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Lane-changing trajectory planning (LTP) is an effective concept to control automated vehicles (AVs) in mixed traffic, which can reduce traffic conflicts and improve overall traffic efficiency. To enhance the lane change safety for AVs, a co-evolutionary lane-changing trajectory planning (CLTP) method is proposed to describe the risk minimization process that co-evolves with the dynamic traffic environment in the limited literature. Firstly, the natural driving data of vehicle trajectory on the expressway provided by the High dataset are used to construct the lane-changing samples. To obtain the future traffic environment information, a deep learning neural network is adopted to capture trajectory dynamics in mobility of surrounding vehicles around a lane-changing vehicle. Secondly, the safe interaction between the subject vehicle and the surrounding vehicles is considered to establish a mathematical model for the temporal and spatial risk identification of a lane change event based on the fault tree analysis method. Subsequently, the risk minimization of lane change is considered as the objective. Based on the acceleration and deceleration overtaking rules and the trapezoidal acceleration method, the longitudinal and lateral displacement schemes during a lane change are designed. Finally, the motion parameters of longitudinal and lateral displacement are acquired to form an ideal lane change trajectory using a genetic algorithm. The results show that this method can effectively achieve higher safety of the lane-changing process, and reduce the traffic conflicts and traffic turbulence caused by dangerous lane-changing behaviors. The findings can provide theoretical support for lane change trajectory planning algorithm design of intelligent vehicles., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Lateral driving behavior analysis is the foundation of freeway cross-section design and the focus of road safety research. However, the factors that influence vehicle lateral driving behavior have not been clearly explained. The dataset of the natural driving trajectory of freeways is used in this study to analyze vehicle lateral driving behavior and trajectory characteristics. As vehicle trajectory characteristic indicators, parameters such as preferred trajectory deviation and standard deviation are extracted. The effects of lane position, speed, road safety facilities, and vehicle types on freeway trajectory behavior are investigated. The results show that lane width and lane position significantly impact vehicle trajectory distribution. As driving speed increases, the lateral distance between vehicles in the inner lane and the guardrail tends to increase. In contrast, vehicles in the outside lane will stay away from the road edge line, and vehicles in the middle lane will stay away from the right lane dividing line when the speed increases. Statistical analysis shows that the preferred trajectory distribution of the same vehicle type in different lane positions is significantly different among groups (Cohen's d > 0.7). In the same lane, the lateral position characteristics of the center of mass of different vehicle types are basically the same (Cohen's d < 0.35). This work aims to explain what variables cause trajectory deviation behaviors and how to design traffic safety facilities (guardrail and shoulder) and lane width to accommodate various vehicle types and design speeds.

The printed circuit board (PCB) is the core control unit of electromechanical equipment. In order to determine the influence of the coupling vibration caused by vehicle-road interaction on the PCB reliability of roadside electromechanical equipment, first, the dynamic load of the vehicle tire is solved by establishing the dynamic model of a vehicle road. Then, the acceleration response data generated by road vibration are obtained by solving the road finite element model. Finally, the power density spectrum of the acceleration response is taken as input excitation, and the deformation response of the PCB under vehicle-road coupling vibration is analyzed. The experimental results show that when the vehicle is driving close to the roadside, the vibration caused by vehicle-road coupling will lead to a large deformation of the PCB, and the deformation value reaches 0.170 mm, which can cause structural damage to the PCB. This shows that the vehicle-road coupling vibration can affect the reliability of the roadside electromechanical equipment; thus, the optimal design of the PCB layout is created. After optimization, the first-order modal frequency of the PCB is increase by 5.4%, which reduces the risk of the components breaking away from the PCB substrate.

