Recent Advances in Transportation Systems Engineering and Management—Volume 1

Road geometry will meet the needs of some road users to a large area while failing to meet the needs of others. So, reliability theory is used to calculate the safety of each vehicle type using the probabilistic approach. The design of horizontal curves is the focus of the current application, which defines the two-limit state functions one in terms of the available (supply) and stopping (demand) sight distances (SSD) and the other as available (supply) and demanded super elevation (SE). Reliability analysis for SSD results shows that the inner lane of horizontal curves is unsafe than compared to their corresponding outer lanes. Whereas in case of reliability analysis for SE results shows that the inner lane of horizontal curves is safer than compared to their corresponding outer lanes. Combination of two failure modes (multi-mode) is considered in series system as the system fails even if one of the individual mode fails. Car is in unsafe category than compared to other vehicle types in both the single mode and multi-mode reliability analysis. System reliability analysis results shows that it follows similar trend as super elevation i.e., inner lane is safe than compared to their corresponding outer lanes. This study serves as a crucial tool for bolstering the safety of curved segments on highways. It prioritizes identifying high-risk curves, enabling the implementation of targeted countermeasures to enhance overall safety.

Traffic accidents annually result in millions of injuries and substantial economic losses worldwide. Historically, safety evaluations have relied on police-reported crash data to mitigate these incidents. However, this approach primarily reacts to accidents, making it less effective for proactive safety assessment. To enhance safety analysis, a more effective approach involves the use of conflict-based safety assessment with a range of surrogate measures of safety (SMoS). These measures allow for the study of critical traffic events that occur more frequently, aiding in the prevention of accidents. This study employs temporal proximity indicators, including Time to Collision (TTC), Post-Encroachment Time (PET), and Time Advantage (TAdv), to evaluate the safety of un-signalized intersections. Furthermore, investigate the critical speeds of vehicles involved in right-turning movements at these intersections to assess conflict severity, as deter-mined by PET values. Additionally, at these intersections, employ k-means, a centroid-based clustering method, to assess the severity levels of right-turning and straight-through traffic using TAdv and TTC, respectively. Our findings indicate that, within the selected study area, the SMoS at Krishna Arcade demonstrate a higher degree of risk compared to Sabban Choraha.

The examination of acceleration and deceleration (A/D) characteristics in vehicles at intersections holds significant relevance in intersection design, fuel emission modelling, and various related domains. This paper presents an evaluation of the A/D behaviour of cars, specifically at signalized intersections, focusing on mixed-traffic conditions characterized by weak lane discipline. To gather comprehensive data, extensive field runs were conducted in Chennai city, India, employing passenger cars equipped with an Inertial Measurement Unit (IMU) and a Global Positioning System (GPS) capable of capturing vehicle dynamics at a deci-second resolution. An algorithm was developed with over 90% accuracy to distinguish between straight and turning movements at intersections. Subsequently, a thorough analysis and modelling of the A/D behaviour was carried out, focusing on ‘stop and go’ manoeuvres at 22 four-lane, four-legged signalized intersections, encompassing both straight and turning movements. The analysis revealed that straight movements exhibited 14.6% higher acceleration and 12.34% greater deceleration than turning movements. The study explores various A/D characteristics and the findings indicate that average and maximum deceleration rates increase with approach speeds, peaking approximately 8 s before stopping. The average critical speeds for acceleration and deceleration manoeuvers were observed to be 8.24 and 16.80 km/h for all approach speed ranges, respectively. Notably, the A/D behaviour was found to be best described by polynomial models in both types of movements with R² greater than 0.8. This research could provide valuable inputs for traffic simulation models, characterizing driving behaviour and developing driver assistance systems.

The disobedience of priority rules makes unsignalized intersections riskier under mixed traffic scenarios. Small-size vehicles move parallel to large-size vehicles, accept a gap in their shadow and haphazardly move into the intersection. So, the critical gap estimation in this situation is a complex task. In that context, the present study is focused on estimating the critical gap of vehicles and developing a logistic regression model to analyze the drivers’ aggressiveness at unsignalized intersections. The critical gap was estimated for right turning and through movements using the clearing behaviour approach. To understand the risk-taking behavior of two-wheelers, their critical gap was compared with the cars and observed that 77% of vehicles were behaving aggressively. So, the parameters that influence the aggressive behavior of drivers were identified and included while developing the model. The proposed model can predict the drivers’ aggressiveness with 92.85% accuracy in mixed-traffic scenarios.

