and the ports along its line.

Xuejun Feng, He Jiang, Liu-peng Jiang

Research on Factors Affecting the Effect of Chinese Port Transformation and Upgrading

Chinese ports are in a critical period of transforming development methods. It is necessary to scientifically realize the transformation and upgrading of ports. However, the factors affecting the port transformation and upgrading are complex, multi-layered and difficult to quantify. All kinds of influencing factors and their relationships are considered comprehensively and a structural equation model for the influencing factors of port transformation and upgrading is established in this article, based on the structural equation model (SEM). The effect of each influencing factor on port transformation and upgrading is quantitatively analyzed, and then the key influencing factors are identified. This was accomplished by conducting the data sampling and the questionnaire survey. This article provides decision-making basis for port transformation and upgrading, which is of great significance.

Xuejun Feng, Jiaojiao Wang, Liupeng Jiang

Study on the Status Quo and Development of Rural Highway Traffic in South Jiangxi

In recent years, with the strategy of revitalizing and developing the country’s south Jiangxi region, the rural transportation in southern Jiangxi has been greatly improved, but it is still in extensive development. The rural highway traffic in south Jiangxi is not optimistic. This paper analyzes the status quo of rural highway traffic in southern Jiangxi, and comprehensively analyzes the characteristics of rural highway traffic in southern Jiangxi from the aspects of highway grade, vehicle problems, terrain and planning, and puts forward two countermeasures for local conditions and talent reserve from the perspective of long-term development.

Qing-Zhang Yuan, Liang-Song Zhi, Wang Jian

Analysis of Child Pedestrians’ Unsafe Road Crossing Behavior at Intersections in School Zones

The characteristics of child pedestrians’ unsafe crossing behavior and the effects of age, gender, accompanying adults and peers on their crossing behavior were examined in this study. Three signalized and one unsignalized intersections in elementary school zones were selected to conduct the observations. Chi-square tests were used to examine the four types of child pedestrians’ unsafe crossing behavior. Children in Grade 4–6 group committed more walking outside of crosswalk and running to cross the road behavior than children in Grade 1–3. Boys in Grade 4–6 were more likely to run and cross against the red light than the girls in the same age. Children accompanied with peers were more likely to walk outside of crosswalk and not look both directions before crossing. Children accompanied by grandparents were less likely to run to cross the road, but children who crossed without adults or peers committed more running behavior. Children showed more unsafe crossing behavior at signalized intersection than at unsignalized intersections. Age, gender and accompaniment have different effects on elementary school children’s road crossing behavior. The insights from this study may provide reference for researchers, educators and decision-makers, to understand the characteristics of children’s road crossing behavior and improve their road safety.

Lianning Fu, Nan Zou

Investigating Private Cars Idling Behavior in Urban Areas

The rapid mechanization in China results in excessive adverse effects recently, such as traffic congestion and air pollution. Affected by the negative effects, an increasing number of citizens decide to use their private cars only at a certain time, which leads to the urban private cars idling (UPCI) phenomenon. In order to investigate the UPCI behavior and its influence factors, this paper, taking Nanjing city in China as a case study, conducted a detailed survey including 279 private car owners. A logistic regression model was developed to investigate the impact factors related with UPCI. The result of regression indicated that the number of children in a family was an impeding factor which caused the fewer UPCI behaviors. The smaller job-housing distances and independence on vehicles, however, aggravated the UPCI phenomenon. The results of this study are beneficial to understand the UPCI behavior, and provide useful information for the effective urban transportation demand management (TDM) and necessary guidance for urban private car purchase and usage.

Lu Xing, Jie He, Chen Zhang, Ziyang Liu, Hao Zhang

Study on Traffic Safety Security System at the Entrance of Middle and Primary School

As a focal point of traffic safety, school area has received extensive attention. Especially in the peripheral areas of primary schools. During the period of schooling, motorcades, motorcycles, and non-motor vehicles are accumulating at school gates, and a large number of pedestrians are mixed there too, which cause traffic disorder. In addition, primary and secondary school students have their own characteristic of crossing the street, so the security of the elementary school area needs more targeted measures. This article starts with the analysis of road traffic characteristics and the traffic accident characteristics in front of primary and secondary schools. Combining typical real cases, this paper proposes security protection measures from traffic organization, traffic enforcement, and transportation facilities. Further constructing a traffic safety guarantee system provides an important guideline for ensuring the safety of traffic in front of primary and secondary schools.

Fengchun Han, Yifan Jiang

A Novel Pedestrian Orientation Estimation Method for Autonomous Driving

Pedestrian orientation estimation is a vital component of autonomous driving system. The challenging factors for pedestrian orientation estimation include pose variations, fast motions, background clutters and crowded people flow. In this paper, we explore a novel pedestrian orientation estimation unified framework, which is based on a monocular camera. Firstly, pedestrian images are normalized to the same size, then extract histogram oriented gradient feature (HOG) which is one of the most effective image descriptor. In addition, we utilize structured Support Vector Machines (SVM) to generate binary classification result. Moreover, Error Correcting Output Coding (ECOC) framework combines with structured SVM to deal with multi-class classification problem. Finally, we conduct our approach on public pedestrian datasets and achieve competitive performance.

Ming Gao, LiSheng Jin, Yuying Jiang, Baicang Guo

Operation Optimization Considering Order Cancellation and Ticket Discount for On-Demand Bus System

The emergence of multi-source and mass travel data and the gradual maturity of acquisition methods make the realization methods of travel demand more diversified. The on-demand bus is a pattern that can meet the needs of personalized and high-quality travel. This project proposes an on-demand bus system based on response to random users’ real-time requests. Under the condition of fixed origin points and destination points, taking the minimum total waiting time of passengers and the maximum profit of the bus as the goals, a model based on the variables of bus fare discount and request valid time is established, and LINGO and the actual car-hailing data are used to calculate and check the model. Through calculation results and the comparison with the traditional bus and the express, the on-demand bus system has shorter travel time than the traditional bus and costs less than the express. Thus the research can be thought to provide a scientific basis for the establishment of the on-bus bus system, and provide theoretical support for further research.

Haipeng Shao, Xingying Chen, Yuxuan Wang, Sufeng Wu

Research on the Satisfaction Degree of Rookie Station Based on Centrality Analysis—Taking Shenzhen University as an Example

In recent years, more and more colleges and universities join the rookie station, however, the users’ satisfaction with the service is not very high. This paper takes rookie station user satisfaction degree as the cut-in point, using the centrality analysis method of social network analysis, taking the actual investigation and the network questionnaire as the data obtaining way, exploring the network relationship between the users and the satisfaction factors of the rookie station, and then provides the improvement plans for the service quality of the rookie station. And taking the rookie station of Shenzhen University as an example, through 100 effective questionnaires, using UCINET software, the centrality of the factors are analyzed. The results show that campus users pay more attention to the tally speed and spatial layout, but they pay less attention to the shipping charge standard and pick-up mode.

Hui Yin, Liang Zou

Evaluation Method of Drivers Vision Impacts from Green Belts of Arterial

As an important part of the cross section of road, the green belt of urban road has heavy impacts on the drivers’ visual environment. Green belt directly relates to traffic safety. But the research on this area is only carried out from the aspects of color and monotonicity. Few research can be found which is about impacts indexes. In this article, the impacts model of green belt is established. The green belts impact value of the different level and different section is obtained by expert method. In order to validate the model, an eye movement instrument (SmartEye) is adopted. The data of impacts indexes can be obtained in SmartEye. Then, ErgoLAB package is used to identify the drivers’ gaze points during the course of the experiment and to generate the view distribution map of the gaze area. After this, the experiment in driving simulator dome under variable traffic flow condition is carried out to modify the model built above. At last, a recommended rating grade standard is presented.

Yu-gang Sheng, Wan-lu Song, Jian-xiao Ma

Study on Urban Road Network Capacity Based on Self-organized Criticality

With the rapid growth of the socioeconomic, urban traffic congestion has become acute. In this paper, we studied the internal mechanism of congestion by analyzing the road network capacity, and conducted a qualitative and quantitative research on road network capacity of Beijing. By applying the theory of self-organized criticality, we analyzed the running status data and traffic congestion index of the road network of Beijing from 2008 to 2012, concluding that the road network of Beijing has the power-law characteristics under the relevant scale, following this, the concept of road network capacity based on self-organized criticality has been proposed. Moreover, we established a calculating model of road network capacity based on sandpile model and the theory of cellular automata, simultaneously made a simulation experiment of sandpile model for a specific road network of Beijing. The obtained results show that our model can be applied as an effective approach to calculate the capacity of road network.

Zhenlin Wei, Shilong Li, Ailing Huang, Jing Han

Transit Signal Priority Optimization for Urban Intersection with the Effects of Downstream Bus Stop

Traffic flow characteristics of intersection will be directly affected by downstream bus service stop, therefore, the effect caused by downstream bus stop should be focused on for optimizing transit signal priority plan of urban intersection. Transit signal priority optimization control unit including signalized intersection and downstream bus stop is identified. Transit signal priority green extension optimization model is proposed, which can optimize transit priority signal timing plan by minimizing total passengers’ travelling delay of the whole control unit. Optimized transit priority signal timing plan is determined by using a signal phase allocation method. The proposed model is evaluated using a VISSIM-based simulation platform calibrated with field traffic volume and traffic signal data of Hangzhongmen Boulevard at Beiwei Road and downstream bus stop in Nanjing, China. The results indicate the promising performance (8.38% passengers’ travelling delay reduction) of the proposed transit signal priority optimization phasing plans, and the evaluation simulated by VISSIM-based platform also reveal the performance. Consequently, the proposed transit signal priority optimization strategy can significantly improve the traveling efficiency of urban transit system.

Yuexin Chen, Rui Li, Wei Cao, Changjiang Zheng

Speed Limit Analysis for Street in Residential Block Based on Minimum Network Costs

With the implementation of government’s new guideline on block system, the gated communities will be gradually opened. However, the entrance of a large number of social vehicles into the residential district produces traffic problems such as environmental problems and noise problems. This study proposed a before-after analysis of speed limit for streets in residential block. Traveler time value model, automobile exhaust treatment cost model and traffic noise prevention cost model are considered to minimize the general network costs, and the best speed limit is obtained. Taking the Liaohe district in Harbin as an example, 15 is the initial value and 5 is the interval value, then the five values are 15, 20, 25, 30, 35. The daily total costs of the study area are 298.99, 309.42, 324.46, 326.27, 350.87 yuan correspondingly. 15 is the corresponding value of the minimum total cost. Therefore, it can be set as the speed limit.