Road traffic safety can be ensured by preventing and controlling the potential risks in road traffic operations. The relevant literature was systematically reviewed to identify the research context and status quo in the road traffic operation risk prevention and control field and identify the key study contents needing further research. As research material, the related English and Chinese literature published between 1996 and 2021 (as of 31st December 2021) was obtained through the Web of Science Core Collection and Chinese Science Citation Database. These research materials include 22,403 English and 7876 Chinese papers. Based on the bibliometrics, this study used CiteSpace software to conduct keyword co-occurrence analysis in the field. The results show that the relevant research topics mainly covered the risks of drivers, vehicles, roads, and the traffic environment. In the aspect of driver risks, the studies focused on driving behavior characteristics. In terms of vehicle risks, the related studies were mainly about the vehicle control system, driving assistance system, hazardous material transportation, automated driving technology, safe driving speed, and vehicle collision prediction. For the road risks, the safe driving guarantee of high-risk road sections, driving risks at intersections, and safe road alignment design were the three study hotspots. In terms of traffic environment risks, identifying traffic risk locations and driving safety guarantees under adverse weather conditions were the two main research highlights. Moreover, mathematical modeling was the main method for studying road traffic operation risk. Furthermore, the impact of environmental factors on drivers, the emergency rescue system for road traffic accidents, the connection between automated driving technology and safe driving theory, and the man-machine hybrid traffic flow characteristics are the subjects needing further research.

The risky lane-changing manoeuvre of vehicles often occurs at expressway entrances, which would result in a high crash risk in the freeway system and significantly impact its safety. The highly anticipated environment of connected and autonomous vehicles (CAVs) is expected to reduce the associated crash risk of lane changing by offering various types of driving support, which utilise surrounding traffic information. The modelling crash risk under the environment of CAV driving during mandatory lane changing in merging areas faces new challenges due to the novelty of CAVs and subsequent shortage of data. To explore such risk situation of multi-vehicle interaction at expressway entrances, this study proposed a supervised learning algorithm and a Bayesian hierarchical model to assess risk levels and predict the probability of risk occurrence at different risk levels of interactive vehicles in real time of mandatory driving behaviour during the merging process. The learning algorithm, based on XGBoost, was exploited to classify risk levels. The Bayesian hierarchical model was used to analyse the probability of real-time risk comprising vehicle physical state layer, multi-vehicle interaction layer and risk probability layer. The probabilistic model parameters were calibrated using Markov Chain Monte Carlo (MCMC) Gibbs sampling method. The K-fold cross validation method was used to validate the proposed model of risk level. The probabilistic model validity was tested through posterior prediction of P-value. The quantitative risk estimation of CAVs through a few merging cases was conducted. Results show that the identification accuracy of slight, low, moderate and high risk is 94.24%, 85.82%, 84.16% and 79.69%, respectively. The P-value of Durbin-Watson's posterior, normal hypothesis, test distribution symmetry and kurtosis are all close to 0.5. Therefore, the method of real-time risk assessment is convergent and has good fitting. This research can promote cautious driving behaviours and provide reference for driver's decision making in the long term under the environment of CAVs., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