Studying driver behaviour and its interaction with various elements of the road and road environment is one of the research areas with the highest potential to reduce crash probabilities, specifically on Indian roads with mixed traffic conditions. Speed is cited as the most influential reason for the accidents and fatalities caused on Highways. However, it is often overlooked that a considerable number of casualties often happen during lane changing, which is not often reported as lane changing is a very subjective event and is tough to comprehend due to various reasons affecting and inflicting the lane changes. Lane Changes are not only the significant causes of Side collisions; a considerable number of rear-end and front-end collisions are owed to sudden lane change manoeuvres. The interest in the Lane change behaviour of a driver is not new. It is widely associated with aberrant driving behaviour in the various pieces of research carried out in the field. Still, it cannot address the actual causes of this behaviour, instead of only the consequences like crash probability, speed, density, travel time and delay and other such factors are correlated with the lane change behaviour. The sudden lane change manoeuvres are often attributed to similar prior visual behaviour, which can also be well detected on time and alarmed if efficient driving monitoring and training module is being developed. This study evaluates the lane change behaviour at toll plazas attributed to the visual behaviour of the driver. The driver often looks at various elements before and after deciding the service lane he wants to pass through on the toll plaza. Previous studies have only worked towards the factors like position and number of HCVs in lanes, serviceability of booths and dwell time. However, the Gaze Behaviour of driver is one of the vital parameters which shows how often the driver is looking into the potential lane and target lanes and how sure or unsure he is of his lane change manoeuvres.

One of the most typical causes of traffic accidents is driver fatigue. By 2030, traffic-related fatalities are anticipated to rank fifth among all causes of death. Extreme fatigue, such as that experienced by drivers, impairs concentration and decision-making. Driver fatigue-related accidents are more dangerous than other traffic accidents because tired drivers frequently fail to take evasive action before an accident. To prevent accidents, it is important to research the amount of driver fatigue. The pupil diameter values can be used to study driver fatigue. The Tobii Pro Glasses 2 eye tracker was used in this investigation to gather data. The NH-11 portion in Rewari, India, along the Rajasthan/Haryana border, was chosen as the study region. GPS tracking was done simultaneously to gather study area geometry data. At different sections of the road, pupil size and speed in relation to geometric data were evaluated for the purpose of detecting the amount of fatigue. According to a study, the driver is relaxed in the straight section which may contribute to fatigue and more anxious in the curved section. Along the same research tract, GPS position points were simultaneously taken during the day and at night. It was found that the size of the pupils dilated more at night than it did during the day. The reason is because the driver is more anxious at night daytime fatigue being greater than night time.

Risky driving behaviour (RDB) is one of the human factors that contributes to more road crash fatalities and injuries. Right-turning vehicular drivers with risky driving attitudes considerably increase the crash risk at unsignalized T-intersections. Therefore, this study aimed to investigate the major contributing factors to risky driving behaviour. A questionnaire was developed to obtain the driver's opinion on RDB at unsignalized T-intersections. Multiple correspondence analysis (MCA) was used to understand how factors related to demographics and riding information affect the RDB. The study results showed that male drivers are more dangerous than female drivers. Moreover, the drivers aged between 25 and 44 years with more travel distance and travel frequency showed higher risk-taking behaviour. The study findings also concluded that the travel modes (viz., autorickshaw and truck or bus) are perceived to be more dangerous than the other travel modes. The authors believe that the findings of the present study might be useful for traffic engineers and safety experts to understand the contributing factors to RDB and to take suitable traffic management measures to reduce crash risk at unsignalized T-intersections.

