Advances in Human Aspects of Transportation

When designing experimental studies in the driving domain, an important decision is which driving scenarios to include. It is proposed that HMI need to be adaptive to the complexity of the driving situation, in order to avoid overloading the driver. To further study adaptive HMI a comprehensive list of factors that determine the perceived complexity of a driving situation is required, yet absent. In this, infrastructure- and traffic characteristics that may influence the perceived complexity of a driving situation were collected from literature. Next, four sets of driving scenarios of varying complexities were created and validated in an online survey. The results of this study include: 1) a list of infrastructure- and traffic characteristics that influence the overall complexity of a driving situation, and 2) validated scenarios of varying complexities. These outcomes help researchers and designers in setting up future driving studies.

The present study is intended to develop statistical models for predicting automobile seat fit based on the relationships between seat dimensions and subjective seat fit. The evaluations of the subjective seat fit for 43 different driver seats and the seat dimensions at six cross-sectional planes (three for the seatback and the other three for the cushion) were measured and evaluated by eight seat-engineers. The best subset logistic regression analyses were conducted to quantify the relationships between the measured seat dimensions and evaluated subjective seat fit at each of the cross-sectional planes. As a result, significant seat dimensions, such as insert width or bolster height, on the subjective seat fit were identified. The developed logistic models show 90% overall classification accuracy at each section with 80% accuracy with five-fold cross-validation. The developed models would be particularly useful to support seat engineers by providing recommended seat dimensions, which could increase seat fit. In addition, the model is useful to reduce development costs for an automobile seat and increase work efficiency in the digital evaluation process of an automobile seat.

In order to guarantee user acceptance and functional safety of automated driving functions, a large number of real driving maneuvers are needed to represent real possible traffic scenarios. Evidence has indicated that people had different driving characteristics based on their demographic and socio-economic characteristics as well as their sensation-seeking score or their assessment of driving costs and benefits. A detailed analysis of driver personality operated in a naturalistic driving study investigates the significant influence of driver characteristics on driving behavior using statistical analysis methods to identify different driver types.

The use of the mobile phone is one of the main contributors to driver distraction. Extensive scientific literature has addressed the issue of driver distraction, highlighting the negative effects of mobile phone use (i.e., calling or texting) while driving. Currently, only a few studies have investigated the effects of social networking activities while driving. The aim of this study is to assess the effect on driver performances and road safety of mobile phone use for social networking activities using a driving simulator experiment. The data collected are analyzed and compared between the scenarios in terms of driving performances and surrogate safety measures. In addition, further information are collected using pre-test and post-test questionnaires. Preliminary results demonstrates the negative effects of using the smartphone for social networking activities on driving performance and road safety, exposing drivers to high levels of risk.

Previous studies suggest that variation in driver’s states, such as being under stress, can degrade drivers’ performance. Moreover, different drivers may have varying behaviors and reactions in different road conditions and environments (contexts). Thus, personalized driver models given different contextual settings can assist in better predicting the drivers’ states (behavioral and psychological); this can then allow vehicles to adjust the driving experience around the driver and passengers’ preferences and comfort levels. This paper aims at developing personalized hierarchical driver’s state models by considering driver’s heart rate variability (HRV) in relation to the changes in various contextual settings of road, weather, and presence of a passenger. Results from 12 participants over 150 h of driving data suggest that drivers are on average less stressed in highways compared to cities, when being with a passenger compared to alone, and when driving in non-rainy conditions compared to rainy weather.

Emerging automated vehicles and mixed traffic flow have been substantially increased demand for modeling human driving behavior in both academia and industry. As a result, many car-following (CF) models have been proposed using parametric and data-driven approaches. Considering the large number of CF models, the critical question is which CF model or category of models (e.g. machine-learning) could accurately regenerate human CF behavior. This study conducts a cross-category comparison between one parametric model (intelligent driver model (IDM)), two new machine-learning CF models based on feedforward neural network (FNN) and recurrent neural network (RNN), and one novel deep-learning CF model (Deep-RNN) with long short-term memory (LSTM). The models are developed in TensorFlow and compared at local and global levels. At the local level, Deep-RNN significantly outperformed the others, followed by RNN and FNN. At the global level, IDM demonstrated the best performance, followed closely by Deep-RNN. The result illustrates there is no one-size fit model and the model should be selected given projects’ characteristics. The result suggests a hybrid approach, which integrates parametric and deep-learning models, could precisely regenerate human car-following behavior.

Despite the “driverless” term, drivers of automated vehicles still constitute an integral part of the human-machine team that will be driving the future. This study emphasized drivers by evaluating the attentiveness, stress levels, and reactions of 67 participants, ages 18–65+ years, during a sudden, total disengagement of automation in a driving simulator-based rural freeway setting. Attentiveness was characterized by a significant increase in gaze fixation and a significant decrease in fatigue, yet stress levels did not appear to significantly change. Regardless of age, gender, or level of non-driving related task involvement, participants reacted to the failure first by steering, requiring 12.30 s (50th percentile) to 29.26 s (90th percentile), followed by speed control after 18.26 s (50th percentile) to 40.86 s (90th percentile). These findings highlight the need for addressing the potentially dangerous implications of automation failure.

Most Koreans have mobile and their location information is collected based on location of the base station in one second increments. Mobile base stations are installed at intervals of 50 m in cities, and up to 2 km apart in rural areas. We developed an algorithm that builds an individual trip chain using mobile base station data and distinguishes home from work area by analyzing daily traffic patterns. The purpose of this study is to analyze traffic generation unit and traffic characteristics through seamless trip chain analysis of individual mobile base station data. A new method and experimental approach are established to estimate the passenger O/D based on mobile base station data. A new method has been analyzed to overcome many of the shortcomings of the existing O/D estimation methods that are based on household surveys, such as zero cells and inaccuracy due to low sampling rates.

This study explores the impact of cues provided by the full windshield head-up display (FHUD) on the visual attention allocation of the driver under different scenes. The full windshield highlights situational cues related to the driving task. In terms of the perception of situational cues, FHUD changed number of fixations and mean fixation durations of drivers. Number of fixations and mean fixation durations in the condition with FHUD were lower than that in the condition without FHUD. In the terms of percentage dwell times in area of interest (AOI), percentage dwell times in front of the field of vision of the driver in the condition with FHUD was larger than that of the control condition, percentage dwell times on both sides was smaller than that of the control condition. It indicated that FHUD could help drivers’ more effectively perceive cues and improve drivers’ visual attention allocation.

We examined the necessity for plausibilization of test scenarios within usability studies for AV HMIs in driving simulator studies. One group of drivers experienced system-initiated transitions without any obvious reason, the other with plausible reasons (e.g. fog for L3 → L2 transition, broken-down vehicle for L3 TOR). The results showed that reaction times to TORs were not influenced by the plausibility while the type of reaction was. Drivers reported less system trust but still knew how to react to the transitions. Non-plausibility did not negatively affect system acceptance. It can be concluded that plausibilization is not necessarily required for all kinds of research questions.