Xiaoning Wang, Shaosha Fan

Research on Evacuation Model of Evacuees with Luggage

Emergency evacuation in large traffic facilities has been important issues of social security. Current evacuation models less consider the situation, which many passengers carry luggage in large transportation hub. This paper proposes a new cellular automation model according to characteristics of luggage. The distance parameter, spatial parameter, empty parameter, obstruction parameter, luggage following rules and new route created rules are introduced in the model. This paper mainly analyzed the effects of carrying or leaving luggage on evacuated pedestrian flow. Evacuation time is verified based on the simulation under the different space occupancy and different ratio of pedestrian with luggage. The article takes a waiting area in railway station as an example to simulate. The result shows that if moving with luggage, as the initial space occupancy grows, the increase of the proportion of people with luggage has more obvious impact on increase of evacuation time; Besides, when pedestrian space occupancy surpass 60% and the ratio of pedestrian with luggage exceed 50%, due to abandoned luggage loss of mobility, the effect of hindering the subsequent pedestrian movement become stronger. Carrying luggage rather than leaving luggage may make overall evacuation time shorter.

Shuang Chen, Nan Zou, Fan Wu

Experiment on Destination Choice Game

A fundamental issue in traffic science is to understand the behavior of traffic participants. Ether to theoretically model the traffic phenomenon or to analyze the complex operation process of the actual traffic system, the underlying mechanism of individual traffic decision-making behavior has always been the focus of relevant scholars. Many researches on traffic decision-making have been done, but the research on destination choice which is the most basic motivation for individual travel is still lacking. In this paper, we establish a simplified laboratory experiment to study individuals’ destination choice behaviors. Considering that increasingly diverse traffic information is provided to residents through the Internet, two treatments are set up to explore the influence of feedback information on human behaviors. In a lot of real scenarios, the individual is most likely to take the degree of congestion into account, so we set the payoff of each destination to a form negatively related to that degree. Experimental results demonstrate that aggregate behavior would achieve user equilibrium rapidly no matter whether there is feedback information or not. Moreover, the feedback information has a certain effect on individual choice behaviors, which is a socially significant discovery. We believe that the results can be combined with other models for comprehensive modeling, which will be helpful to the traffic planning and management in the future.

Haoran Li, Chuanci Cai

Alleviate Traffic Congestion and Reduce Energy Consumption by Setting a Peak-Only Bus Lane on a Bottleneck-Constrained Highway

With the great popularity of the public transit which is a kind of green transportation, peak-only bus lane is gradually implemented on the corridors of large cities to make the bus runs a privilege to go through the bottleneck, then the bus runs can keep a faster speed which will definitely attract more potential commuters. And thus this will alleviate the traffic congestion caused by private cars and reduce the energy consumption and emissions to some degree. In this paper, we investigate the impact of the peak-only bus lane on alleviating traffic congestion and reducing energy consumption by using bottleneck model with auto and bus modes. The peak-only bus lane will occupy the bottleneck’s capacity by a fixed amount just within a fixed peak hour period. While the capacity of the bottleneck for auto mode commuters is time-varying within the whole commuting period. It is assumed that the mode choice and the departure time choice are governed by the user equilibrium criterion and nobody can decrease his/her total cost by adjusting the mode or the departure time in the equilibrium state. The departure rates for both bus and auto modes are derived analytically. The travel cost and energy consumption are analyzed with different bus dispatch frequencies and bus lane capacities. The numerical results showed that the setting of the peak-only bus lane will descend the number of commuters who choose the auto mode, and thus decrease the system’s total travel cost and energy consumption to certain degree. The optimal setting of the road resources and the frequency for peak-only bus lane was also investigated. We believe that the results are helpful to the planning and operating of peak-only bus lane, and it’s useful to alleviate traffic congestion, reduce the energy consumption and protect the environment.

Xingfei Wang, Xingang Li

Research on Public Transit Priority Level and Travel Cooperation Level

Public transit priority strategy is a key measure for alleviating urban traffic congestion problem, but there are few researches on public transit priority level. The connotation of public transit priority level is analyzed. Public transit priority level includes travel time priority level, travel expense priority level, travel comfort priority level and comprehensive priority level. Public transit travel time priority level is analyzed at different travel distance, different public transit carrying speed and car travel speed. Questionnaire survey based on traveler’s acceptance is conducted. The relationship between travel cooperation level and travel time priority level, travel expense priority level, travel comfort priority level is obtained. The results shows that the key of improving travel cooperation level is to moderately increase car travel expense, increase public transit travel time priority as far as possible and increase public transit travel comfort as far as possible.

Chengming Zhu, Zhenhua Mou, Changxi Ma, Yugang Wang

An Intelligent Road Waterlogging Sensor for Traffic Safety: Principle and Algorithm

Road waterlogging affects the behavior of driver-vehicle unit, thus road waterlogging perception technique is highly important to traffic safety. In this work, a pressure-guiding waterlogging perception method is introduced, and this sensor is modeled based on the principle of differential pressure to realize the real-time measurement of the road waterlogging level. In order to decrease non-linear measurement error of this waterlogging sensor under complex road environment, this paper proposed an adaptive correction algorithm according to the principle of data fusion. The experimental results show that this proposed method has much higher stability and measurement accuracy than typical measurement methods of the road waterlogging level.

Qin-jian Li, Feng Chen, Huang-qing Guo

Travel Decision of Shared Bike Based on Subway Transfer

Subway is an important part of Public transportation. To increase the attraction of subway, solving the problem of transfer in the beginning and the end of subway is the most important. The paper points out that how shared bikes make it convenient for the transfer of subway by the trip decision of travelers. According to the comparation between shared bikes and other traffic modes, the paper creates a function model by using the difference value between the travel time of two traffic modes. And the paper indicate that search time is an important factor whether most travels will choose shared bikes or not. And then for the improvement of search time, the paper makes a suggestion at both the government and the corporate level, which is aimed to make it convenient to transfer between shared bikes and subway.

Yongneng Xu, Ren-fei Wu, Qiao Qiao, Zhu-ping Zhou

Evaluation of On-Street Parking Effectiveness Based on Lean Time Management

An on-street parking management concept based on lean time management was proposed. The on-street parking evaluation index system based on lean time management is constructed from three aspects: parking fee, parking duration, facility and management. Established an on-street parking time-entropy model based on lean time management, and evaluated the parking effect using the system and model. The main factors influencing the on-street parking effect can be found from the evaluation results, which can provide the basis for further parking planning.

Jia-li Ge, Wen-hong Lv, Peng-fei Wang, Guo-juan Wang, Lu-li Liang

Accurate Identification of Accident Black Point Based on Hazard Attribute Analysis

After more than 30 years of rapid development, China’s expressway has entered a stage of comprehensive long-term development. The safety problem of expressway has become a hotspot in the development of expressway. The accident black points as the focus of research on highway safety issues are directly related to the improvement of highway safety conditions. In this paper, the risk index is used to characterize the risk of accident multiple sections. Based on the analysis of the risk attributes of expressway accidents, the risk curve model of accident points is established. Considering the superposition of danger, Risk curve combination model, and then to promote the accident multiple point of the risk curve model, so as to establish the full range of highway safety function and curve model; to determine the accident black points to determine the threshold, combined with the highway risk curve model and determine the threshold, The establishment of highway accident black point recognition model, to achieve accurate identification of accident black points.

Jianyou Zhao, Yongmei Xue, Yao Peng, Chuang Zhou

Spatio-Temporal Autocorrelation-Based Clustering Analysis for Traffic Condition: A Case Study of Road Network in Beijing

Traffic congestion is an increasingly serious problem worldwide. In the last decade, many cities have paid great efforts to establish Intelligent Transportation Systems (ITS), and a large amount of spatio-temporal data from traffic monitoring system is also accumulated. However, with the devices and facilities of ITS getting completed, effectiveness of ITS practices is always restricted by traffic information fusion and exaction technique. Traffic condition-determining is a crucial issue for Advanced Traffic Management Systems, on which many researchers have done profound studies. The existing studies are mostly focused on traffic condition recognition at a certain road and time point; while in practice, it’s more meaningful how different kinds of traffic condition are correlated and distributed in space-time. Therefore, in this research we present an improved spatio-temporal Moran scatterplot (STMS), by which traffic conditions are pre-classified into four types: homogenous uncongested traffic, heterogeneous uncongested traffic, homogenous congested traffic and heterogeneous congested traffic. Then at the basis of STMS, a novel spatio-temporal clustering method combining pre-classification of traffic condition is proposed. Finally, the feasibility and effectiveness of the clustering methodology are demonstrated by case studies of Beijing. Result shows that the proposed clustering method can not only effectively reveal the relation of traffic demand to road network facilities, but also recognize the road sections where congestion originates or gets alleviated in the network, which provides foundations for traffic managers to alleviate congestion and improve urban transport services.

Wei Wei, Qiyuan Peng, Ling Liu, Jun Liu, Bo Zhang, Cheng Han

Passenger Flow Prediction for Urban Rail Transit Stations Considering Weather Conditions

Precise prediction of urban rail transit passenger flow is essential for the development of organizing plans by the rail transit management and operation department, and also is the fundament to achieving passenger transport guarantees. This study collected Ningbo rail transit Route 2 passenger flow data and candidates of key driving factors including station type, population and employment position density, transfer facilities, main land area within an 800 m radius, particularly considering weather conditions, and then Random Forest was applied for passenger flow prediction. The prediction results show that the models considering the weather factors is superior to the models without consideration, mean absolute deviation (MAD) and mean absolute percentage deviation (MAPD) are reduced by 14.40 and 57.55%, respectively. The model involved weather factors is more accurate under hot and heavy rain weather conditions. Employment position, population density and commercial service facilities land area within an 800 m radius of the station, are the most important factors influencing the passenger flow, while average temperature is more likely to affect the passenger flow than precipitation. These results suggest that the passenger flow forecasting model based on random forest can achieve rapid calculation under different weather conditions, and provide important data basis for urban rail transit passenger flow density warning, passenger flow guidance and operation scheduling.