To determine a reasonable speed limit and ensure traffic safety in a dynamic low-visibility environment with fog, a driving simulator study was conducted. A total of 31 young participants were recruited, and each completed 5 driving simulator trials under varying visibility conditions and speed levels during the daytime. The combined coupling effect of the visibility and driving speed on drivers' recognition times was explored, and a quantitative model of the recognition time, visibility, and driving speed was established. A determination method and suggested value of a reasonable driving speed limit in dynamic low-visibility conditions were proposed based on the stopping sight distance model. The results show that there are significant differences in the recognition times of drivers under different visibility and speed conditions. The reasonable driving speed limit values in dynamic low-visibility conditions should be based on visibility changes. When the stopping sight distance is 75 m and the visibility is less than 35 m, the speed limit should be 20 km/h. When the visibility is between 35 m and 60 m, the speed limit should be 30 km/h. When the visibility is between 60 m and 140 m, the speed limit should be 50 km/h. When the visibility is greater than 140 m, the speed limit should be 60 km/h. These research results can provide a theoretical reference for the formulation of a VSL in a dynamic low-visibility environment related to fog and reduce crash risk in conditions of inadequate visibility in fog., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Objective: As the number of tunnels and traffic accidents increase, it is necessary to study the drivers' visual characteristic in the tunnels. Considering that freeway tunnels have limited space and narrow sight zone, drivers usually have a short visual blind zone and visual shock when entering and exiting the tunnels. This study aims to investigate the characteristics of drivers' visual load in the entrance and exit zones of extra-long tunnels, and to provide a theoretical basis for the traffic safety prevention and control measures of the engineering design., Methods: 20 drivers were enrolled to conduct real vehicle tests in the Guizhou Sifangdong Tunnel at different time periods (daytime, twilight, and nighttime). The drivers' pupil area was collected by an eye tracker. The maximum transient vibration value (MTVV) of the pupil area was selected as the index of visual load. In addition, the changing characteristics of visual load in the entrance and exit zones were examined. Using ANOVA, the significant difference of visual load in different zones and at different time periods were performed. Accordingly, the overall drivers' visual load in the entrance and the exit zones were compared. Exponential function models of the MTVV value and the speed of pupil area change were constructed, where the pattern of mutual influence was examined., Results: The changing pattern of the drivers' visual load at different time periods in the entrance and exit zones were markedly different. The comparison of the overall visual load was as follows: exit zones at nighttime > entrance zones at nighttime > entrance zones at twilight > exit zones at twilight ≈ entrance zones at daytime ≈ exit zones at daytime. Moreover, the MTVV value positively correlated with the speed of the pupil area change. Finally, this study proposes an evaluation standard of visual comfort based on the speed of the pupil area change., Conclusion: This study highlights the driving risk in extra-long tunnel. These findings could provide a basis for studying the setting method of visual guidance facilities in entrance and exit zones of extra-long tunnel. Also, this study could provide a theoretical basis for the evaluation of drivers' visual load in the tunnel.

Statistical data shows that single-vehicle crashes account for half of all traffic crashes on expressways in China, and previous research has indicated that main contributing factors were related to whether and how the inside shoulder was paved. The inside shoulder provides space for drivers to make evasive maneuvers and accommodate driver errors. However, lower-cost construction solutions in China have resulted in the design of numerous urban expressway segments that lack inside shoulders. This paper has two objectives. The first is to reveal the safety impacts of inside shoulders on urban expressways by driving simulator experiment. The second objective is to propose optimal range and recommended value of inside shoulder width for designing inside shoulders of urban expressways. The empirical data, including subjects' eye movement data, heart rate (HR) and the lateral position of vehicles, were collected in a driving simulator. The data were analyzed to evaluate the safety impacts of the inside shoulder. The results have revealed that the inside shoulder has an impact on drivers' visual perception, behaviors, and psychology; in particular, it has a significant effect on vehicle operations. In addition, this paper recommends the desired and optimal inside shoulder widths for eight-lane, two-way divided expressways., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

In order to fully understand the research progress of human factors and traffic safety in curve driving, from the perspective of driver-vehicle-road-environment dynamic traffic system, this paper explored the current research status and development trend of human factors of curve driving, and displayed the development process and structural relationship of human factors research of curve driving by using scientific knowledge map. Through the core collection database of Web of Science, 1408 English literatures related to human factors research of curve driving published from 2012 to 2022 (as of October 1, 2022) were obtained, and the literatures in this field were sorted and analyzed based on the VOSviewer visualization software. The results show that China, Tongji University and Accident Analysis and Prevention are the country, institution and journal with the largest contribution rate in the field of human factors research on curve driving. Co-citation analysis shows that the research contents in this field are divided into 5 clusters: driver's visual characteristics, risk of collision, vehicle dynamics characteristics, the influence of traffic engineering facilities on driving behavior, selection of driving speed. The co-occurrence analysis of keywords shows that the topics of curve geometry design and vehicle dynamics, driving behavior and risk, driving speed and safety, behavior prediction and intervention measures are the current research hotspots in the research field. It is found that the development trend of traffic safety improvement in curves is to construct a continuous, consistent, multi-level visual reference frame conforming to driving expectation through visual guiding technology, and summarizes the technical concept of linear visual guidance. This study can provide a reference for the study of human factors of curve driving. [ABSTRACT FROM AUTHOR]