The purpose of this study was to avoid off-road glances of drivers while operating steering wheel mounted switches. However, a large number of switches on multi-functional steering wheel give rise to difficulties in memorability and finger-reaching and require hand-eye coordination. The ideation and prototyping process is as follows. Firstly, we integrated three directional entry sets into one, accompany with a function mode switching button for circulating selections of “radio control mode”, “cruise control mode” and “digital dashboard display control mode”. Secondly, we employed natural finger positioning (NFP) strategy and introduced multi-finger pull gesture NFP device for more effective blind-positioning movement of controlling directional entry keysets. Thirdly, to avoid function mode confusion, the “voice prompt upon key operation” is provided and proved to be much effective in the feasibility test. It allowed subjects to acknowledge the status of function mode timely and reduce operation errors.

Human-machine cooperation (HMC) is often still rigid and unintuitive. However, with more ability transferred to machines, the need for intuitive cooperation rises. To achieve this, new concepts need to arise and be implemented for machines to get a better understanding of their cooperation partner and to be able to act as expected. This includes adapted cooperation schemes based on actual dimension of control, e.g. conscious or subconscious HMC. In this paper, we give an overview on a generic architecture designed to achieve intuitive HMC and introduction to an example application.

Each year, there are thousands of road accidents in the United States. The issue has led to additional safety adaptive features in recent cars of which many complained about the safety and the cognitive workload impacts on decision-making processes of some of the features, particularly the ESMS. The study aimed at increasing public awareness on the potential safety of ESMS support in cars. Nine websites (710 public comments) and two articles were reviewed, including. The comments were categorized into positive and negative impacts. Of the 710 comments, 73% were negative and only 27% were positive. Findings highlighted possible hazards associated with ESMS in cars such as image obscuration, high display brightness in dark driving conditions, poor visibility during raining, distraction, etc. Manufacturer improvement on the ESMS was also suggested. Findings from this study would add to the available knowledge on ESMS for the National Highway Traffic Safety Administration (NHTSA).

In the era of 5G and intelligent development, the layout and architecture of the Internet of Vehicles are slowly being established. In the future, the urban travel system will gradually become a research hotspot in the automotive field. Mobile mobility services are an important part of smart cities. The combination of multi-modal transportation, shared travel, electric vehicles, and autonomous driving is an important direction for automobile industrial transformation. In order to study the future transportation service system, This article will build a new type of transportation service system from the perspective of social supply and demand, improving user experience and promoting trilateral win-win situation. The combined market users cognitive model theory of the present system, logic and feasibility.

Accurate speed control can effectively improve the efficiency of train operation. The advantages and disadvantages of the speed display form directly impact the interaction efficiency and the driver’s correct situational awareness of the train running state. Three kinds of train speedometer forms were designed, and the existing interface was compared with the three types. 28 subjects were selected to carry out four speed control experiments. The results showed that, the response time and accuracy performance were the highest in the case of color highlighting; the response time performance was higher but the accuracy performance was the lowest in the case of graph without numbers; the accuracy was higher but the response time was the lowest in the case of scale sparsity. This study shows that the speed display design should be give priority to color highlighting, while weighting the influences of number highlighting and scale sparsity.

High-risk organizations are inherently complex and depend on the latest technologies to survive and function properly. Therefore, introducing new technology to such an organization is inevitable. Studies show that the installation of new technology always involves some changes to the organization and its members. The railroad industry, as an example of a high-risk and safety-critical organization, strives to avoid catastrophic events, while performing dynamic tasks under strict time constraints, operating technology posing large-scale physical hazards. High Reliability Organizations (HROs) are a subset of high-risk organizations designed and managed to avoid such accidents. This paper discusses the adaptation of HRO principals as part of the implementation process for the Positive Train Control (PTC) technology in a safety-sensitive railroad organization.

Playing a crucial role in the start of high-speed train driving, braking test is a necessary task to be conducted before train departure. In the train braking test, a driver needs to make a quick response according to a hint displayed on the human-machine interactive interface screen and then operate a driver’s master handle to the designated position. This paper makes a braking test for the driver’s operations of a Chinese CRH train based on the application of an eye tracker. Then, through analysis of eye movement data involved during the interaction, vision characteristics of the interaction are illustrated. The research result is of referential values to design optimization of man-machine interaction interfaces.

For the purposes of relief of drivers’ working strength and spiritual stress and increase of working efficiency, this paper studies design of the metro train’s driving interface and comes up with an optimization proposal aiming. Firstly, investigation survey is conducted on drivers’ driving satisfaction; secondly, importance and use frequency of equipment are surveyed; thirdly, drivers’ driving operation processes are recorded with videos, the tracks of drivers’ operation processes are analyzed; fourthly, based on the above survey analysis, an optimization design proposal for driving interface layout is proposed, while man-machine verification of the proposal is conducted with the JACK virtual simulation technology; and finally, drivers’ overall satisfaction with the optimization proposal is investigated. As shown in the results, the optimized proposal is advantageous in rational layout, convenient operations and clear tracks of operation processes, which can help relieve drivers’ driving strength effectively and increase their satisfaction significantly.

To achieve the operational objectives of intercity trains, in particular, reducing the station dwell time, it is necessary to improve the boarding and alighting efficiency. The vehicle layout considerably influences the boarding and alighting efficiency. In this paper, a method to simulate pedestrian dynamics is proposed. The effects of three layout factors on the efficiency are investigated; furthermore, the regression curves of different factors and cumulative high density maps are considered for analysis. The results show that when the door width ranges from 800–1900 mm, the relationship between this width and the boarding and alighting efficiency is a quadratic function. When the hall width ranges from 1300–2100 mm, the relationship between this width and the efficiency is a power function. When the aisle width ranges from 650–950 mm, the relationship between this width and the efficiency is a cubic function.

Vehicle-to-infrastructure (V2I) technologies are known as the next generation of intelligent transportation systems (ITS), enabling data transmission between vehicles and road infrastructure. V2I communication models offer a variety of safety, mobility, and environmental applications in smart cities. Another innovative concept within the ITS is the human-to-infrastructure (H2I) communication model. H2I deals with the vulnerability of the users to damages and deteriorations of civil infrastructure. While many studies deal with V2I, limited research has been conducted in the area of interaction between humans and transportation infrastructure systems. This study presents a comprehensive review of the current studies in the arena of V2I and proposes the vital basics for establishing a robust H2I model for the next generation of the smart, civil infrastructure systems.