Kangkang He, Gang Ren, Shuichao Zhang

An Algorithm for Searching Freeway Speeding Unlicensed Vehicles

A timeless retrospective algorithm for finding unlicensed vehicles on highway speeding is proposed. The algorithm mainly uses the images captured by the freeway capture device to obtain the speed information of the vehicles, and the distance and speed of the vehicles. The time backtracking method is used to determine when the vehicle enters the entrance, then screen the image to determine the illegal vehicle information. The application of the algorithm is implemented through a C language program. The results show that freeway speeding unlicensed vehicle search algorithm can search for speeding unlicensed vehicles and alert freeways for unlicensed speeding.

Lu-li Liang, Wen-hong Lv, Peng-fei Wang, Jia-li Ge, Guo-juan Wang

Study on the Behavior and Psychology of Pedestrian Traffic Violations on the Crosswalk

Pedestrian traffic violations on the crosswalk are common in many Chinese cities. As the weak side within many traffic participants, pedestrian safety is often not guaranteed. In order to reduce pedestrian violations and improve pedestrian safety fundamentally, behavior and psychology of pedestrian crossing the street should be studied and it is addressed in this paper. Firstly, a questionnaire survey was carried out to collect data. Then, frequency and causes of pedestrian violations, pedestrian preferences to crossing facilities were analyzed using mathematical statistics. Based on the analysis above we find that pedestrian violations is related to the job style, and the main reason for pedestrian violations is the psychology of saving, conformity and dependence. Finally, some suggestions about enhancing pedestrian safety education and strengthening pedestrian traffic management are proposed.

Ya-xiong Han, Yue-ying Huo

Cooperative Optimization of Seat Control and Ticket Price for High-Speed Rail Passenger Transport

With the rapid construction of the high-speed railway in China, the operational efficiency and revenue performance are getting more and more attention from operators. In this paper, the idea of revenue management is adopted to adjust the passenger flow of parallel trains through differential pricing considering the preference of passengers for different parallel trains. Based on utility theory, the Multinomial Logit model is used to describe passengers’ choice behavior among parallel trains, and a cooperative optimization model for ticket price and seat control of high-speed rail network with multi-train and multi-stop stations is established. At the same time, the optimization strategy of differential pricing and seat control of parallel trains is obtained. The validity of the model is proved by numerical experiments based on the train of Beijing-Shanghai high-speed railway. The optimization polices of this model in this paper can provide optimization strategy for the revenue management of high-speed parallel trains and enrich the synchronous optimization theory of capacity control and pricing in revenue management.

Zhen-ying Yan, Fang Gao, Ping-ting Zhang, Yujia Zhang, Hui Liu, Xiao-juan Li, Jian-wei Ren

Influence of Lane Change on Driving Behaviours in Traffic Oscillations Based on Vehicle Trajectory Data from Aerial Videos

Many Car-Following (CF) models and analysis methods have been applied to many practical and theoretical studies, relatively, only a few in Lane-changing (LC) development. This research aims to fill the gap by proposing a new tracking lane-changing trajectory and theoretical method to study date. In this paper, we employed Unmanned Aerial Vehicle (UAV) to record the moving data of the vehicles in Nanjing, China. Based on existing research methods, we study the influence of lane-changing (LC), a comprehensive data analysis indicates that drivers show similarity of their lane-changing habit but with variety, and different drivers’ lane-change trajectory data show different lane-change “personality” including aggressive and timid characteristic. By analyzing the data and comparing it with the related research based on NGSIM, we can obtain the corresponding changes in driver characteristics: (i) A timid (aggressive) driver tends to become less timid (aggressive) or convert to slightly aggressive (timid) after experiencing LC; (ii) These changes were systematic and suggest that drivers tend to become more aggressive (characterized by decreasing average time headway after LC) perhaps to prevent another LC occurring. The research conclusions of this paper are similar to those of the existing research results, but also have some innovation points, so it can be proved that the data extraction method and the theoretical analysis method in this study are reasonable and innovative. Therefore, what we found in this paper are significantly helpful to study the characteristics of Chinese drivers, and which have enlightening effect to intelligent transportation system (ITS), unmanned driving and other new technology application in traffic field.

Qian Wan, Guoqing Peng, Zhibin Li, Wenyong Li, Qianqian Liu

Discriminant Model of Driving Distraction During Mobile Phone Conversation Based on Eye Movements

In order to investigate the characteristics of drivers’ eye movements during distracted driving caused by mobile phone conversation and establish a driving distraction discriminant model, a driving simulation experiment was conducted. The eye movement index data were collected by eye tracker under different traffic scenes which include normal driving and perform simple or complex conversation secondary task on the urban road and freeway, then the variance analysis was used to analyze the characteristics. Finally, according to the characteristics of drivers’ eye movements, a driving distraction discriminant model based on fisher discriminant analysis was constructed for different road types. The ANOVA results showed that the effectiveness of road type and conversation task on the cumulative proportion of the driver’s focus on the area of interest in the front road is not statistically significant. However, the average duration of the driver’s attention under urban road scene is significantly higher than that of the freeway, and with the increasing of difficulty of driving task, the average duration of attention increased significantly. In addition, the road type and conversation task significantly influenced the change range of pupil area. The accuracy rate of the discriminant model is 75.2% for the driving distraction on urban roads, and 78.3% for the distraction on freeway.

Lian Xie, Min Duan, Wenyong Li

Study of a New Method of Traffic Organization in Reconstruction and Extension of Chang-Zhang Expressway

Through the study of a new method of traffic organization to reconstruction and extension plan for the reconstruction and extension of the Chang zhang Expressway, from the aspects of program design, emergency response and security measures in the implementation process, the system summarizes the advantages and disadvantages of the transportation organization management for the reconstruction and expansion of the Chang zhang Expressway, and provides reference cases for the subsequent reconstruction and extension of similar highways.

Yazhen Chen

The Research on Comprehensive Safety Analysis and Improvement Measures of Changzhang Expressway Yaohu Bridge and Houtian Terminal Interchange: Based on Lane-Changing Behavior

The bridge has a strong closure itself and such as the factors that the bridge is high above the ground, which makes it difficult to rescue after the traffic accident. Because of the complexity of the traffic situation, the terminal interchange is the traffic accident prone area. The frequent incidents of expressway bridges and terminal interchange have severely affected the expressway safety, which has becomes one of the bottleneck of the freeway safety. Based on the characteristics of vehicle operation on the Yaohu bridge from Nanchang to Zhangshu expressway and Houtian terminal interchange, this study researched service level and the vehicle running status in weaving section, and then put forward the people-oriented of traffic management strategies and improvement measures which would significantly improve the safety level of large Bridges road and traffic efficiency.

Chen Chen, Yazhen Z. Chen

Study on the Stability Control Strategy for Distributed Driving Electric Vehicle

This paper describes a stability control strategy for four wheels distributed driving electric vehicle (4WD). The stability algorithm consist of two parts: (1) The upper hierarchical controller that determine the required yaw moment which used to maintain the vehicle stability; (2) The lower hierarchical controller that distribute the driving or braking force of each wheels. The upper hierarchical controller calculate the yaw moment through sliding model theory which take account into the error between actual value and idealized value for yaw rate and side slip angle. The lower hierarchical controller distribute the required yaw moment by adjusting braking or driving torque based on tire load condition. Firstly, the required yaw moment is preferred to distribute by the hub wheel motor. Then the hydraulic brake system compensates for the required yaw torque, when the hub motor outputs the maximum torque. Numerical simulation studies have been conducted to evaluate the proposed vehicle stability control strategy. The simulation results demonstrated that the proposed stability control strategy can improve the vehicle handling stability and driving safety.

Deng Hai, Xianyi Xie, Lisheng Jin

Regression Tree Model of the Scale’s Dynamic Adjustment of Cruising Taxicab Capacity

Based on the taxi operation datasets from Taxi Information Management System in Ningbo City, a regression tree model for the scale’s dynamic adjustment of cruising taxi capacity was established by considering the average daily loading time of single taxi, mileage utilization and other indexes. The scale’s dynamic adjustment mechanism of cruising taxi capacity and thresholds standard of key indicators were proposed by coupling the functions on the balance between supply and demand and the importance ordering relationship of indicators, which consisted of the taxi ownership per person, the sharing ratio of taxi in public transport trip structure, and other indexes. The results indicate that, (1) in the three-layer structure of regression tree; mileage utilization has the strongest effect on the scale of cruising taxicab capacity. Then the average daily revenue of single taxi, the average waiting time of single taxi’s carrying, the average operation time of single taxi, and the revenue per 100 km have the stronger influence which decreased progressively. And the average daily loading time of single taxi is chosen as the third layer of classification indicator; p-values of the indicators in every layer are less than 0.05 and all passed the significance tests. The standard error and the ratio of mis-discrimination between training and testing samples are 6.13% and 0.07 which indicate the overall accuracy of model is better. (2) When mileage utilization is less than 0.6179 and the average daily revenue of single taxi is less than 798.38 Yuan, the scale of cruising taxi capacity is surplus and need to be reduced. (3) When mileage utilization is more than 0.6774 and the average waiting time of single taxi’s loading is more than 259.09 s, the scale of cruising taxi capacity is insufficient and suggested to increase 463 taxies.

Xiaofei Ye, Min Li, Xuan Li, Lili Lu, Yu-ming Jin

Impact of Road Alignment on Lane Departure: A Driving Simulator Study

Lane departure is a major cause of side-swipes, rear-end collisions, and crashes. Road curvature, as an important part of linear road design, plays a vital role in lane departure. Based on study of the Curve radius and slope of the road, the linear parameters can be optimized to reduce the probability of lane departure. The curvature radius and slope of the road are designed in UC-winRoad and multiple experiments through a driving simulator are performed to output the evaluation data. Based on the radius of curve, slope, and turning direction, numerical analysis of the lane offset are proposed. The relationship between lane departure and road alignment is obtained by analyzing the |P1| value after fitting the vehicle trajectory. The study found that the right-turn curves have a larger lane departure than the left-turn curves, and that too small and too large a curve radius will result in a large lane departure.