This paper discusses low-cost approaches capable of ranking traffic intersections for the purpose of signal re-timing. We extracted intersections that are comprised of multiple roads, defined by alphanumeric traffic message channel segment codes per international classification standards. Each of these road segments includes a variety of metrics, including congestion, planning time index, and bottleneck ranking information provided by the Regional Integrated Transportation Information System. Our first approach was to use a ranking formula to calculate intersection rankings using a score between 0 and 10 by considering data for different times of the day and different days of the week, weighting weekdays more heavily than weekends and morning and evening commute times more heavily than other times of day. The second method was to utilize unsupervised machine learning algorithms, primarily k-means clustering, to accomplish the intersection ranking task. We first approach this by checking the performance of basic k-means clustering on our data set. We then explore the ranking problem further by utilizing data provided by traffic professionals in the state of Tennessee. This exploration involves using MATLAB to minimize the mean-squared error of intersection rankings to determine the optimum weights in the ranking formula based on a city's professional data. We then attempted an optimization of our weights via a brute-force search approach to minimize the distance from ranking formula results to the clustering results. All the ranking information was aggregated into an online SQL database hosted by Amazon web services that utilized the PHP scripting language. [ABSTRACT FROM AUTHOR]

A review of 115 studies on Australian local area traffic management (LATM) schemes covers network planning, computer modelling, overall design considerations, the deployment of various traffic control devices, project evaluation and numerous before and after case studies. However, no research has been published about the formulation of LATM policies and the processes involved that were formulated during the 1970s and 1980s and aimed at discouraging non-local through traffic in residential areas, improving road safety, and improving environmental amenity through physical devices. This paper develops a conceptual model of the interactions amongst institutions of government (state and local), organisations (national research institutes and universities), and civil society (the consulting industry, lobby groups and community action groups). The model is implemented through a series of unstructured interviews with key players involved with research and advocacy, capacity building, and state government policy makers that determined: who was responsible for the governance of LATM schemes? What were the respective roles of institutions and organisations in relation to the early formulation of policies and plans, especially issues of authority? Who were the key players in these institutions and organisations? To what extent did external influences of ideas by overseas agents (policy transfer) occur in decision making? A recently implemented LATM scheme (Seven Ways) by Waverley Council describes the latest approaches, including community participation. The conclusions note the importance of a society investing in road research, having universities capable of delivering high-quality professional development programs, and having a consulting industry that is willing to deliver innovative, practical advice to local governments. Suggestions are made about areas for further research [ABSTRACT FROM AUTHOR]

To better understand the research focus and development direction in the field of driving behavior active intervention, thereby laying a scientific foundation for further research, we used the combination of topic words and keywords to retrieve relevant articles from the Core Collection Database of Web of Science (WOS). A total of 578 articles published from 1992 to 2022 were finally obtained. Firstly, the time distribution characteristics, country distribution, institution distribution and main source journal distribution of published articles were explored. Then, by using the CiteSpace and VOSviewer software, cited reference co-citation analysis, keyword co-occurrence analysis and burst detection analysis were carried out respectively to visually explore the knowledge base, research topic, research frontier and development trend of this field. The results indicate that the USA, Australia and China are the three most active countries in the studies of driving behavior active intervention. Accidental Analysis & Prevention, Transportation Research Part F: Traffic Psychology and Behavior, and Journal of Safety Research are widely selected journals for publications related to this field. The research frontiers in the field of driving behavior active intervention focus on: “traffic safety and crashes analysis, as well as enforcement intervention”, “driving risk and education for young drivers”, “information provision and driving behavior”, “workload and situation awareness for automated driving”. It is worth noting that in recent years, “warning system”, “time”, “work load” have become research hotspots in this field. To sum up, by a bibliometric overview of research on driving behavior active intervention over the past thirty years, this paper clarifies the development skeleton of this research field, determines its hot topics and research progress, and provides a reference for the follow-up exploratory scientific research in this field. [ABSTRACT FROM AUTHOR]