Driver assistance systems have been in use for a decade and the automated vehicles are expected to hit the market soon. Collaboration between drivers and assistance systems, especially in SAE Level 3 of driving automation, plays a significant role as it is directly related to driving safety and the acceptance of automated vehicles. This contribution proposes driver state feedback control as a possible method for taking the driver state into account in driver-vehicle interaction. The feedback control creates a loop in which the takeover request affects the driver state and the driver state adjusts the takeover request. The functionality of the proposed interaction method is examined in an exemplary experiment on a driving simulator with twenty participants in which the gaze direction of drivers acts as a sensory state. The results indicate an improvement in the performance of drivers during the takeover situation by involving driver state in the design of the takeover request.

The development of driving automation is one of the major topics in automotive engineering and is progressing at a fast pace. One key to the success of these systems is the acceptance by users and the actual usage. Surveys on the potential usage and acceptance have shown that the higher the automation level, the higher the acceptance and willingness to engage in side-activities. A driving simulator study with N = 61 was conducted with a between-subject design to compare the acceptance and usage of a conditionally (L3) and a highly (L4) automated driving system (ADS). Drivers were free to use the ADS as they liked. Results show that when using the L3 ADS, drivers spent more time on non-driving related activities and drivers using the L4 ADS spent more time with their eyes closed. The overall acceptance of the L4 ADS was higher.

Increasing urbanization and the simultaneous growth of car-based individual transport pose major challenges for many cities. On the one hand, streets and parking facilities are reaching their capacity limits, and on the other hand, car emissions are a burden for both residents and environment. A transformation from one-person car use to emission-free shared mobility could be part of the solution. Small autonomous, electrified shuttle buses, which can carry 10–15 people on-demand, are already in the technical development stage. At present, however, many questions remain unanswered regarding the design of mobility services around the technological platform. This paper therefore explores which factors influence the willingness to share rides and to abandon private car ownership. While for the willingness to use ridesharing, especially the familiarity with the passengers and, to a small extent, the purpose of the trip has an influence, the expected advantages in terms of flexibility and costs are particularly important for the willingness to abandon a car. A positive attitude towards conventional car driving counteracts both measures surveyed.

With the introduction of ADAS systems and vehicle automation, an interface informing the driver of the automation state is required. This study evaluates the suitability of a visual interface comprising up to 64 LEDs on the steering wheel perimeter; it displays continuous visual feedback about the automation state—including notifications of an unscheduled hand-over due to sudden system failure. Three HMI (Human Machine Interface) designs were evaluated: two versions with visual cues on the steering wheel and one without (baseline). We implemented the designs in a driving simulator and compared the subjective responses of 38 participants to questionnaires measuring user experience, trust, and acceptance. The designs with visual cues improved the participants’ user experience, as well as their trust in, and acceptance of, automated vehicles. Moreover, both designs were well perceived by participants.

As the shift from manual to automated driving occurs, the driver will be required to take a supervisory role in monitoring the driving environment and system parameters. Driver State Monitoring Systems (DSMS) have been proposed to evaluate the state of the driver and provide support for driver engagement. However, it is not clear how a DSMS may impact attentional mechanisms. Nineteen young adults (mean ± SD age = 19.58 ± 0.94 years) experienced a simulated semi-autonomous driving journey. Participants’ visual attention via eye tracking fixation and visit metrics were compared before, during, and after two distinct notifications designed to enhance driver engagement. The first notification displayed biofeedback changes in physiological state; the second notification provided speed limit changes. Results revealed participants spent longer attending to the outside driving environment during biofeedback. The results suggest the potential for feedback based on relevant physiological parameters to enhance global visual processing strategies during semi-autonomous driving.

Severe weather conditions, such as heavy snowfall, rain, heatwave, etc., may affect travel behaviors of people and finally change traffic patterns in transportation networks. Hence, this study has focused on the impacts of a weather condition on travel patterns of public transportations, especially when a heavy snowfall which is one of the most critical weather conditions. First, this study has figured out the most significant weather condition affecting changes of public transport ridership using weather information, card data for public transportation, mobile phone data; and then, developed a decision tree model to determine complex inter-relations between various factors such as socio-economic indicators, transportation-related information. As a result, the trip generation of public transportations in Seoul during a heavy snowfall is mostly related to average access times to subway stations by walk and the number of available parking lots and spaces. Meanwhile, the trip attraction is more related to business and employment densities in that destination.

The usage of partially automated systems has transformed certain traditional driving into monitoring tasks. Simultaneously, drivers may voluntarily switch attention to engage in a secondary visual task. The main purpose of this study was to explore how individuals’ attentional networks (i.e., alerting, orienting, and executive control) influence their visual attention allocation between monitoring and visual secondary tasks. In this study, we simulated specific dual-task condition by a well-controlled monitoring task combined with a visual secondary task. Participants’ visual attention allocation behaviour and task performances were compared with their attentional functions measured by standard Attention Network Test. Two attentional components’ significant effects were found: First, participants with more efficient alerting network spent less time on the monitoring task and exhibited more frequent switching behaviour. Second, participants with more efficient orienting networks showed longer reaction times in the secondary task and conducted less consecutive secondary task trials in once switching.

There are always submerged risks involved with advanced technology; therefore, it is necessary for policymakers, inventors and technology companies to scrutinise potential risks when they consider implementing new technology. This paper attempts to extract generic lessons from a failure relevant to autonomous transport systems. We use fault tree analysis (FTA), a reliability block diagram (RBD) approach and failure mode and effect analysis (FMEA), for analysing a fatal pedestrian accident caused by a level-3 self-driving car in 2018. The work highlights the importance of prematurity of test driving self-driving cars on public roads and the potential of an insightful analysis method that can capture human factors. In this work we theorise accident reporting systems, and provide a framework for triple loop learning.

Rear-end collisions are one of the most common types of road accidents, often caused by the sudden deceleration of the leading vehicle during a car-following situation. In-vehicle applications based on Augmented Reality (AR) technology could optimize the driver’s visual attention, providing new and additional visual feedback to improve the driving experience. This study has focused on a new AR application aimed at improving the safety of rear-end driving conditions, by means of different AR video and audio warnings. A driving simulator study was carried out to test the effectiveness of the proposed AR system and assess the ability of drivers to avoid rear-end collisions, with and without the AR warnings, in an urban road scenario. Significant positive effects of the AR warnings on driving speeds and road safety were observed, mainly consisting in lower speeds, decelerations and reaction times and improved surrogate measures of safety.

This research investigated the effect of road geometric features and operational conditions on the occurrence and severity of traffic accidents at signalized intersections in Abu Dhabi city, UAE. Speed, number of lanes, lane configuration, traffic signal sequence (lead/lag or split phasing), average hourly traffic volume per lane were used as independent variables. The accident occurrence was tested by using Poisson’s regression modeling and the accident severity was examined by using multinomial logit modeling approaches. The Poisson model showed that at 4-leg intersections, one of the major causes of the accident, is passing of a street (either minor or major street) through the intersection. It was also found that at 3-leg intersection, the main cause of the accident is minor street passing through the intersection. The research also found that the higher the traffic volume the higher the chance of occurrence of traffic accidents. The multinomial logit model showed that five significant variables affect the severity of traffic accidents occurs at signalized intersections. the significant variables are the speed of the main road, traffic signal sequences, number of through lanes of minor road number of left lanes of main and minor roads.