Weiwei Guo, Mengqi Ren, Jiyuan Tan, Yan Mao

Research on Driving Fatigue Level Using ECG Signal from Smart Bracelet

Fatigue level was studied using ECG signals collected from smart bracelet, and the data collected from the smart bracelet could reduce the interference to the driver during the experiment, increase the accuracy of the data. In order to accurately fatigue level, the algorithm of driving fatigue level was proposed based on multi-index fusion theory. Aiming at the missing status of the comprehensive indicator T value from principal component analysis, BP neural network was used for data compensation. The threshold of fatigue level was determined on the basis of the peak trough of the comprehensive index T value. Based on experimental analysis, it was found that the algorithm can effectively identify the wide awake and severe fatigue states when the data was missing.

Jiyuan Tan, Xiang-yun Shi, Weiwei Guo

An Analysis of the Travel Patterns of Pilgrimage Groups in Lhasa Tibet

Religiously-influenced pilgrims are commonly seen in Lhasa, a political and cultural center in Tibet. This study observed the travel modes of pilgrims in Lhasa between 2011 and 2017. Information was gathered using questionnaires and interviews. Travel modes of pilgrims and non-pilgrims were compared to identify each group’s regular patterns. The study assessed differences in the characteristics of the Pilgrims’ travel behavior at different ages, and differences in the behavior of pilgrims with different employment statuses. Given the significant differences among pilgrims’ backgrounds, surveys were conducted with subjects of different age groups and employment types. The study’s conclusions represent the experience of local pilgrims. Transportation management departments can use this information to better understand the travel needs of pilgrims and provide a higher standard of travel services to ensure the smooth conduct of the pilgrimage. The results of this study also provide a reference for research about pilgrims in other areas, particularly in inhabited areas in Tibet. It can also provide quantitative data to support religious study in Tibet.

Gang Cheng, Shu-zhi Zhao, Zong Wang

Research on Drivers’ Cognitive Level at Different Self-explaining Intersections

One demand for road is the ensurance of self-explaining, under which means road users can make correct subjective classifications and expectations of road environment. Based on quantification of driver’s driving cognitive behavior and the self- explaining road theory, this paper designs road environments with different self-interpretation levels as experimental scenes. Through a driving simulation experiment, the changing process of driver’s cognitive workload level is simulated based on Hidden Markov Model. The Hidden Markov Model identifies the driving intention under the combined working conditions, thereby judging driving awareness of the road environment, and evaluating the self-interpretation level of each experimental scene.

Wuhong Wang, Shanyi Hou, Xiaobei Jiang, Qian Cheng

A Novel Multiple Object Tracking Algorithm for Autonomous Vehicles

Multiple object tracking is a vital task for autonomous vehicle environment perception. In this paper, we design a novel multi-object tracking method for autonomous vehicles. In the detection section, we utilize popular Faster-RCNN as our baseline method. Then, in data association, we combine appearance, motion, and interaction model to build a unified feature descriptor to explore the nature of tracking object. We evaluate our algorithm on a popular and standard benchmark and compare with the state-of-the-art methods. The results denote that our algorithm achieve good performance at high frame rates.

Hai Deng, Ming Gao, Li-sheng Jin, Bai-cang Guo

Study on Routing Optimization Model of Container Sea-Rail Intermodal Transport Based on Transit Period

Container sea-rail intermodal transport is one of the organizational forms of multimodal transport. It refers to providing an integrated container transport service by the effective convergence of water and railway transportation. It has long industry chain, high resource utilization, and good comprehensive benefits. On the basis of considering transit period, this paper proposes a route optimization model of container sea-rail intermodal transport by taking the minimization of total cost as the objective function. At the same time, this paper increases the constraints on transport capacity and transfer capacity. Finally, combining with a numerical example, the model is solved by optimization software. A container transport scheme with relatively least total cost meeting the transit period limit is acquired, which proves the feasibility of the model.

JunXiao Liu

Passenger Flow Prediction Model of Intercity Railway Based on G-BP Network

Inter-city railway as the city’s comprehensive transportation system, the development of urban industrial economy and the image of the overall improve greatly boost. However, scientific and reasonable forecast traffic is the focus on the study of the inter-city railway construction project, which aim is to obtain the characteristics and rules of passenger flow, planning area to provide comprehensive system for railway planning and the actual resources and foundation of real and reliable data. Based on the grey relational analysis method influence the traffic data and the relationship between influencing factors, choose the main influence factors of traffic influence factors of the BP neural network model is established. Finally combined Lanzhou to Zhongchuan Airport inter-city railway project to traffic prediction research and survey data, it is concluded that the influence factors of the BP neural network model has good predictability to the traffic.

Hai-lian Li, Meng-kai Lin, Qi-cai Wang

Comparative Study on Value of a Statistical Life in Road Traffic Based on Mixed Logit Model

In order to further improve the accuracy of evaluation models on value of a statistical life (VOSL) in road traffic, four mixed logit (ML) models of route-choice with truncated normal distribution and lognormal distribution were used to construct VOSL models. A route-choice questionnaire was designed by the stated choice method, and the traffic survey was carried out in Dalian with survey data obtained. Monte Carlo simulation algorithm was used to calibrate parameters by 150 simulations, and the 4 ML models were analyzed comparatively. Finally, the VOSL estimate of private drivers in Dalian and its distribution function were obtained. The research results indicate: ML model with truncated normal distribution has $$\overline{\rho}^{2}$$ of 0.1516 and hit ratio of 70.42%, which has a lower accuracy. 3 ML models with lognormal distribution have a high accuracy, whose $$\overline{\rho}^{2}$$ are all between (0.2–0.4) and hit ratios all above 80%. The 4th ML model whose parameters of fatal risk and travel cost obeying lognormal distribution simultaneously has the highest accuracy, with the greatest $$\overline{\rho}^{2}$$ (0.2534) and the highest hit ratio (84.76%). VOSL in road traffic based on the 4th ML model obeys lognormal distribution with parameters (2.0622, 0.67402) with the mathematical expectation of 986,840 RMB. The maximum probability is 9.45% when VOSL is 500,000 RMB.

Wen-ge Liu, Sheng-chuan Zhao

Research on Point-to-Point Direct Transportation Organization Mode of Railway Bulk Goods

This paper firstly gives the definition of point-to-point direct transportation products for railway bulk cargoes, and then analyzes the organization conditions of point-to-point direct transportation. Finally, the total vehicle hour consumption of the loading and unloading traffic in the whole transportation process is taken as the objective function to found Point-to-point direct traffic flow organization model, and corresponding cases are given for analysis to verify the feasibility of the model.

Wei Lu

Research on Accident Causing Chains with Bayesian Networks on Waterborne Engineering

The accident mechanism is established to strengthen the safety management and reduce accidents of waterborne transport projects combined with security science. Basing on “2-4” model theory, this mechanism analyzes the influences on the security of waterborne projects construction. The impact factors include personal behaviors, project management and environment. We calculate the probability of each factor with Bayesian network and rank them as they contribute the accident. According to the probability, prevention measure and security management methods can be made to reduce accidents.

Junyong Wang, Yongrui Wen

Study on the Impact on Drivers of Performance Difference Between Pure Electric and Conventional Fuel Bus

The accident rate would rise first and then reached the same level when the traditional fuel buses are replaced by pure electric vehicles in batch. In order to study this special phenomenon the impact on bus drivers were studied. The causes were studied to short the adaptation period of drivers and improve the safety level. 200 bus drivers were regarded as the research objects. The actual driving parameters were measured. The bus drivers were investigated. The passengers and traffic participants were investigated too. Driving speed estimation, the acceleration of driving, the driver drowsiness and vehicles found as evaluation criteria were selected as assessment index to compare the impact on the drivers from pure electric bus and conventional fuel bus. Result showed that the driving speed estimation errors were larger from pure electric vehicle in the early stages of the vehicle replacement. The acceleration of driving and braking deceleration were larger from pure electric vehicle. Low labor load from pure electric vehicle caused dull sleepy phenomenon appeared early compared to conventional fuel bus. Pure electric vehicles were more difficult to be found by traffic participants for the low noise. These were the important cause of accidents rate rising early after vehicle replacement. The reasons attributed to driver fatigue and attention distracted were fallacy in operation management. Strengthen the driver management and education could not change this situation. After the replacement of fuel oil buses by pure electric buses, drivers should experience these differences. The driving skills would not be the only requirements.

Wei-hua Zhao, Kai-xi Yang, Yu-han Li, Chu-Na Wu

Application of Accident Causation Chain in Security Management of Ports and Channels

With the rapid development of globalization, China has experienced constantly accelerated development of market economy after joining the WTO, leading to more frequent foreign trade. The port and channel, as important infrastructure, have also expanded its development space. In this paper, the author mainly discusses the application of accident causation chain in security management of port and channel construction by studying the causation chain of classical, modern and contemporary accidents in combination with the characteristics of port and channel construction.

Majing Lan, Zhiqiang Hou

Comparative Study on the Measures to the Safety Management of Bulk Liquid Dangerous Goods Storage in Port Areas

In this work, the international and Chinese standards of bulk liquid dangerous goods terminal storage and handling are compared and evaluated. The safety management of ship operation in port and the safety management of terminal operation are selected as the key contrasting indexes of the port operation of bulk liquid dangerous goods. Afterwards, a revised proposal for the safety management of bulk liquid dangerous goods in port is proposed.

Chaoyu Ruan, Xin Lu, Zhiqiang Hou

Research on the Influence of Traffic Factors Based in Mixed Logit Model on Short-Rent Lease of Housing

With the aim to explore the influence of traffic factors on short-rent housing lease, this paper utilizes the utility function from the aspects of traffic convenience, traffic accessibility, generalized transportation cost, location advantage, road safety and traffic environment. We construct a mixed logit selection optimization model based on dis-aggregate theory, in which the reliability analysis and correlation analysis of SPSS are used as the basis for the tenant to decide short-rent housing. Based on the obtained questionnaire data of D-optimal method and the influence of different traffic modes and travel purposes on utility coefficient, maximum likelihood estimate (MLE) is introduced to solve the weight ratio, Matlab programming is used to solve to MLE, which shows that: expanding the traffic convenience and the accessibility of transportation infrastructure along the short rental housing source is the most effective means to stimulate the short rental market. Moreover, the reduction of transportation cost and the improvement of location advantage have a positive impact on short-rent housing rental satisfaction, demand and flexible price advantages. The evaluation value of road safety and traffic environment weight is on the low side, and the expected utility space is huge. Strengthening the service level of the vehicle will be conducive to share the running pressure of the rail transit.