Driver Monitoring Systems (DMS) play an important role in improving road safety by actively monitoring driver behaviour and alertness while driving. The Cipia-FS10 device, distinguished by its cutting-edge computer vision capabilities, expands its ability to increase driving safety. This revolutionary technology meticulously records critical variables such as head position, eyelid movement, and gaze direction, delivering an instantaneous assessment of the driver’s condition. The study focuses on examining warnings generated by the DMS, which was incorporated into ten buses running along the renowned NH-65 Inter-Urban corridor, stretching 200 km from Hyderabad to Vijayawada (HYD-VIJ). The article aims to examine the risky behaviours displayed by bus drivers along this route, resulting in increased road safety awareness and actions. The graphical depiction of alert frequency constantly coincided with evident trends, clearly demonstrating the DMS technology’s effectiveness. In addition, the study used a grey relation analysis approach to categorise alerting kinds and locations, revealing significant differences in alert creation. The findings from this study revealed an additional hierarchy of alert kinds and their relative importance in various areas of alert occurrence patterns. The spatial distribution of these notifications is visually represented as a heatmap. These findings contribute significantly to establishing a safer driving environment by methodically interpreting alarm patterns, highlighting DMS’s critical role in modern vehicle safety systems.

The use of personnel cars has increased recently, which has clearly resulted in a reduction of quality of the air. Pollutant emissions from moving cars are the main cause of air pollution in metropolitan cities. One of those main pollutants released creating a negative impact on the environment is carbon monoxide (CO). The current study was done at three different four-legged signalized intersections in the metropolitan city of Hyderabad to investigate how several aspects of traffic stream, such as approach volume (ATV), average queue length during red-light wait time (QL), area of intersection (AOI), and cycle time length (CT), affect CO concentrations (COC) levels at signalized intersections (SI). When predicting CO at SI, two models employing multiple linear regression (MLR) and support vector machines (SVM) have been considered. CO levels at three signalized junctions were obtained as 9 ppm for Gandimaisamma crossroads and 12 ppm for both Bachupally and Pragathinagar HTL crossroads. The increment in COC with increase of CT, QL and ATV and decrease of AOI was noted due to the rapid movements of the vehicles at the signalized intersections. The models exhibit a certain simulated COC and field COC are resulting same sets of roadway and traffic conditions through validation. The results shown that MLR having a prediction accuracy of 0.96 with R², MAPE of 4.4, whereas R² obtained using SVM is 0.98 and MAPE of 4.04, which indicates SVM based simulation predicts the CO concentration more accurately than MLR simulation.

The transportation network is straining to keep up with the increased traffic as a result of the mixed traffic system and unregulated growth of private modes. Over-speeding and congestion are the two main issues for urban planners. Speed management measures and effective enforcement are necessary to reduce over-speeding, which is the major cause of traffic accidents. Hence this study works in finding an efficient measure to achieve traffic speed management and thus examines how well Automatic Number Plate Recognition (ANPR) and The Infra-Red Traffic Logger (TIRTL) systems function in terms of collecting traffic data and identifying over-speeding vehicles. Results revealed that the ANPR correctly detected only 51% of the total vehicle classes, whereas TIRTL correctly detected 96% of the vehicle classes. A maximum speed reduction of 20 km/h has been observed in the car, with an average speed reduction of 8 km/h. Finally, the developed ANN model might aid urban planners in creating new speed management technique efforts by properly estimating the correctness of the speed management technique in an urban setting.

Road accidents are becoming a major cause for loss of life and property, and their number is showing a tremendous increase worldwide. One of the major steps through which road safety can be increased is by properly designing the road geometry. Reliability analysis was used as a tool for safety analysis of different systems. In highway analysis, deficiency in geometry results in undesirable manoeuvres which may not result in accidents, but is also considered as a failure of highway system. Application of reliability theory in highway analysis helps in considering the stochastic behaviour of drivers. The study considered 22 crest vertical curves located in northern districts of Kerala. The roads chosen were two-lane rural highways. Reliability analysis was conducted based on stopping sight distance, length of curve for stopping sight distance and length of curve for intermediate sight distance. Data pertaining to highway geometry, spot speed and accidents on the selected curves were used for conducting the reliability analysis. The accident data collected was transformed into Equivalent Property Damage Only (EPDO) and utilized as the metric for curve safety assessment. Reliability indices were determined and used to establish a safety evaluation criterion for crest vertical curves, representing their reliability. A Safety Performance Function was formulated for crest vertical curves based on these reliability indices.