This study implemented virtual environment technology to examine how the spacing and height characteristics of a column-type background arrangement affected collision-prediction accuracy for an approaching object set in vast virtual space. Participants were divided into two groups for testing, including the “safety-oriented type” and “accurate judgment type.” Results showed that participants in the safety-oriented type group tended to make collision/non-collision judgments at earlier stages, when columns were higher and more narrow. On the other hand, subjects in the “accurate judgment type” group tended to make accurate collision judgements at later stages (i.e., as column spacing increased).

At SAE Level 3 of driving automation, human drivers are not expected to continuously control the vehicle or monitor the driving environment. However, due to system limitations, drivers would be prompted to intervene and “take-over” the vehicle in certain instances. This brings into question the capability of human driver to take control after being out of the loop for prolonged periods. Distractedness has been identified and modelled in previous studies however, paucity exists with regards influence of drowsiness in the absence of a secondary task on take-over performance. This study discusses the effect of parameters like take-over request lead time and the degree of driver’s drowsiness on take-over performance. Experiments were conducted in a high fidelity driving simulator on 12 licensed drivers. Results reveal significant influence of lead time and degree of drowsiness on different performance parameters. Subjective scores of drivers also correlated with objective parameters of drowsiness.

Statistics affirm that traffic accidents are the main cause of death in developing countries. The indicators are alarming, so governments, manufacturers, and researchers have been looking for solutions to mitigate them. Despite all efforts to face this problem, the number of victims remains high. A significant percentage of traffic accidents are caused by external factors, so the search for solutions that use information from multiple sources is crucial. This article presents a traffic accident prediction system based on heterogeneous sources using data mining techniques and machine learning algorithms. The development of this system includes the following tasks: collecting information from different sources, performing cluster analyses and feature selection, generating new datasets, performing machine learning algorithms to define accident rates, and sending traffic rate levels to the vehicles. For this article, we focused on performing cluster analyses to determine high-risk clusters that identify drivers with risky driving patterns.

People want to be comfortable, and perception of what makes each user comfortable can vary greatly. This makes it important that vehicle products meet the different expectations of users through flexibility in their interior environment design. One of the most prominent predictions in personal mobility progression is a move towards shared autonomous vehicles. SUaaVE is a European project aiming at improving acceptance, trust and comfort of future shared automated vehicle users, through development of a system concept known as ALFRED. This paper presents a theoretical framework for an adaptive model, with comfort componentised into attributes. Application of the model aims to drive a response to vehicle user’s individual characteristics and preferences - such that their comfort can be optimised intelligently by manipulation of vehicle features and functions as part of the ALFRED concept.

We have focused on the unconscious movements of participants. Previously, we checked all video off-line to obtain the frequencies of participants’ movement. Although we could discuss the relationship between the subjective ratings of participants and the frequencies of the unconscious movements, we recognized that the visual judgment was too heavy for us to carry out. Thus, in this paper, we installed the body pressure measurement system. First, we analyzed time-series data of participant’s body pressures on the seat during some typical movements. As a result, we found the relationship between the movement types and the characteristics of the COP trajectories. Next, we carried out the driving simulator experiments. When we made a comparison between the frequency with the visual inspection of video images and those counted with the body pressure data, we found that there were some false detections with the analysis of the body pressure data.

Tricycles, consisting of a motorcycle for the driver and a sidecar for passengers, are a staple of Philippine transportation. With the amount of CO2 produced by tricycles, the Department of Energy and the Asian Development Bank spearheaded the creation of the “E-Traysikels”. While being environmentally friendly, it is also important for the design to be ergonomic, thus, the study aimed to assess the fit and comfort to Filipinos of the “E-Traysikel”. Dimensions of the e-tricycle were compared to corresponding Filipino anthropometric dimensions. Postures of selected passengers and drivers were taken and assessed using Rapid Entire Body Assessment and Rapid Upper Limb Assessment. Perceived comfort when riding the e-tricycle were also gathered. Results showed multiple parts of the “E-Traysikel” are smaller than corresponding anthropometric measurements. REBA and RULA scores range from acceptable to medium risk. Recommendations were provided to increase the comfort of the “E-Traysikels” for the passengers and drivers.

Ergonomic design of heavy truck cabs has a significant impact on road safety and driver health. In the design phase of the cab, a full understanding of the driver’s driving posture and operating habits is the necessary foundation for the human-machine interface design and the requisite guarantee of a good driving experience. However, at present, in the design of heavy truck cabs in China, insufficient consideration is given to the driving habits of drivers, resulting in poor ergonomics and user experience complaint. Through interviews and questionnaire surveys with heavy truck drivers with the static method of significance testing, this article investigated and analyzed the characteristics of professional truck drivers’ driving postures and the frequency of operating actions which provides improvements suggestion to the ergonomic design and the driving experience of the truck.

This study used the Vicon motion capture system to record the spatial positions of the points and to obtain the range of five joint angles in comfortable driving positions for Chinese men and women. The data could provide basic reference data for the establishment of the human body template to do the ergonomic verification of Chinese automobile cab.

Three different road environments (urban, suburban and rural) were implemented in a fixed – base driving simulator. Forty – five participants drove the three road environments in which two zebra crossing with a pedestrian that crosses the road were implemented: in one case, the driver was helped by the Pedestrian Collision Warning System (PCWS) which provided a combined visual-auditive warning, while, in the other pedestrian crossing, the warning system was absent. The recorded interaction conditions between driver and pedestrian during the tests were classified in three groups according to Time To Zebra arrive $$ \left( {{\text{TTZ}}_{\text{arr}}^{*} } \right) $$ . Results showed positive effects of PCWS that induced the driver to reach lower speeds in presence of that system, improving the general risk conditions at which the pedestrian is exposed during the interaction with drivers at crossroads.

The growth of the European market for road-freight transport has recently led to important changes. Moreover, due to the geographical context of France, truck drivers from different countries circulate on French roads to deliver their goods. Having road safety concerns in mind and based on a literature review, as well as interviews, a French questionnaire has been developed. Aiming at collecting data among truck drivers from different European countries, the questionnaire has been translated into seven languages and has been administered at four highway rest areas in France. The collected data were analyzed by means of multiple correspondence analysis, which pointed out new links between working conditions, driving behaviors, perceptions of the road environment, job skills, and risk factors. The practical implications of the results for improving the safety of the infrastructure used by truck drivers and their well-being are discussed.