Bo Sun, Pengpeng Jiao, Yujia Zhang

An Accurate Prediction Method for Airport Operational Situation Based on Hidden Markov Model

This paper is mainly devoted to an prediction method for airport operational situation which is one of the most important parts of the airport operation system. In order to provide theoretical support for high-level airport management, field operation management, air traffic control and airlines, and improve the service capacity of the airport, this paper makes a prediction study of the airport operation situation. Hidden Markov (HMM) prediction model is established based on the analysis of airport operation system. Baum-Welch and Viterbi algorithms are used to solve the prediction results. The model is validated and applied in a domestic hub airport. The results show that the prediction accuracy of HMM is 60 and 20% higher than that of Autoregressive Moving Average Model and Grey Markov model, respectively. It can also improve the situation value of airport operation situation, i.e. airport service capability. This method is more suitable for the analysis of airport operation.

Xintai Zhang, Yanwen Xie, Yaping Zhang, Zhiwei Xing, Xiao Luo, Qian Luo

Parking Demand Forecasting Model for Urban Complex Based on Shared Parking: A Case Study of Harbin City

The paper takes urban complex as research object, aiming at the problem that the current parking facilities allocation neglects the difference of parking demand features of various buildings, which worsens the contradiction between supply and demand of parking. Analysis shows that the peak parking hour of various buildings in the urban complex is complementary, and the supply and demand are seriously imbalanced based on the parking survey data in Harbin. The main influence factors of urban complex parking demand are analyzed, and the revision coefficient of parking generation rate model of urban complex under the influence of a single factor is constructed combining with the actual parking demand. Based on the idea of shared parking, a parking demand forecasting model of urban complex under the comprehensive action of multiple factors is established by using regression analysis method, and the Yuguang-Intel Industrial Park in Harbin is taken as an example to verify the validity of the model. The results show that the predicting value of parking demand by the model is closer to the actual parking demand, which can effectively avoid the imbalance between supply and demand, and improve the utilization efficiency of parking facilities.

Xian-cai Jiang, Longyang Zhang

Research on Multimodal Transportation Path Optimization with Time Window Based on Ant Colony Algorithm in Low Carbon Background

Green transportation has always been the focus of international attention. With the proposal of “One Belt And One Road” and the emphasis on logistics efficiency and cost at home and abroad, multimodal transport, as an advanced form of transport organization, has been developing continuously. However, there are few studies on carbon emission of multimodal transport in domestic and foreign literatures. In recent years, high-speed railway has become an indispensable way for Chinese tourists to travel, and the use of high-speed railway in the field of logistics also arises at the historic moment. Order is proposed in this paper for a batch of goods, by air, high-speed rail and highway combination of three kinds of transport mode, build the satisfying path capacity constraints, hard time window to minimize the total transportation cost under the restriction of the mathematical model of the total cost including transportation cost of transport costs, transport costs and carbon emissions, and using ant colony algorithm to solve the model, then use different local optimization strategy for processing, finally it is concluded that the optimization results are verified through the calculation example.

Dongxin Yao, Zhishuo Liu

RBFNN-Bagging-Model-Based Study on Bus Speed Predication

To establish intelligent bus information systems for the purpose of providing information support for the “smart city” construction, the speed of buses running in the urban road network must be accurately predicted. Common prediction models on bus speed by adopting neural network or supporting technologies like Support Vector Regression (SVR) can well predict vehicle speed on uni-structural sections, but when the prediction scope is extended to the general urban road network (with coexistence of various complex section structures), these models can hardly achieve satisfactory generalization effect, and may generate significant differences in prediction accuracy on different section structures. Therefore, this paper puts forward a RBFNN (Radial Basis Function Neural Network)-based Bagging integrated learning prediction model which can effectively deal with issues concerning the accurate predication of bus speed in the context of general road network. Major research contributions of this paper include: (1) Introducing speed of taxi with sufficient data and a high road coverage rate as the secondary data source so as to make up for sparseness of bus positioning data; (2) Selecting RBFNN as the base model and based on integrated learning philosophy, improving it to RBFNN-Bagging model, which can overcome the shortcomings of uni-structural model and better adapt to differences in section structures. The model raised in this paper, through verification of measured data, has realized an over-90% prediction accuracy rate of bus speed in different sections within the general urban road network, and has witnessed an over-10% promotion in prediction accuracy when compared with that of the neural network and SVR model.

Xiaoguang Wang, Hai-hua Han, Jin-hui Qie, Si-yang Li, Chun Zhang, Hong-yu Wang

Research on Applying Solar Energy Technology to Rail Transit Vehicle

Rail transit vehicle consumes a great deal of power in operation, while applying solar energy technology could reduce the consumption of electric energy. This paper researches on the solar energy technology applying on rail transit vehicle’s hot water supply and photovoltaic power generation system. Hot water supply system of solar energy which can supply hot water through day and night consists of solar collector, water tank, molten salt heat exchange system and control system. Photovoltaic power generation system connects in parallel with rail transit vehicle’s charger to supply electric energy to storage battery and DC load, it consists of buck-boost chopper, photovoltaic cell and power generation controller.

Yanwei Lu, Wang Xing, Jialin Zhou, Mintang Sun, Shufeng Li, Xinying Hou

Analysis of Typical Attacks on Intelligent and Connected Vehicle Cyber Security

The research on risk attacking and vulnerability mining of vehicle cyber security has been carried out all over the world, and the hidden dangers and problems of cyber security exposed by different types of automobiles have become more and more frequent. How to build an ecological circle of cyber security of the whole automobile industry chain still has a long way to go. This paper takes Ford Winged Tiger as the research object, and makes a detailed analysis of the typical cases of the brake system being attacked. By changing the CAN bus data message, the accelerator pedal will fail, which provides a reference for the management and prevention of the cyber security of intelligent and connected vehicle.

Xingshu Liu, Ling Yang

A Prediction Precision Inference Method for Passenger Alighting Station Based on the Condition Hypothesis

Smart IC-card has been widely used in fare payment systems of public transport, which produces a large number of ticket checking records and spatiotemporal trajectory information. Accurately predicting passengers’ travel stations based on IC-card data plays an important role in intelligent transportation. However, incomplete IC-Card transaction records are widely existing. The IC-card not only does not record the actual boarding stations but also lacks the information of alighting stations because passengers do not need to swipe card when they get off. Therefore, it is difficult to construct the actual passenger travel link, which makes it challenging to predict alighting stations accurately. Targeting on this challenge, we propose a “Boarding Cluster to Alighting Station” alighting station prediction model (BCTAS) by condition hypothesis. First, the model analyzes the travel characteristics of passengers’ public transport. Second, the smart IC-card transaction records and map-matching algorithm are used to construct the mixed boarding station link. Third, the model performs the station clustering and cluster expansion to merge the same name station and the nearest station into a cluster, and further constructs the mixed boarding cluster link. Fourth, a Variable Order Markov Model that named Prediction by Partial Match (PPM) is adopted to predict the mixed boarding cluster link and then predict the boarding station. Fifth, the model infers the prediction precision of the alighting cluster and alighting station based on the condition hypothesis. Finally, our approach was evaluated by using the public transport data obtained in Shenzhen city, China. The results show that (a) with the increase of training data, the precision of the model is gradually enhanced, (b) by using the mixed boarding cluster link, the prediction precision of the boarding cluster and boarding station could reach 88.05% and 84.52% respectively, (c) Based on the condition hypothesis, it can be inferred that the lower limit of the prediction precision of the alighting cluster and alighting station is 78.09% and 74.96%, respectively.

Fan Li, Qingquan Li, Zhao Huang, Jizhe Xia

Deep-Learning-Based Detection of Obstacles in Transit on Trams

Due to the pervasive employment of trams, the measurements to keep the transit of trams safe are necessary and emergent. In this sense, we put forward a Neural Network based on Convolutional Neural Network, in which we made some modifications to make it more flexible. Such as passthrough layer to ensure some small objects detectable, anchor boxes to ensure a high-speed detection, and batch-normalization layers to make the network be malleable for objects with different distributions. With this network, we can efficiently detect possible obstacles, such as pedestrians, cars and some other objections that may endanger the trams. We test the network among several databases with 5000 samples, and the average accuracy rate is 94.12%, the average detecting speed is 30 FPS, the smallest detectable object’s size is 20 × 20 pixels, these all show remarkable result.

Yiming Li, Guoqiang Cai

Prediction of Failure Rate of Metro Vehicle Bogie Based on Neural Network

Metro train bogie system is located between the car body and the track, which is one of the key subsystems to ensure the safety of train operation. As a complex system, bogie system is composed of many components, once the failure happened, it would impact the normal operation of the whole train. In order to better predict the failure rate of bogie system, radial basis function (RBF) neural network is introduced to predict the failure rate of the whole system through the fault data of bogie components, and genetic algorithm is used to optimize the model. Experimental results showed that the proposed method can accurately predict the bogie failure rate, and can be used as a system-level reliability prediction method, providing a data basis for later system improvement and optimization.

Xiuqi Wang, Yong Qin, Yong Fu, Meng Ye

Vehicle Risk Analysis and En-route Speed Warning Research Based on Traffic Environment

In this paper, we established a method to assess the risk of traffic environment and proposed a vehicle speed early warning model that is related to the traffic environmental risk index. This risk assessment method of traffic environment takes into account three risk factors: the risk exposure, the probability of accident occurrence and the severity of accident. Simultaneously, two dynamic risk factors of operating speed and real-time speed are also introduced. The vehicle speed warning model is correlated with the Traffic Environment Risk Index. The establishment of Early Warning Vehicle Speed and Vehicle Speed Early Warning System are based on the Evaluation Index of Operating Vehicle Speed and Velocity Gradient. The traffic environment risk assessment method and speed early warning model are validated by using the accident data and the section speed data of Kunshi Expressway, respectively. The Spielman correlation coefficient between the risk grade and the number of road accidents is determined from our experiments to be 0.7109. The average value of speed gradient of early warning vehicle speed is less than that of running vehicle speed gradient. The accident rate of early warning speed is lower than that of running speed in the same section.