Traffic flow characteristics at diverging sections of roads are different from those at mid-block sections on account of the merging and diverging manoeuvres of vehicles. A study was conducted to assess traffic characteristics at diverging sections of four-lane divided urban roads. The objective of the study was to analyse the variations in speed, flow, and headways of vehicles at the diverging sections. A four-lane divided urban road in Kozhikode district, Kerala, India was chosen for the study. Data was collected using video recording and TIRTL at the diverging and mid-block sections for observation stretch of 100 m. Speeds, headways, and traffic volume data were extracted and analysed. During peak and off-peak periods, vehicle speeds reduced by 20–30% and 15–25% respectively. Probability distributions showed that vehicle speeds follow a normal distribution, while headways follow log-normal and GEV distributions. The study site was also modelled using VISSIM, with inputs such as geometric details, speeds, traffic volume, and composition. Various scenarios were analysed to identify the changes in vehicle speeds and headways at the diverging section.

Metro interchanges play a crucial role in ensuring the efficiency and effectiveness of a metro system by facilitating seamless transfers, reducing travel times, and enhancing the overall commuting experience. Well-designed and well-maintained interchanges contribute significantly to the success of a metro network by providing efficient connectivity and promoting public transportation usage. This research aims to study, identify, and prioritize the significant parameters essential for the planning and design of metro interchanges. Additionally, it aims to develop a composite level of service for metro interchanges to enable their comprehensive evaluation. The proposed approach utilizes a mixed methods methodology that incorporates various surveys and analytical techniques, including primary surveys, clustering analysis, and the analytical hierarchy process. A case study of four metro interchange stations in Delhi was chosen in order to comprehend the current user behaviour and determine the composite level of service. In order to calculate the overall quality of service and rating, user opinions were gathered to evaluate the degree of service for each parameter. The effectiveness, functionality, and user experience of metro interchange stations are all evaluated. This is accomplished by using the metro interchange composite index, a thorough measures that takes into account a number of interchange infrastructure components, including safety, comfort, convenience, universal accessibility, interchange time, information provision, and facilities as observed through user behaviour. The findings of this research provide valuable insights for urban planners, transportation authorities, and metro system operators. By identifying and improving the significant parameters, such as accessibility, signage, wayfinding, safety, and aesthetics, metro interchanges can be optimized to enhance overall efficiency and user satisfaction. In summary, this research presents a comprehensive approach for evaluating metro interchanges, encompassing effectiveness, functionality, and user experience. The utilization of the metro interchange composite index provides a robust framework for assessing and improving the performance of interchange stations. By considering user behaviour and preferences, this study contributes to the development of more user-centric and efficient metro systems.

This project aimed to study the Gandhinagar Intersection design in Belgaum City, India, where the traffic is proliferating and causing congestion and safety issues for vehicle movement. The objective is to provide an alternate proposal to the inefficient intersection in Belgaum City that connects NH-48. This intersection caters to many vehicles, including commuters, commercial trucks, and public transportation. Over time, the existing intersection has experienced increasing congestion, leading to delays, reduced capacity, inefficient operation of the Intersection, and compromised safety for motorists and pedestrians. To address these challenges, an initiative for alternate proposals has been undertaken, focusing on geometric and traffic design elements. The alternative proposal aims to focus on improving the traffic flow, reducing congestion, and enhancing the safety of road users. To satisfy the above needs, a proper geometric design for smooth traffic movement needs to be planned. Based on the data analysis from the study, it is recommended to shift the existing pedestrian underpass to align it with the current crossroads for smooth vehicle and pedestrian movement. Also, it is recommended to provide a service road on the RHS of NH-48, with the required gradient, up to the Airport Road underpass to provide connectivity with NH-48.

Pedestrian deaths constitute to about 23% of the road deaths globally. Although several researchers have contributed to the pedestrian safety analysis, arriving at comprehensive solution requires an in-depth study. This is attributed to various complex factors involved at the pedestrian crossings, in a typical urban scenario. Pedestrian path for crossings mainly depends on the spontaneous interaction with the space available. This phenomenon is rather a psychological reaction of the pedestrian rather than aspects to safety and comfort. This work identifies the traffic conflict situations between pedestrian and vehicles in a typical urban scenario. A discrete model for the same is analysed for the urban scenario. For the work, three multilane intersections with high pedestrian volumes in the city of Bengaluru are used for the study. Patterns of travel both for pedestrian and vehicles are observed with videographic data. The lateral and longitudinal critical distances between pedestrian and vehicles are measured and calibrated using an open-source software ‘tracker’, for real life scenario. Statistical analysis and regression are undertaken to assess the pedestrian behaviour at the urban intersection crossings. The approach chosen is realistic and can be used for studies especially for intersections with heterogeneous traffic conditions.