This present paper is to apply the Systems Theoretic Accident Model and Process (STAMP) and its corresponding the Causal Analysis using Systems Theory (CAST) as an innovative method to analyze a road traffic collision involving a goods vehicle travelling downhill ostensibly caused by a brake failure on a mountain road in Vietnam. The developed STAMP-CAST model of the collision under study showed that although driver’s inexperience, together with the truck’s low quality and severe road conditions were found as potential factors directly leading to the collision, the inadequate control actions of various actors residing at higher levels of the Vietnamese road transport system also contributed to the crash.

This study examined the effect of Perceived Contrast Enhancing (PCE) lens technology on traffic signal detection and recognition for color-normal and color-deficient observers compared to a neutral density lens. Eighteen color-normal and eighteen color-deficient participants performed a visual-motor task while wearing two different PCE lenses with specific spectral transmissions as well as a neutral-density lens. At random intervals, simulated traffic light signals were presented 5° to the right and left of the participant’s focal point, to which participants identified signal color using a three-button input device. Response time and error rate were recorded. We found that lens tint did not have a significant main effect on response time and error rate. The data collected in this study lends considerable evidence to the assumption that PCE lenses will not impair driving.

Particulate matter and greenhouse gas emissions are two of the main challenges of current mobility. The switch to electric drives, especially in motorized individual transport, could be part of the solution. However, the number of registrations of private battery electric vehicles (BEV) in Germany is currently increasing only slowly. Among other things, some user groups are currently difficult to address with electro-mobile offers, especially car drivers without their own parking space who would be dependent on public charging facilities. Semi-public charging stations, which are used by companies or authorities in certain periods of the day and are made available to the public outside these times, could be an additional offer here. Therefore, the aim of this paper was to better understand the users’ requirements for semi-public charging stations and to identify possible trade-offs. The results revealed that the station’s distance to the destination was the most important attribute followed by the temporal availability, the obligation to re-park, the costs, the surroundings, and finally the charging strategy. In contrast, user factors were of minor importance for the usage decision.

Although hospitals are sensitive to noise and are considered silent zones, many are located in urban areas and are subject to high levels of noise. In this study, an assessment of traffic noise, around a major hospital in the city of Doha, Qatar, was conducted during the morning and evening periods. The results indicated that the noise values exceeded the World Health Organization’s reference value of 50 dBA for both morning and evening times, and were higher than the 55 dBA limit at which serious annoyance is generated. Additionally, it exceeded the Qatar local standards for both daytime (55 dBA) and nighttime (45 dBA) noise levels. The results indicated that one of the main sources of noise was road traffic. Different solutions were proposed for a possible action plan to reduce the high level of noise.

Here, we aim to investigate the relationship between characteristics of railway stations and errors in train stop positions. Hence, two kinds of logistic regression analysis were conducted with two different objective variables: train stations with or without the occurrence of delays in braking manipulations and stations with or without the occurrence of misrecognition of stop positions. The explanatory variables included velocities near stations, braking manipulations, and features of the stations. Logistic regression analysis revealed that the delay in braking manipulations was significantly associated with the ratio of the maximum brake notch and the mean of velocities at 200 m before train stops. The delay in braking manipulations occurred frequently at stations where the train velocities when approaching the stations were high and the maximum brake notch was frequently used. Logistic regression analysis further revealed that the misrecognition of stop positions was significantly associated with the existence of a stop sign for four or six vehicles and where there were many stopping velocity patterns. A stop sign before a stop position and decreasing train velocity for a caution signal caused the misrecognition of stop positions.

Since the dawn of the new democracy in South Africa, practitioners, policy makers and stakeholders have been resolute on the need to confront spatial fragmentation in order to overcome the spatial inefficiencies that the spatial geography has imprinted on the transportation landscape in the country. Gauteng province is home to the full cycle of impacts and outcomes of apartheid driven spatial and transport inefficiencies. Urban spatial and transportation critics have suggested that adopting a smart transport planning system in the province is one way of seeking to reverse and correct the spatial and transport inefficiencies in Gauteng province. Making use of discourse analysis and systems innovation theory, smart transport and spatial fragmentation integration levers in Gauteng province are unraveled. Transport household databases of the 2003 and 2013 national surveys by the Department of Transport in South Africa as well as Statistics South Africa 2001, 2009, 2011, 2015, and 2018 census and community household surveys complement and provide an interpretative framework for situating spatial fragmentation and smart transport intersections including efficiencies and or inefficiencies in South Africa. To address spatial fragmentation, it is proposed that advanced spatial planning incorporating smart technologies be applied.

Shared bicycles have brought new challenges to the urban environment while facilitating the mobility of residents. The main manifestations are the chaos of urban management and the damage to the city’s landscape. The literature points out that governments, enterprises, and the urban environment should collaborate to help to improve the bike-sharing system from different aspects such as policy management, operation, maintenance, and public supervision. However, very few pieces of literature investigate the service from users’ perspective or what is the impact of the service on their lives. Combined with field surveys and literature studies, I randomly selected 10 users around the Siping campus of Tongji University for questionnaire interviews. The results show that people are satisfied with the bike-sharing service and its corresponding environment. The biggest pain points are inconsistency and unsafe while riding. The bike system and the urban environment match well in public spaces, but the residential areas and the working places need to be improved. Sharing bikes increase people’s willingness to travel within short distances and enhance social interaction. Last not least, bike-sharing users are more concerned with the urban environment and are more likely to accept the green traveling lifestyle. Finally, I proposed strategies and recommendations based on environmental policy, planning, design and education aiming to integrate users, service system and urban environments.

Object: To construct a set of comprehensive evaluation index system for wayfinding systems, and conducts trial evaluation using Beijing Metro Line 1 as an example. Methods: The research followed the principle of main factors, the principle of dynamics, and used the combination of quantitative and qualitative factors to select the evaluation indexes, which includes functional, normative, safety and coordination indexes. Field tests were performed on Beijing Subway Line 1 using evaluation indexes. Results: The overall renovation time in the stations has been half a century, mainly reflected in the absence of platform doors, the dim lighting inside the stations, and the insufficient installation conditions at key intersections. In addition, Line 1 passes through mature urban areas, where the business is prosperous, and the environmental information outside the stations often change. All these also make it difficult for maintain information connecting inter-stations and out surroundings.

Object: Based on the preliminary research results of the national standards for the evaluation indexes of railway passenger station wayfinding systems, Shandong Province was selected for field-test. The test process and results provided first-hand information for the improvement and optimization of national standards. It can also find problems in the wayfinding system of Shandong Railway Passenger Station and make suggestions for improvement. Methods: First, a questionnaire was prepared based on the preliminary evaluation indexes proposed in the national standard. Second, based on the sampling method in the National Standard, combined with the actual situation of the Shandong Railway Passenger Station, Qingdao Stations, Jinanxi Station, and Weifangbei Station were tested as sampling stations. Results: Among three railway stations tested in Shandong Province, Jinanxi Railway Station had lower scores in terms of basic specifications, safety, and coordination.