Jian Xiong, Yan-li Bao, Zhou-jin Pan, Yi-fan Dai

The Prediction of Delay Time Class Caused by CTCS-3 Onboard System Fault Based on Decision Tree

The faults of train control system will lead to delay, which will affect the operational efficiency of the railway network. In this paper, the decision tree algorithm (CART) is used to predict the delay time level caused by CTCS-3 On-board System Fault, which takes the location of train failure, the fault component of CTCS-3 on-board system, the fault phenomenon of CTCS-3 on-board system as data features. In the natural language fault record, based on expert experience, extract the key features needed and grade the delay time. The selected features are put into the decision tree algorithm for classification and prediction, SMOTE algorithm is used to solve the problem of unbalanced number of categories, and grid search algorithm is used to adjust the model parameters. Finally, the output results of the algorithm are analyzed. The decision tree model yields a classification accuracy of 76% for the given data of fault feature and can be considered for delay time level prediction caused by CTCS-3 system fault. From the experimental results, the proposed method can be recommended for the prediction of the delay time level caused by CTCS-3 system fault.

Lijuan Shi, Ang Li, Liquan Chen

Road Network Equilibrium Analysis Based on Section Importance and Gini Coefficient

Traffic flow on road network has a character of disequilibrium under the road network structure, traffic flow distribution and so on. In order to quantify its imbalance, taking section importance as the index, the model for road network equilibrium analysis is proposed based on the Gini coefficient. First, considering the road network structure, traffic flow distribution and the influence between sections, the section importance measurement based on space-time influence and space-time distribution is constructed to reflect the critical level of sections in the road network. Second, the road network equilibrium is discussed through Gini coefficient and Lorenz curve. Finally, the proposed model is applied in a subset of Beijing’s road network, and the results show that the model is simple and flexible to evaluate road network equilibrium in different dimensions. It has great significance for mastering the distribution law of traffic flow, optimizing road network structure, adjusting traffic capacity allocation and improving the efficiency of road network resources.

Fei Su, Xiaofang Zou, Yong Qin, Shaoyi She, Hang Su

Research on Driving Workload Characteristics of Drivers Under Various Dangerous Scenarios Based on EEG

In order to study the driving workload characteristics of drivers under various dangerous scenarios, the electroencephalography (EEG) data of drivers under different dangerous scenarios are analyzed based on real driving experiments. The ErgoLAB human-machine environment synchronization platform was used to collect and extract the driver’s EEG signal. Meanwhile the appropriate EEG index was selected. The statistical analysis method was used to study the EEG data of the drivers, and the EEG variation rates of the driver under various dangerous scenarios was obtained to reflect driving workload. Two conclusions are reached from the experiment designed to figure out the relationship between driving workload and dangerous scenarios. Two conclusions were reached from analyzing indicators. First, various dangerous scenarios have significant impacts on driving workload. When there exists one dangerous scenario with fewer non-motor vehicle protection measures easily causing serious traffic accidents such as pedestrians or bicycles, there will be a higher driving workload. Besides, the impact on the EEG variation rates of the driver in various dangerous scenarios caused by the external factors such as turning and encountering pedestrian (bicycle) or a relatively sound protection measures taken like vehicle interactions is small, resulting in lower driving workload. Second, driving workload is not only affected by dangerous scenarios but also by driving experience and the age of driver.

Shumin Feng, Bin Sheng

Classification of Beijing Metro Stations Based on Multi-source Data and Gaussian Mixture Model

At present, the metro plays an important role in people’s daily travel. In order to clarify the function of the metro stations and to improve the service level of the metro, the reasonable classification of metro stations is particularly necessary. In this paper, multi-source data including Internet data and ridership data is obtained, and the data is analyzed to obtain 12 clustering initial variables. After that, 3 common factors are extracted from the 12 initial variables by factor analysis. According to the extracted common factors, 249 metro stations in Beijing are divided into 4 clusters by Gaussian mixture model, and the probability values that a station belongs to each cluster are obtained.

Feng Wan, Jianrui Miao, Shuling Wang

The Progressivity of a Per-kilometer Congestion Tax in Beijing

In recent years, the traffic congestion problem in Beijing during peak hours has attracted more and more attention. And a series of charging policies or researches were designed to relieve the congestion. In this article, we focus on the per-kilometer congestion tax and carry on empirical analysis to measure its progressivity. Based on the survey data,we calculate the mileage of each sample, add them up, and divide these samples into different groups according to income level and spatial district. Then we introduce the Suit index to analyze income and spatial distributional effects of the per-kilometer congestion tax among different groups. It is found that a per-kilometer congestion tax is regressive in terms of the income distribution. That is, compared to higher income group, the lower would pay more for the tax. And in the case of spatial distribution, the tax is progressive. That is, compared to urban counterparts, the rural residents would bear more tax burden. Finally, the econometric multiple regression method was applied to explain the characteristics of resident commuting mileages in Beijing. The result suggests that the highly educated residents tend to travel far for work.

Tian Yu

Social Network Analysis and Connection Strength Evaluation of Urban Tourist Attractions Using Car-Hailing Data: A Case Study of Beijing

For large cities with huge tourism market, tourism travels can have significant impact on the urban traffic, which, cannot be ignored in both urban transportation and tourism planning. This paper first proposes a simple and effective spatial matching method to identify tourist travel patterns based on massive online car-hailing data. Then we construct the tourist attractions network based on the tourist movement by car. From the perspective of social network analysis, the development status of the holistic tourist attractions network and the influence of the attractions are evaluated. Finally, connection strength based Jenks natural breaks classification method is employed to divide the attractions into four levels: unconnected, weak, moderate and strong connection. Taking Beijing as case study, the main factors that affect the connection strength among attractions are the popularity of the attraction and the spatial proximity of the attraction. These findings in tourist movement can facilitate authorities and planners to develop tourism destinations and manage tourism traffic better.

Shixia Ma, Xuedong Yan, Xiaobing Liu, Deqi Chen

Visualization of Spatio-Temporal Traffic Performance in Urban Road Network Based on Grid Model

Traffic congestion monitoring is a very important problem in big cities. This paper describes a novel computation way of traffic performance index in urban road network. Floating car data are used in the extraction of traffic attributes. In addition, we use the grid model to reconstruct the road network and present the visualization approach of spatio-temporal traffic performance based on it. We take the 5th ring area of Beijing as a case area. The case results indicate that traffic performance is worse in the PM than in the AM. Moreover, it is worse in the north and middle area than in the south area. This method efficiently distinguish the congestion’s area and time of the urban road network. It is much helpful with traffic managers in city traffic management.

Liwei Wang, Yingnan Yan, Deqi Chen

A Cooperative Motion Control Strategy of Multi-objects Simulation Based on CAV Testing Platform

Test system of Connected and Autonomous Vehicles (CAV) is a newly-developed research area. Nowadays, CAVs are basically tested in real time field test. However, the field test has two disadvantages: (i) the safety of pedestrians and other conventional vehicles cannot be guaranteed in field test, (ii) the testing period can be prolix because of the scarcity of certain extreme driving conditions. In this paper, a cooperative control algorithm of mobile unit is designed. In the proposed algorithm, motion and reaction of different traffic participants can be simulated, such as pedestrian, animals and non-motor vehicles. Motion models of traffic participants are built up in two dimensionalities: trajectory and reaction. After setting appropriate simulation parameters, the scarce driving scenarios can be easily reproduced so that the CAV test period is expected to significantly shortened. We also build up a comprehensive testing framework to realize the designed function. In the end, numerical analysis and experiments are carried out to show the algorithm’s feasibility.

Yuning Wang, Jiahao Huang, Bo Wang, Yiming Hu, Yubin Hu, Qing Xu

Research on Attention Capacity Measurement for Drivers’ Visual Space Information

In this paper, drivers’ visual space attention capacity was researched, and a way of measuring this attention capacity by driving simulation experiments has been proposed. Firstly, based on static and dynamic traffic information the quantitative and incremental stimulus information sources were established and the road traffic virtual scenes with different amounts of information sources were built. Then 30 subjects (half experienced and half novice) were selected to participate the simulation experiments, the amount of stimulus information that the subjects sensed at each test point were tested, and subjective questionnaires were carried out after each test. Finally, experiment data were statistically analyzed. The results shown that when the stimulus information was 2 or 3, the subjects could get the information, however, when the number of stimulus was 4 or 5 or 6, the amount of information that the subjects sensed were obviously decreased to 38, 19 and 8% separately. The subjects’ average attention capacity was 4.27, but there was a significant difference (p = 0.02) between the experienced and the novice. The attention capacity for experienced drivers was 5, and that was only 3.54 for the novice. Moreover, during driving, the distribution of the amount of information obtained by the subjects was similar to the Poisson distribution. The results should have a guidance for the research of driver’s psychological behavior and intervention, as well as the renovation of traffic information sources and environment.

Li Zhu, Jian Xiong, Fengxiang Guo, Yahui Xie

An Improved Convolutional Neural Network for Monocular Depth Estimation

Depth estimation from monocular image plays an essential role in artificial intelligence, which is one of the important ways for sensing the operating environment in automatic-driving system or advanced driving assistant system. The most recent approaches have gained significant improvement for depth prediction based on convolutional neural networks (CNNs). In this paper, a novel framework of CNNs is proposed for monocular depth estimation based on deep ordinal regression network (DORN) and a U-net structure. The new model is trained, verified in process and tested on 5000 images from a simulation experiment platform provide by “Grand Theft Auto”. To eliminate or at least largely reduce the impact from ground truth with no depth values, three different training strategies were employed for network optimization. We developed an effective weighted training strategy for depth prediction to improve the estimation accuracy. The comparison of evaluations over our results and DORN demonstrated the effectiveness of our method. The results showed that the proposed method achieved state-of-the-art performances.