Road traffic injuries and crashes are one of the major public concerns contributing to mortality and morbidity figures across the globe. Researchers estimated that around 90% of all causative factors for crashes are attributed to road users of which drivers are the principal controlling elements. Therefore, understanding complex human driver behavior and their possible violations or errors are necessary to control and prevent accident occurrence to a considerable extent. Studies on driver behavior of commercial vehicles such as trucks are scattered widely and scarcely explored hindering the possibility of road safety outcomes. This underscores the need to excavate and synthesize the past studies for an effective understanding of human factors causing truck crashes. In this paper, an attempt has been made to systematically review the pieces of literature and to identify the causative factors affecting truck driver behavior. The trend of studies shows a promising framework for improving truck driver safety on taking care of human factors influencing crashes. Most kinds of literature have cited unsafe driving behaviors as a predominant source of truck crashes. The outcomes of this research can be utilized by transportation firms and stakeholders for identifying the possible lags to develop pragmatic and possible effective preventive measures featuring truck driver safety. [ABSTRACT FROM AUTHOR]

Road traffic safety should be evaluated throughout the entire life-cycle of road design, operation, maintenance, and expansion construction. However, traditional methods for evaluating road traffic safety based on traffic accidents and conflict technology are limited by their inability to account for the complex environmental factors involved. To address this issue, a new road safety evaluation method has emerged that is based on driving behavior. Because drivers' behaviors may vary depending on the driving environment and their personal characteristics, evaluating road safety from the perspective of driver behavior has become a popular research topic. This paper analyzes current research trends and mainstream journals in the field of road safety evaluation of driving behavior. Additionally, it reviews the three most commonly used driving behavior data collection methods, and compares the advantages and disadvantages of each. The paper proposes the main application scenarios of road safety evaluation methods based on driving behavior, such as road design, evaluation of the effects of road appurtenances, and intelligent highways. Furthermore, the paper summarizes a driving behavior index system based on vehicle data, driver's physiological and psychological data, and driver's subjective questionnaire data. A comprehensive evaluation method based on the fusion of each index system is presented in detail. Finally, the paper points out current research problems and the future development direction of the road safety evaluation method based on driving behavior. [ABSTRACT FROM AUTHOR]

Sitting in traffic congestion for hours in a posture that requires recurrent actions of manually pressing the pedal and braking excessively can result in fatigue, especially on the driver's leg and back. This fatigue can have long-term implications and adversely affect the driver's health. Thus, this paper aims to model and develop a control system that utilizes a linear actuator to replace the leg activities involved in pressing and releasing the brake pedal. This approach, combined with the implementation of a PID controller, offers a novel solution to control the vehicle speed by integration with the linear actuator that focus on low-speed driving condition. The design process begins with creating a 3D model using SolidWorks to visualize the movement of the linear actuator and Pedal subsystem. This model is then connected to Matlab-Simulink, where a PID controller is implemented and integrated into the electrical circuit to control the actuator's movement. Integration with the vehicle dynamic model enables a comprehensive analysis of the system's behavior on the vehicle dynamics. This research compares the trial and error method with the Matlab tuner for implementing the PID controller. The performance of the system will be evaluated based on the steady state error, overshoot, rise time, and settling time. The results demonstrate that the Matlab tuner outperforms trial and error method by achieving a faster response and significantly reducing steady state error during robustness testing. With the integration of the linear actuator, the system is capable of tracking the desired speed and has the potential to replace the leg activities involved in pressing and releasing the brake pedal. For future work, validating the proposed mechanism with a physical prototype of the linear actuator and pedal using hardware-in-the-loop techniques poses a challenge, as hardware constraints may vary with different environments. [ABSTRACT FROM AUTHOR]