Object: The proposed evaluation indexes of the subway wayfinding systems was verified in Shandong Province. On the one hand, the evaluation indexes will be further revised and improved, and on the other hand, the subway wayfinding system in Shandong Province will be comprehensively evaluated to provide suggestions for further improvement. Method: Questionnaire and multi-level sampling method was used to sample Qingdao City. Results: The score of Line 3 is higher than that of Line 2 and Line 11. Using the Normative index score as the dependent variable and the subway line as the independent variable, a one-way analysis of variance was performed. It was found that there were no significant differences in the three subway lines in the Normative index. Line 2 and Line 3 have no significant difference in Normative index.

To improve the identification efficiency of safety signs in the subway, investigations on the safety signs of the subway were carried on. 158 participants were invited to participate the questionnaire test and the experiment to the redesigned safety signs. Tobii X2-30 was used to collect eye movement data and the area of interest (AOI). Wilcoxon rank sum test and Mann-Whitney U test were used to analyze the difference of the new safety signs and the original signs on the first saccade latency, the first fixation duration, and the total fixation duration in AOI. The results show that the value of P for four signs are less than 0.05. The analysis to eye movement are consistent with the selected subjects for the participants, which indicates that the new designed safety signs are better than the original. And the parameters that mentioned can be used for the test of signs.

The contemporary scenario sees the substantial affirmation of innovative technologies as digital tools necessary for the creation of an increasingly connected society. These technologies have a systemic relevance as they feed the value of the production system chain and have the ability to innovate processes, products and services in all economic sectors of human activity. The TIAMBIENTA project is focused on creating an ecosystem of home automation services through the use and integration of the new tools of digital technology for the design of the interior spaces of the motorhome. The project involves the construction of a cloud home automation sensor system. The sensor network will be interconnected through a control unit capable of collecting data, sending it to the central cloud platform and introducing direct implementation protocols on the internal environment control systems of the motorhome. Among the various enabling technologies that we have taken into consideration, a fundamental role has been given to ICTs, information and communication technologies, fundamental for collecting the data and recording and adjusting the user experience.

The rapid development of artificial intelligence, big data, and automation have the potential to transform the maritime industry. While change is inevitable, automated solutions do not guarantee navigational safety, efficiency or improved seaway traffic management. This paper describes lessons learned throughout the Sea Traffic Management (STM) Validation project. The STM project tested low-level automation functions intended to enhance navigational safety and efficiency. The results indicate that although the additional information was useful, there may be a disruption in current working practices, and potential gaps in the existing regulatory framework, and training and skill development of future mariners. The aim of this paper is to argue for a systems approach to better understand and prevent technologies from becoming “unruly” in the maritime context. This approach will consider how the technologies impact various system elements to support a more safe and sustainable shipping industry.

Artificial intelligence (AI) may be the panacea for improving safety and efficiency in shipping. Solutions to navigation problems are often challenged by information uncertainty, complexity and time demands. Tactical decisions to understand traffic patterns and future vessel encounters can be compared to a game of chess where an agent has goals and considers the next several moves in advance. AI approaches to machine learning is a reactive tactic but remains relatively ‘‘weak” and relies on computational power and smart algorithms to recreate each decision every time. Ships are required to follow the International Regulations for Preventing Collisions at Sea. While assumed to be the defining rules of the road, these may be ‘‘violated” to solve traffic situations in practice without creating increased risk to the situation. In order to create safe and reliable technologies to support autonomous shipping, the system cannot just rely on where it has to go but anticipate the goals of the surrounding vessels. This paper will explore the challenges, knowledge and technology gaps regarding AI in the shipping sector.

Modern technology revolutionised marine navigation, reducing errors and increasing navigation safety. However, the same technology has been associated with critical accidents and navigators’ errors. On the other hand, expert mariners have proved to manage complex situations, adapting to unforeseen events successfully. To better understand the effects of new technologies and how work is currently done, the Portuguese navy promoted a study about navigation team performance. The results suggest that navigation technology appears to have a strong anchoring effect on team activity. While sensemaking and intuitive judgements complement the shortfalls of the decision support system (DSS), it was found that the combination of high automation influence with lack of coordination leads to a collaborative biased perception of the situation.

In this validation exploration, we have studied a virtual reality ship command bridge against the standards and regulations that maritime training simulators must adhere to. We created a virtual reality replica of a command bridge with limited functionality that underwent user testing with 16 experienced ship officers. The results show that our training application did not meet all simulator criteria, but we point out that each of the shortcomings can be overcome with new generation hardware and expanded virtual reality programming. Our conclusion is that VR is a valid, affordable and efficient tool for command bridge simulator training.

Operators and regulators of offshore and maritime domains should adopt evidence-based safety training to prepare the workforce for emergency egress. This paper uses pedagogical frameworks and data mining tools to identify training gaps in mandatory offshore safety training, and offers evidence-based virtual environment (VE) training solutions. A VE training setting was used as a human behavior laboratory to provide trainees with artificial experience and record their learning progress in the context of evacuating a virtual offshore petroleum platform during a series of credible emergencies. A longitudinal study was conducted to collect data at three critical learning stages: skill acquisition, retention, and transfer. The empirical evidence identified strengths and deficiencies in the VE training. The modeling provided a more comprehensive assessment of the VE training and demonstrated the utility of data-mining tools for future adaptive training applications.

This study presents a survey that has been conducted as part of a larger research project focused on crew resource management in the maritime domain. As research focused on this type of training is currently limited, the Ship Management Attitude Questionnaire (SMAQ) developed by a Swedish marine insurance company, has been adopted to explore NTS knowledge of fourth year students in a maritime education program. Thirty-one students within the maritime academy’s Nautical Science (n = 21) and Marine Engineering (n = 10) programs participated in the survey. The age of the participants ranged between 22 and 46 years (M = 26.6, SD = 5.79). The results show that the questionnaire as is, is maladapted to explore NTS. It is also indicated that practices trained are not always encountered in the work onboard. The article concludes with a discussion on how to potentially improve the evaluation and assessment of NTS in maritime degree programs.

Many ship collisions and groundings occur due to navigators’ erroneous situation awareness (SA). The objective of this study is to develop a method to measure SA for maritime navigation and collision avoidance (SA-MA). This study uses the Situation Awareness Global Assessment Technique (SAGAT) as a basis and tool to assess SA. Both interviews with experts and simulator experiments are used. Ten participants, five navigators with extensive experience, and five second-year students at a nautical science program participate in the simulator experiment. Hierarchical Task Analysis (HTA) is used to map the navigation and collision avoidance tasks as input to the SA queries. The objective measurements collected from the simulator and subject matter experts are used for the SAGAT score. A well-developed SAGAT query and simulator experiment results in a difference in the SA-MA between the experienced navigators and the students with less experience. The study found it is difficult to measure SA-MA, especially for level 2 and 3 SA.