Jing Kang, Anrong Dang, Bailing Zhang, Yongming Wang, Hang Su, Fei Su, Tianyu Ci, Fangping Wang

Vehicle Trajectory Extraction Method Research for Intersection Bayonet Data

In order to extract the vehicle trajectory on the urban road network and provide data basis and technical support for analyzing the balance of supply and demand of urban traffic, the method to extract the vehicle trajectory which is based on intersection bayonet data will be constructed. Firstly, the daily travel trajectory of the vehicle can be obtained by using the data of intersection bayonet and the method of license plate grouping and time order sorting. Secondly, considering the relationship between link travel time and the vehicle to achieve the separation of the vehicle trajectory chain. Finally, the decision indicator of high-grade road proportion will be used to improve the TOPSIS method, and the approach based on the TOPSIS method will be built to reconstruct vehicle trajectory and infer the trajectory of the lost point which is generated by the heuristic depth-first directional algorithm. The paper chooses Suning County in China as an example to verify the reliability of the above approach. Moreover, it is found that the approach can effectively achieve the extraction, separation, and reconstruction of the vehicle trajectory.

Bingjian Yang, Hao Yue, Wencan Gao, Mengyu Zhang, Yang Liu

Critical Section Identification in Road Traffic Network Based on Spatial and Temporal Features of Traffic Flow

The capacity of critical section is one of the important reasons for leading to urban road traffic congestion. The identification of critical section has great significance to alleviate traffic congestion, and can provide support for traffic planning, network transformation, residents’ travel plans and so on. Based on the spatial and temporal features of traffic flow, the critical section is defined as the one which has more contribution to the overall network and has greater influence on other sections in this paper. In the section importance measurement framework, space-time distribution is used to explain the contribution of one section to the network, space-time influence is measured to describe its influence on other sections, and the critical section is given by the ranking of section importance. At last, the proposed model is applied in a subset of Beijing’s road network, and the results show that the model is practical and feasible, and can identify critical section in road traffic network effectively.

Fei Su, Xiaofang Zou, Yong Qin, Shaoyi She, Hang Su

Public Traffic Passenger Flow Prediction Model for Short-Term Large Scale Activities Based on Wavelet Analysis

The short-term large scale activities refer to various large-scale activities with a duration of several hours, with features of high peak passenger flow and short gathering time. The analysis of public transport passenger flow characteristics and travel demand prediction for large-scale activities can provide a targeted organization plan for public transportation security in the context of large-scale activities. Based on the smart card data of Beijing, the paper analyzes the spatial-temporal characteristics of passenger flow under the background of large-scale activities. The Discrete-Fourier transform is used to study the frequency domain characteristics of large-scale active passenger flow sequences. Then, through the steps of sampling, decomposition and reconstruction of passenger flow sequence features, the public traffic passenger flow prediction model for short-term large scale activities based on Wavelet analysis was established. And reconstruction steps to establish a short-term large-scale public transport passenger flow forecasting method based on wavelet analysis. The method overcomes the weaknesses that data detail information are ignored in large-scale forecasting during modeling, and improves the stability of forecasting results in short-term forecasting. A case study of Beijing was conducted to validate, and the result shows that the mean absolute percentage error (MAPE) and mean absolute error (MAE) are 0.22% and 1.47%, respectively.

Yunqi Jing, Jiancheng Weng, Zheng Zhang, Jingjing Wang, Huimin Qian

The Impact of Subject Diversity on Taxi Transportation System

In order to analyze the impact of different driver types and passenger types on the taxi transportation system, a simulation method is applied to reproduce the process of driver and passenger matching in the taxi market. According to the driver’s decision-making way, drivers were divided into three types: searching for the closest passenger in sight, searching for the most profitable passenger per hour by taxi-hailing app, searching for the closest passenger by taxi-hailing app. According to passenger travel characteristics, passengers are classified into ordinary passengers, congested passengers, short-distance passengers and marginal passengers. Formulate passenger taxi generation, passenger disappearance, driver decision, taxi parade, taxi pick-up passengers on board, taxi to transport passenger rules. Select passenger’s waiting time, driver’s search time, driver’s income, taxi’s empty rate, taxi’s status, number of specific passengers disappeared, ratio of disappeared passengers’ number to total disappeared number as evaluation indexes. Research shows that different types of drivers and passengers will have different impacts on the taxi transportation system. Using taxi-hailing app can help improve the taxi transportation system. Searching for the closest passenger by taxi-hailing app mode can improve passenger’s actual load efficiency while ensuring the driver’s income. It will not screen and eliminate special passengers and improve the fairness of passenger travel. Therefore, it is recommended drivers search for the closest passenger by taxi-hailing app.

Wencan Gao, Hao Yue, Bingjian Yang, Mengyu Zhang, Lucheng Zhao

Driving Behavior Characteristics on Urban Expressway On- and Off-Ramp by Simulation

Traffic bottlenecks are easy to form on ramps, which restrict the capacity of urban expressway. The paper studied vehicle driving behavior characteristics on on- and off-ramps by simulator test, the utilization of acceleration section of on-ramps and that of deceleration section of off-ramps, speed transition on ramps, the merging position on on-ramps and the departure position on off-ramps were analyzed. The research would provide theoretical foundations for ramp alignment evaluation, traffic flow control on ramps and coordinated ramp control strategy optimization. It was discovered that vehicle acceleration did not distributed uniformly on ramps. Vehicle driving speed increases before acceleration section on on-ramps and it decreases before deceleration section on off-ramps, which indicates the acceleration and deceleration sections were not used adequately. The analysis of vehicle driving speed on the key positions showed that speed transition on off-ramps was better than that on on-ramps. The merging point where vehicle coming from ramps enter the expressway traffic flow clusters near the end of acceleration section, and the departure point where vehicle coming from expressway enters the ramp clusters on the half part of transition section. This phenomenon indicates that the transition section of on- and off-ramp was not used with expectation.

Cai Xin, Zhong Yi, Zhao Yong, Mao Yan

Optimization on Design Parameters of Road Longitudinal Slope Based on Truck Dynamics

In recent years, with major cities turning to the stock development stage, the development and construction of underground space has gradually become an important strategy for sustainable urban development. The construction of underground passages at freight transport hubs will help the separation of passenger and cargo, which will greatly alleviate urban traffic jam and improve transport efficiency. However, due to the restriction on urban land use and construction cost, it is difficult to achieve gentle slope design for all of underground passages, longitudinal slopes with large gradient are unavoidable. Generally, trucks have quite large gross weight, its uphill speed reduction and downhill brake disc temperature rise would affect road capacity and traffic safety greatly. Therefore, it is quite necessary to propose optimal design of longitudinal slopes given the consideration of truck dynamic performance and its driving safety. Truck models were established in TruckSim, they were used to simulate vehicle driving status uphill and downhill then. Speed reduction and brake disc temperature rise were used to obtain suitable slope gradient and length based on simulation. It was concluded that slope gradient and vehicle output power ratio have great influence on truck climbing ability. Using speed reduction of 20 km/h between vehicle uphill original speed and its stable uphill speed for reference, the maximum slope length for uphill with different gradient could be obtained. Slope gradient and vehicle gross weight have giant impact on brake disc temperature rise. Using brake disc temperature of 200 and 260 °C for reference, suitable slope length for downhill with different gradient were obtained.

Cai Xin, Zhong Yi, Zhao Yong, Mao Yan

Research on Express Highway Safety Features and Improvement Measures

Chinese express highway has following characteristics: incomplete control of access, divided directions, multiple lanes, heavy volume of traffic, high speed, severe lateral disturbance, etc. These lead to the highest traffic accident rate and death rate, which makes these express highways become the most unsafe highways in China. This study focuses on express highway to analysis its representative safety features, including access management, speed control and anti-dazzle facility installation, then points out improvement measures. Through optimizing road cross-section layout, controlling access density, installing traffic control facilities, the access management can be realized. To realize speed control, speed buffer zone could be installed between two adjacent speed zones with different speed limit values. It is suggested that anti-dazzle facilities should be demolished at small radius curve to eliminate obscure vision.

Jiahui Li, Chengwu Jiao, Nale Zhao, Keman Wu, Siyuan Hao

Failure Propagation Analysis of Complex System Based on Multiple Potential Field

In consideration of the complex system structure and its functional behavior, a method of analyzing the system failure propagation process based on multiple potential field model is proposed, for the sake of seeking out all the possible failure propagation paths with their lengths if faults occur. Firstly, the structure and functional behavior of the complex system is introduced based on the complex network model. Secondly, system failure properties are analyzed and the whole process of system propagation is simulated based on the proposed failure propagation model. Finally, a case study based on railway train bogie system has been implemented to demonstrate the proposed method, which shows that the proposed model and method work well on the complex system.

Yong Fu, Yong Qin, Lin-Lin Kou, Dian Liu, Li-Min Jia

Influence of Foam Liner on Tunnels Subjected to Internal Blast Loading

The tunnels face terrorist attacks which will cause huge economic and social losses. To study the influence of geofoam liner on circular cast-iron tunnels in saturated soil subjected to internal blast loading, a new approach was introduced to simulate blast loading with LS-DYNA. The results showed that the geofoam liner could reduce the damage and provide protections to the lining due to small blast loading. Geofoam liner could be used as an effective mitigation method for tunnels.

Yuzhen Han, Xiuren Yang, Jingfeng Ni

The Optimal Road Tolls and Parking Fees for Managing Daily Household Commute in a Linear City

This paper exams a daily traffic pattern of household on a morning and evening commute link. It is assumed that the parking is located along commuting routes radiating from the CBD and the households have two preferred arrival times, i.e., school start time and work start time. Based on bottleneck model, the households’ departure time choice is assumed to follow the user equilibrium principle according to tip cost. The analytical solution of the proposed model is derived. We then design pricing schemes, i.e., a time-varying road toll and a location-dependent parking fee. Within the framework of the extended bottleneck model, we proved that the proposed joint scheme of road toll and parking fee can effectively eliminate the queues behind the bottleneck, even reduce the schedule delay by reversing the spatial order of parking. We also find that the location-dependent parking fee with no road toll could improve the morning commute pattern. Furthermore, the numerical results show that the proposed pricing schemes can indeed improve the efficiency of the household commute through decreasing the total travel cost.

Yi Yao, Ling-Ling Xiao, Wei-Jiu Zhang

Airfield Smart Operations Management and Application of Shared Services

Nowadays, traditional ground-service model cannot meet the requirements of multiple-runway and multiple-terminal operations. To solve the problem, we introduce new technology and applications to change the traditional safety operations management in all aspects and multiple perspectives. This article takes unpowered equipment management and smart transportation as examples to make a research on shared services which based on Airfield Smart Operations Management.