This study focuses on optimizing toll plaza design by considering queue areas and the required number of lanes. Data from seven Indian toll plazas, collected at five-minute intervals, were used to establish a linear relationship between average and maximum queue length. Additionally, Level of Service (LOS) thresholds were developed based on queue length using k-means clustering. Notably, the study takes into account queued vehicles, making it easier to estimate vehicle counts in real field conditions. Findings indicate that for design LOS-C, the queue area should be 102.00–174.24 m long. Queue length is also linked to queue delay, aiding in tollbooth clearance time determination. Furthermore, the study assesses the impact of increasing Electronic Toll Collection (ETC) usage, known locally as FASTag, on the required number of toll lanes. This research serves as a valuable resource for field engineers designing queue areas and toll lanes, addressing current traffic conditions.

The grade-over facilities are provided for crossing pedestrians in urban regions, but still, it is observed that people are reluctant to use the facility. Hence, the primary focus of the present study is to evaluate the factors affecting pedestrians using and not using the Foot Over Bridges (FOBs). The results showed that avoiding accidents is the primary motivation for all users to use FOB. Further, the results showed that improving cleanliness at FOB can tend most users to use FOB. Further, the nonusers of FOBs gave more preference to the location of FOB from the point of crossing. Results showed that placing the FOB close to bus stops can motivate nonusers to use the FOB. Additionally, the results showed that pedestrians preferred FOB in the region near recreational zones if cleanliness and lifts/escalators were provided.

Socio-economic progress of a society creates an additional burden on road infrastructure due to increase in the number of vehicles and in turn road crashes. The identification of road sections characterized by frequent crashes is the first step for any successful road safety management process, considering the limited available resources. Emergency Vehicle Services (EVS) is a crucial component in road crash management. This study focusses on the effective distribution of emergency vehicle service resources across a road network. Ernakulam District is taken as a case study. Sixty two black spots are identified in the study area based on accident severity weightage estimated using PTV Visum Safety. The locations of the black spots are then transferred into QGIS along with the locations of 24-h working hospitals and ambulance services in Ernakulam district. KANIV-108 ambulances are also incorporated into QGIS and a geo-spatial analysis is done to find the fastest routes between ambulance service station locations, black spots and hospitals. The sixteen black spots which cannot be reached within the platinum time are assigned to new emergency vehicle service centers proposed at proper locations identified. This work will be helpful in the efficient deployment of emergency vehicles so as to minimize the response time to a road crash in the area.

Typically, every city boasts its unique backdrop, characteristics, and challenges; however, urban difficulties in India exhibit similarities to those encountered in developed nations. The urban landscape of the country is marked by highly diverse traffic patterns, often lacking in lane discipline. Vehicles not only interact with those directly ahead but also with nearby ones, necessitating a deep understanding of lane-changing dynamics and their impact on traffic flow. Analyzing driver behavior in such scenarios, especially along mid-block segments of urban roads, presents significant complexity. This research focuses on extracting vehicular trajectory data from mid-block locations under varying traffic conditions to identify patterns in vehicle following and lane-changing behavior. The primary goal is to develop a driver behavior model that considers safe speed differentials between leading and following vehicles, along with the necessary clear space to prevent rear-end collisions. Additionally, it seeks to establish guidelines for maintaining safe lateral distances and speeds to reduce side-swipe collisions. This entails determining Time to Collision (TTC) thresholds based on following vehicle speeds and Safe Lateral Distance (SLD) thresholds using k-means clustering aided by a Python tool. Subsequently, risk levels are categorized into high, medium, and low tiers. The modeling phase employs Gradient Boosting Regression (GRB), Support Vector Machines (SVM), and Random Forest Algorithm (RFA) techniques.