Studies on contemporary submarine control room configurations revealed a bottleneck of information transition. The co-location of operators dependent on each other for task-relevant information relieved this, however, the impact of operator co-location on subjective Situation Awareness (SA) was not assessed. In the current work, half of the teams from the baseline study and half of the teams from the co-location configuration were evaluated on two SA questions: (1) “Rate the awareness of the total number of vessels surrounding the submarine” and (2) “How many vessels did the entire command team encounter during the scenario?”. Participants completed high and low demand Return to Periscope Depth scenarios and responded to the SA questions immediately after finishing each scenario. Results indicate that operator SA decreased in the high demand scenarios regardless of control room configuration type. Furthermore, operator SA was greater in the co-location configuration than in the baseline study (contemporary configuration).

Modeling and simulation of a system, such as maritime traffic, with high complexity and a wide range of requirements including ships, navigators, control centers, shipping companies, meteorological systems, and geographic information systems requires human involvement. For maritime traffic simulation in a digital environment, modeling of human factors, a major element, is necessary, and for the reproduction and prediction of realistic maritime traffic situations, it is reasonable to model and reflect the navigator’s cognitive processes, behavior patterns, navigational expertise, navigational errors, etc. To develop an intelligent ship agent for maritime traffic analysis, we will analyze the navigator’s ship navigation-related cognition and behavior, and introduce the status of the development of an agent-based cognitive and behavioral model as similar to the navigator’s behavior.

Conformal 3D symbology presented on a head tracked head-mounted display (HMD) has the capability to enhanced pilot situation awareness, performance and workload by providing an unlimited field of view of operational hazards. In recent years, a body of research has emerged highlighting the technical advancements (i.e. HMD encumbrance and optical enhancements) that could enable the unique capabilities and benefits of HMDs to be realized on commercial and business flight decks in the near future. The current paper provides a systematic review of the HMD-related pilot benefits (performance, workload, situational awareness, and usability) that have been reported in the literature. We conclude by highlighting the operational contexts where HMDs might enhance pilot performance, flight safety and efficiencies.

Future deep space missions will present new physical and cognitive challenges that could increase risks to astronaut performance. In addition, crews may no longer be able to depend on timely support from NASA Mission Control Center (MCC) due to distance from the Earth. Astronauts will have to work autonomously using onboard resources, while still maintaining high performance. It is critical to understand the type of support MCC currently provides in order to replicate that type of support onboard. A Contextual Inquiry was performed to characterize the support that MCC currently offers to space crews. An expert Focus Group was convened to understand the types of tasks astronauts will do on a future Mars mission, as well as the challenges associated with those tasks. Results from these activities elucidate the types of intelligent tools and capabilities that will be needed for autonomous crews on future deep space missions.

Various stressors such as microgravity, vibration, radiation, restriction, and isolation in manned spaceflight environments can cause a variety of negative psycho-physiological effects. At the emotional level, for example, they may provoke anxiety and depression, which affects the astronauts’ operational efficiency and overall mission performance. The colour design of a spaceflight environment could positively affect a person’s emotional level and thus help to counteract such negative psycho-physiological effects. This paper presents a new model for validating the colour design of spaceflight environments at the psycho-physiological and emotional level in order to increase the quality of emotional habitability and support efficiency and performance. Psycho-physiological experiments were tested on six coloured light in a dedicate physical mockup of a specific spaceflight environment. In particular the sanitary area of the space station was used as a case study. As result the highest quality of emotional habitability was achieved in a yellow coloured light environment, that is very close to the natural solar condition. Note: In order to support the confidentiality in this paper is not mentioned the name of the space station.

This paper addresses design requirements for a what-if tool for airport management. First it provides an overview of the challenges in airport management and the need for a what-if tool. Following this motivation, theoretical and existing solutions of what-if systems are presented to conclude on an approach for a what-if system design specifically for the Total Airport Management (TAM) concept. TAM requires the cooperation of relevant stakeholders at an airport working towards different company specific goals yet trying to optimize overall airport operations. As the interactions between the various processes are highly complex the effects of an individual action on overall operations are not easily understood. Hence there is a need for a process to predict the overall effects of any action and to allow a comparison between several options. This will be provided by a what-if analysis tool, which provides a major component of a cooperative decision support system.

An online questionnaire about assistance systems in helicopters was answered by 153 professional pilots from all areas of civil and military aviation. The results indicate that pilots generally appreciate the systems provided in their helicopters but see potential for improvement in the usability. One notable fact is the high proportion of visual display concepts. The human auditory channel is supported by the systems to a comparatively small extent. Pilots would like more possibilities to directly influence the systems. The multimodal approach is considered promising for the future. The results suggest that assistance systems and their forms of display to the pilots must be designed differently depending on the current flight phase.

We studied how pilots handle operational variations during arrival and approach instrument flight procedures (IFPs), focusing on factors that may be related to performance-based navigation (PBN). PBN is a key enabler of the Next Generation Air Transportation System (NextGen). We developed a factor rubric based on an iterative review of events in the Aviation Safety Reporting System (ASRS) public database and prior research. We coded 164 ASRS reports selected for relevance to PBN. We identified where each event occurred relative to the route of flight, tallied the coded factors and event outcomes, and gathered data on crew actions that indicated resilience to operational variations such as unexpected behavior of aircraft automated systems. We conclude that PBN appears to magnify the effects of operational complexity for these events. Pilots would benefit from training that provides opportunities to experiment with new situations they could encounter in PBN scenarios.

Air transport is now so common that airlines carried 4.3 billion passengers in 2018 [1]. Most passengers travel safely. However, the air transport system is complex and as a result accidents continue to happen. Some accidents involve communication breakdowns between pilots and air traffic control (ATC). The aim of this project is to construct a glossary of factors that may lead to pilot-ATC communication breakdowns. The glossary is based on information collected from: (1) a review of literature in various research fields, and (2) interviews with pilots at two major airlines in Europe and the Middle East. The project is ongoing. This paper describes the methodology and preliminary results from the pilot interviews. It also includes a list of 68 communication factors as well as one sample glossary entry. The glossary will contribute to aviation safety by raising awareness of communication factors that cause accidents.

The integration of crew resource management into the product design process for aerospace systems is discussed. Human-centered design methods - which can include human in the loop simulations, rapid prototyping, problem definition, evaluations, and verifications - often rely on operational knowledge of expert users to address human-systems integration needs. Modern integration efforts attempt to reduce the divide between user intentions and system state allowing for a safer system operation. However, in a multi-crew environment, crew interactions ought to be heavily taken into consideration. For this reason, crew resource management is recommended as a training supplement to both aerospace designers/researchers and expert users.