Zhang Rui

Evaluating the Impact of Traffic Congestion on Mid-block Fine Particulate Matter Concentrations on an Urban Arterial

The primary objective of this paper is to evaluate the impact of traffic congestion on mid-block fine particulate matter (PM2.5) concentrations on an urban arterial. Data of mid-block and background PM2.5 concentrations were collected second by second during peak and non-peak hours on an urban arterial. Then micro traffic conditions were extracted from videos at ten seconds intervals, including traffic volume, traffic flow speed and high-duty vehicle fraction. Results showed that traffic volume had significant influence on mid-block PM2.5 concentrations. Mid-block PM2.5 concentrations were not correlated with traffic level of service. Furthermore, a modified passenger car equivalent was calculated from the aspect of contribution on PM2.5 concentrations using multiple linear regressions model. Then a comprehensive model was established to model the impact of micro traffic conditions on PM2.5 concentrations. Results of the comprehensive model showed that PM2.5 concentrations increased with the increase of total volume or heavy-duty vehicle fraction. Besides, low traffic flow speed resulted in high PM2.5 emission factor, leading to the increase of PM2.5 concentrations. The findings of this study can help better understand traffic congestion and micro traffic conditions on PM2.5 concentrations.

Xiaonian Shan, Changjiang Zheng, Xiaoli Zhang

Uncertainty Analysis of Rock Strength Based on Mohr-Coulomb Criterion

Due to uncertainties of the input parameters, such as the maximum principle stress, the minimum principle stress, the cohesion and the internal friction angle, the evaluation of the rock strength becomes the uncertainty problem. In such case, the uncertainty analysis method was proposed to deal with the uncertainty of the rock strength based on Mohr-Coulomb criterion. To describe the properties of the random variables, the indoor experiment was performed to obtain the mean and the standard deviation of the input parameters. Furthermore, the random technique was introduced to yield the sample data based on the mean and the standard deviation. More importantly, the factor of safety (FOS) was defined to evaluate the rock strength based on Mohr-coulomb criterion. Meanwhile, Monte Carlo method was introduced to the probability of the factor of safety. The results show that FOS has a range of [0.6, 1.4], and shows an obvious normal distribution.

Yongfeng Ma, Rangang Yu

Dynamic Maintenance Decision Model for Essential Equipment of Metro Based on Markov Chain

Maintenance of essential equipment is an important factor in ensuring the safety operation of urban rail transit. The traditional maintenance decision-making usually has irrational repairs schedule and excessive maintenance. In order to proffer solution to the problems associated with the traditional maintenance decision-making, the current maintenance mode of equipment were analysed. After critical analysis of the traditional maintenance decision-making, based on Markov chain a Dynamic maintenance decision model and scientific planning of the decision-making process was proposed. Furthermore, the components of the essential equipment of rail transit was also analysed. Through preventive maintenance interval and frequency, reliability and other factors, a Markov chain prediction model is established to predict the time interval for repairing the equipment. The validity of the model was proved by processing the actual maintenance data with MATLAB, which provides a reasonable basis for the dynamic maintenance decision-making of equipment.

Jun Wu, Yongneng Xu

Research on the Choice of Shared Car Travel Behavior Based on Medium Commuting Distance

With the rapid development of urbanization level, the choice of urban residents to travel under medium commuting distance has a great impact on urban traffic congestion and environmental pollution. Shared car travel modes can alleviate traffic pressure. This paper takes the travel choice behavior of residents under the medium commuting distance as the research object. Through the t-test to the age, the number of private cars, whether there is car rental experience, travel expenses and travel time as the influencing factors. Multivariate Logit selection probability model of the traveler’s choice of private car, shared car, taxi and net car is established. The SPSS software is used to calibrate and test the model parameters by using the maximum likelihood estimation method to obtain the travel mode selection probability, which provides a reference for the development of shared car mode.

Yongneng Xu, Xiaotian Wang, Zhou He

Study on Passenger Flow Characteristics and Classification Method of Rail Transit Stations Based on AFC Data—A Case Study of Ancient District of Suzhou

The passenger flow characteristics of rail transit stations are important data bases for urban rail transit development planning, rail transit station connection strategy designation, underground space planning of rail transit stations and surrounding land development. Traditionally, the characteristics of rail passenger flow are acquired by manual survey method, and the continuous passenger flow characteristics cannot be obtained. In this paper, AFC data is used to analyze the passenger flow characteristics of rail stations, and the classification method of rail stations is studied according to the different characteristics of passenger flow in and out of different stations. Finally, the passenger flow and station classification of rail stations in the ancient urban area of Suzhou is taken as an example.

Peipei Peng, Daixiao Zou

Realized Application of a Contactless CPU Card for Public Transport Interconnection

Public transport cards from various cities cannot achieve transactions in other cities. This means they fail to meet current technological development trends and public travel demands. This paper puts forward a method to realize contactless CPU cards that feature cross-regional, cross-transportation-modes, as well as cross-industry interconnections in public transport. It does so by unifying the public transport card system composition, card files and application requirements, terminal transaction flows, clearing and settlement information interfaces, as well as the contactless interface communication, security system, test system. This method features compatibility between advanced financial electronic cash applications with traditional public transport card electronic wallet applications. It also features dual application shared files and balances, the national transport One-Card clearing and settlement platform building, as well as cards with international IIN and RID codes, the compatibility of a dual key system and dual algorithms, dual-coin function support. At present, more than 200 cities in China have joined the transport One-Card interconnection. More than 12 million One-Card interconnection cards have now been issued, and the national transport One-Card clearing and settlement platform has processed 30 million data exchanges after more than two years of application and implementation. The successful realization of the national transport One-Card interconnection has been improving the standards of public travel service and management in the transportation industry. It has also been useful for promoting the healthy development of the transport One-Card industry.

Guo-jing Xing

Bearing Fault Diagnosis with Impulsive Noise Based on EMD and Cyclic Correntropy

Periodic pulses are an important fault feature of rolling bearings, so the ability to accurately and efficiently identify pulse components is important for bearing fault diagnosis. Due to the complicated wheel-rail contact relationship in actual train operation, it often generates many impulse noises which similar to the fault signal structure. Unfortunately, spectral kurtosis (SK) methods often fail to effectively diagnose under impulse noise. In order to solve this problem, this paper proposes a bearing fault diagnosis method based on Empirical Mode Decomposition (EMD) and cyclic correntropy (CCE) function. Compared with the SK method, the method proposed in this paper can effectively suppress the influence of impulse noise. Moreover, this paper also proposes a fault diagnosis evaluation index $$ KR_{s} $$ to quantitatively compare the diagnostic effects of different methods. Simulations and real data of the train axle are utilized to demonstrate the feasibility and effectiveness of the proposed method and index.

Yu-Ze Wang, Yong Qin, Xue-Jun Zhao, Shun-Jie Zhang, Xiao-Qing Cheng

Research on Driving Behavior of Mountain City Passenger Car Drivers Based on GPS Data

In order to study the driving behavior characteristics of urban drivers in mountainous cities. In this paper, a modern data processing technology “GPS” has been used. Through GPS acquisition and comparative analysis method, the travel speed value of six passenger cars in Chongqing, which is collected in two days, is processed, and the effective acceleration value is filtered out. From the point of view of the proportion of sharp acceleration and acute deceleration in the driving process of the driver, the driving acceleration of six vehicle drivers is compared and classified, so the driver behavior characteristics are obtained. Then the driving speed of different drivers on the same road section is compared separately, and the behavior characteristics of different drivers for the same speed limit are summarized. The results show that: (1) The habits of different drivers in the driving process are not the same, the experiment out of three models, “Remain Constant”, “Preference Acceleration”, “Fast and Slow” type; (2) Because of its properties, in the process of driving, the speed range of passenger car is not large. That is, when driving the passenger car, different drivers will control the driving speed in a more stable range; (3) Different drivers treat so-called speed limit signs differently when crossing the same road, the experiment out of two types, “Complete Follow” and “Appropriate to Follow”; (4) Chongqing belongs to the mountain city, the large number of tunnels and bridges in passenger routes makes drivers more vigilant than other plain areas. In this paper, make a quantitative analysis of driver’s driving behavior from the angle of GPS data, which is helpful for the management department to control and supervise the driving behavior such as driver speeding, and provides the basis for the improvement of road infrastructure.

Ying Chen, Jin Xu

A Comprehensive Collision Prevention Approach for Rural Highway in Mountain Area

Many serious traffic collisions occur at rural highways in mountain area during the rapid urbanization in China, when traffic demands are large, vehicle composition is complicated. This brings tremendous pressure on transportation agencies. In order to improve safety performance of rural highways in mountain area of China, a comprehensive collision prevention approach was developed systematically. A case study regarding the effect of before-and-after implementation of this advanced collision prevention approach at Longyan, Fujian Province was conducted. It showed that highway risk level (HRL) evaluated through highway risk assessment method in the technical guide for the implementation of highway safety and life protection engineering was reduced from 19.09 to 7.59 with safety level improved from grade IV to III. The merit of this newly developed approach has been verified and is very promising for future large scale promotion and implementation.

Fengchun Han, Dan Zhao, Wen Shen, Sheqiang Ma

Determinants of Long Distance Traveler’s Arrival Modes: A Case Study of the Beijing Capital Airport

Before the formal long-distance travel, the travelers usually have four common modes to get to the airport or railway station: metro, airport coach, auto, and taxi. This study was proposed to analyses the determinants of long-distance traveler’s arrival modes to the airport. Based on the theory of planned behavior (TPB), a questionnaire survey was designed and conducted to acquire the variable data of the psychological factors that affect urban air passengers’ arrival modes. After the pilot survey, Beijing Capital International Airport was chosen to conduct the survey and more than 3700 sample data was acquired. With the sample data, the coefficient relationship between the behavior attitude, subjective norm, perceived behavior control, and behavior intention was analyzed after validating the reliability and validity. The study also employed a structural equation model (SEM) to explore the insight between the determinants and decision. The correlation variables analyses result and path coefficient reveal that the behavior intention of using various travel modes with the subjective norm having the most impact on the behavior intention. The conclusion part explained why the railway was less used than the coach and people love to use taxi or auto to arrive the air terminals. This study reveals the key determinant that influence the choice of behavior.

Zhenhua Mou, Weiwei Liang, Yanyan Chen, Yao Lu, Shaohua Wang


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