According to MoRTH (Ministry of Road and Transport Highways, Bharat), in Bharat, were recorded 1,53,972 persons killed by road accidents only in the year 2021. At least 1 out of 10 people killed on roads across the world are from Bharat. Globally, Bharat ranks second in terms of number of road accidents and ranks first in the number of persons killed per lakh people. Traffic injuries are not equally spread over the world, however; some countries are hit harder than others, and the chance of being killed in a road crash depends on where one lives. The paper explores critical factors influencing road safety and proposes effective strategies for mitigating accidents and fatalities. It analyzes the multifaceted nature of road safety, incorporating elements such as probable causes, severity index, and blackspots. By examining statistical data, the paper underscores the importance of comprehensive road safety measures. The paper identifies major blackspots and a three-year consolidated severity index. Additionally, it addresses the significance of public awareness campaigns, law enforcement, and policy development in fostering a safer road environment. Sarkhej-Gandhinagar highway is taken as a case study. The findings highlight the need for a holistic approach that integrates technological advancements with behavioral interventions. Ultimately, this paper contributes to a deeper understanding of the intricacies involved in road safety and provides valuable insights for policymakers, researchers, and stakeholders striving to reduce road accidents and safeguard human lives.

Safety of Powered Two-Wheelers (PTWs) is a major concern in many low- and middle-income countries. However, studies on PTWs’ safety and the occurrence of different crash types are relatively scarce. The present study uses the proactive safety approach to investigate the effect of traffic states on PTWs’ safety in mixed and weak-lane-disciplined urban traffic. A multidimensional surrogate safety measure called Anticipated Collision Time (ACT) was used to identify the rear-end and side-swipe conflicts involving PTWs. The study estimates the crash risk of PTW riders using the extreme value theory (EVT) approach. The results revealed that the side-swipe crash risk of PTW is higher than that of the rear-end when the traffic operates at below-capacity conditions. But for congested conditions, both rear-end and side-swipe crash risks remain the same. The higher side-swipe crash risk is due to the frequent filtering and overtaking maneuvers of PTWs and higher relative speeds during low-density conditions. Therefore, necessary measures must be taken to discourage or avoid such maneuvers of PTWs in low-density conditions. The findings will also be beneficial for PTW rider training programs as well as for implementing risk mitigation strategies on urban roads.

Roundabouts are characterized by heterogeneous traffic flows, which can be challenging for pedestrians due to their design. The unique circular design of roundabouts necessitates pedestrians to adapt their conventional crossing behaviors, considering factors such as varying vehicle speeds, dynamic traffic flow, and the absence or presence of crosswalk markings. The objective of this study is to comprehensively examine and analyze pedestrian crossing behaviours and safety at two distinct roundabout locations. The analysis looked into various aspects of pedestrian behaviour and crossing patterns and revealed a significant occurrence of path change behaviour among pedestrians, particularly at exit points, indicating the dynamic nature of pedestrian movement within roundabout. The safety of pedestrian crossings at roundabouts under mixed traffic conditions was evaluated and Time to Collision (TTC) was chosen as the Surrogate Safety Measure (SSM) for conflict analysis. The two-wheeler’s TTC value was the lowest among the three selected vehicle categories. By comprehensively understanding the intricate dynamics of pedestrian movements, city planners and policymakers can make informed decisions to enhance pedestrian safety and optimize traffic flow and create more efficient and secure urban environments.

The road construction and maintenance activities are an integral part of road life cycle. The accident rate is more in construction corridors. Lower speeds are necessary along construction corridors considering safety of road users and construction crew. This study is conducted to investigate the actual vehicular speeds maintained along the construction corridors on national highways, as compared to the standards. Also, an attempt is made to quantify the effectiveness of road safety adopted on heterogeneous traffic speed behaviour along the construction corridors. Speed studies are carried out along ten construction corridors, identified enroute where upgradation of existing 4 lane divided carriageway to six-lane national highway, connecting Bengaluru to Mysuru, in the state of Karnataka, India. The geometrics onsite have been compared with the standard requirements. The rate of speed reduction through the advance warning zones towards the work zone for the vehicular traffic was found to be around 23%. The rate of increase in the speed was observed to be around 18% for the vehicles exiting the work zone. The studies concluded that the heterogenous traffic exceeded the permissible speed limit by 75–88% along the construction corridors. However, the rate of speed reduction and increase was found to vary for different vehicle categories. This study forms a window to understand the traffic behaviour along the construction corridors in similar geographical areas.