To support the Revolutionary Vertical Lift Technology project’s goal of addressing source noise and response for vertical takeoff and landing aircraft, the authors have developed a noise training aid. This training aid depicts the predicted ground noise footprint using a noise algorithm and a flight simulator. This paper describes the implementation of the noise training aid, feedback from potential users on improvements, and future plans that will eventually provide an inflight noise display.

Offshore helicopters play a vital role in energy production worldwide and must be operated safely. Safety is underpinned by hazard identification, which aspires to be predictive and remain operationally relevant. A process to elicit pilots’ operational hazard knowledge in a predictive manner is currently absent. This paper redresses this by developing a Task-Based Hazard Identification Survey Process which, through Talk-Through interviewing, collects data from a statistically representative sample of pilots based in specified regions. A factual and exhaustive hazards’ template is formed, to which various statistical methods are applied. Subjected to multiple validation and reliability checks, the process delivers on the aspiration to be predictive on safety.

The commercial air travel industry has incentivized strategies that maximize the number of bodies that can fit into the cabin. This demand for increased capacity in a limited space has led to economy class cabins becoming increasingly cramped. This lack of space particularly impacts travelers who are living with obesity. To develop an understanding of this issue, we evaluated the current space within the cabin and compared it to anthropometric data of both the general population and a cohort of people living with obesity. The lack of accommodation for those living with obesity may have severe impacts on the health and safety of all passengers. Upon review of the data, it is clear that there remains more work to be done to address the accommodation of passengers that better reflect the anthropometry of the flying public. Identifying a solution that balances economics with passenger health, safety, and comfort will require a collaborative effort between carriers, manufacturers, regulators, and passengers.

NASA’s Urban Air Mobility (UAM) Sub-Project is engaged in research to facilitate the introduction of air taxis into the US National Airspace System. Given the history of conventional aircraft operations, it is clear that dispatcher support will be required for UAM. This paper presents a gap analysis, system requirements, and a workstation design concept for the UAM dispatcher or Fleet Manager (FM) position. The gap analysis focuses on the differences between the tasks of the airline dispatcher and those projected for the FM. FM system capabilities and data requirements are then presented as foundations for software development. An initial user interface concept is provided. The FM software uses a single, large display. The system supports prediction, monitoring, and task execution. This paper is intended to support FM software design for future air taxi systems.

According to the statistics, emergency landing and evacuating case of commercial aircraft usually causes serious accidents, this paper investigates the definition, the airworthiness regulations of commercial aircraft emergency landing, analyzes the impact on passenger evacuating, when the structure and system around cargo are damaged, due to luggage dash during the emergency landing. This paper also introduces methods of avoiding the impact of luggage’s dash on passenger evacuating during emergency landing.

In order to clear the factors and degree that affect the comfort experience of the aircraft cabin, and to make a reasonable strategy for improving the comfort of the aircraft cabin, the comprehensive evaluation system of the comfort in aircraft cabin is studied. An indicators system, weight system, and evaluation method for cabin comfort evaluation are proposed, and the comfort of aircraft cabins is evaluated from four aspects: the indicators of criterion layer, the indicators of attribute layer, the factors of factor layer, and the overall comfort of cabin. Based on the evaluation system, the cabin comfort of a flight was investigated, and 206 valid questionnaires were obtained. Statistical analysis of the data found that the factors and indictors influencing comfort. The comprehensive evaluation system of comfort experience in civil aircraft cabin provides quantitative reference for the selection and optimization of cabin scheme, and provides direction for the improvement of aircraft cabin comfort in future design.

The fast-paced advancement of ground transportation methods such as connected and autonomous vehicles makes it difficult for professionals to design infrastructure, which includes airports. Due to the amplified variability in both transportation modes and demographics, planners must consider the best alternative, which will service all of their users while integrating an autonomous system. This paper describes mobility activities at the interface between ground transportation and airport terminal, characteristics of automation in airport access, and planning and design requirements with a focus on human factors. Knowledge gaps are identified. A human factors study is introduced for understanding characteristics and behaviour of users of landside facility. This paper aims to assist planners and designers in considering human factors when planning for autonomous systems in airport terminals; specifically focusing on pick up and drop off zones.

The development of cockpit flight scenarios is an important precondition for cockpit design and crew workload analysis. Aiming at the complex dynamic relationship between crew, aircraft, and environment, this paper proposes three dimensions of cockpit flight scenarios. Based on the engineering practice, a cockpit flight scenario matching method is proposed to simplify the scenario development work while ensuring the integrity of the scenario. This paper provides recommendations for flight scenario development in the cockpit development process.

Stall is one of abnormal events in flight which can cause fatal accident if the pilot cannot overcome the critical situation. This research examines the effect of pilot anticipatory condition towards pilot performance when encountering a stall and several other human factor conditions such as stress and sleep duration of previous night. A total of 18 respondents were divided into two groups namely surprised and anticipated against stall scenario. The respondents have passed the stress level test before it was continued with a flight simulation which included a stall scenario in it. Based on the results of the research, surprised and anticipated conditions as well as sleep duration of the pilot affect pilot performance in encountering stall. Pilots who have anticipated stall have a greater chance to have better performance. In addition, pilots with more than six h sleep duration also tend to have better performance in encountering stall.

Based on ICAO recommendations and statistics on aviation events and incidents during air traffic control, a spectrum of characteristic errors of n = 21 air traffic controllers was generated, which most fully and comprehensively illustrates their erroneous decisions. To establish the coefficients, a mathematical method of ranking priorities was applied. To summarize the views of m = 37 professional air traffic controllers involved in the experiment, regarding the frequency and hazards of errors identified in the ICAO scale, a multiplicative approach was implemented. It has been founded that the error’ rate indistinguishability indicator in a group system of preferences is equal $$ R_{LF}^{*} = 1,23 \cdot 10^{ - 2} $$ , and the error’ danger indistinguishability indicator is three times worse and equal $$ R_{LD}^{*} = 3,77 \cdot 10^{ - 2} $$ . Integrative (holistic) indicator of each error’ significance summarizes its significance coefficients in terms of frequency and hazards and is multiplicative. That allowed building the final group system of preferences. The degree of indistinguishability of the errors significance is equal $$ R_{g}^{*} = 0,91 \cdot 10^{ - 2} $$ , which testifies to the effectiveness of the proposed approach to the implementation of ICAO recommendations regarding the frequency and the dangers of unwanted events in flight safety management.

High-level human factor engineering principles, which could be used to develop many detailed review guidelines in the design and evaluation of Civil Aircraft Flight Deck Human-Machine Interface, have been introduced in this paper. These principles only address the human factor engineering aspects of the Flight Deck design, but no other related considerations, such as instrumentation, control or structural design. The human factor engineering review principles are organized into four categories: general principles, awareness principles, workload principles and error management principles.