Although the existing Driver Behavior Questionnaire (DBQ) covers a wide range of drivers' aberrant behaviors, advances in technology have made some questions out of date. These advancements could lead to human errors while driving, and therefore some items of DBQ need to be updated to reflect the influence of technology on driving behavior such as mobile phone usage while driving. This study aims to modify the widely used DBQ by including "mobile phone usage while driving" items and validate it in Iranian context. The impact of demographic items on each factor scale is also investigated. A shortened DBQ that include drivers' aberrant behaviors and additional questions on mobile phone usage while driving was developed. A total of 298 drivers (168 males and 130 females) between the ages of 18 and 60 participated in this study. Results showed that the mean score of two mobile phone usage items is significantly correlated with violation behaviors. Besides, younger drivers, male drivers, and drivers who were involved in an accident in the past three years behave more aberrant. Statistical analysis shows that drivers who use their mobile phones while driving are more likely to be involved in a traffic crash. Moreover, mobile phone usage while driving decreases significantly by age and males use their mobile phones more than females while driving. [ABSTRACT FROM AUTHOR]

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Objectives: Florida ranks among the states with the highest rates of work-zone crashes involving large trucks. With significant emphasis in Florida's strategic highway safety plan, understanding work-zone crashes involving large trucks and resulting injury severities is critically important. This study investigated the contributing factors influencing the driver injury severity of single-large-truck crashes in work zones, benchmarked against non-work zones in Florida.Methods: Using work-zone and non-work-zone crash data from 2011 to 2019 (inclusive), driver-injury severities in single-large trucks crashes were studied using random parameters logit models that allow for possible heterogeneity in the means and variances of parameter estimates. The available data included a wide variety of factors known to influence driver injury severity, including spatial and temporal; vehicle and traffic; roadway, harmful events, and driver characteristics.Results: The model estimates produced fundamental shift in unobserved heterogeneity for work-zone and non-work-zone crashes involving single large trucks. More importantly, the likelihood of large truck drivers' injury severity is about fourteen-times higher on rural and six-times higher on urban interstate highways and 1.3 times lower with 10 miles per hour below the posted speed limit for large trucks inside work zones relative to non-work zones. The model results also indicate that the likelihood of severe driver injury is higher for heavy truck (more than 26000 pounds), a lane-shift work-zone configuration, and careless driving in work-zone crashes involving single large trucks.Conclusions: The model findings add valuable insights to have profound effects in the safety performance of large trucks and in-vehicle safety technologies, such as, Advanced Driver Assistance Systems, for careful driving along the work-zone segments with lower speed, leading to Automated Driving Systems. These measures include various policy-related safety countermeasures including revisiting traffic control plan for lane-shift on highways specifically for large trucks and developing training modules for Florida registered truck drivers. [ABSTRACT FROM AUTHOR]

Objective: As novice teen drivers are uniquely susceptible to the harmful effects of secondary activities on cellphones, 38 states and Washington D.C. have banned all types of cellphone usage for drivers younger than 18 years or in the learner/intermediate phase of driving. Despite the prevalence of such cellphone prohibitions, several surveillance studies have highlighted the persistent engagement of teenagers in cellphone-distracted driving, which increases the related crash risk. Most of the prior studies broadly consider cellphone usage as a general distraction instead of investigating different distraction-related tasks associated with cellphone use. This study analyzed the cellphone crashes of novice teenagers (aged 15-17 years) to discover the grouping of contributing factors by crash severity levels and cellphone usage types.Methods: The current study collected five years (2015-2019) of related crash data from the Louisiana Department of Transportation and Development. A manual effort was carried out to recognize the type of cellphone tasks before collision by reading the narratives of police-investigated crash reports. Association rule mining was applied to explore the associations between numerous crash attributes in multiple circumstances without relying on any predetermined hypotheses.Results: The cumulative effect of cellphone distraction and no seatbelt usage is frequently visible in confirmed injury crash scenarios. Cellphone crashes of novice teenagers at intersections are strongly associated with talking/listening rather than texting/browsing/dialing and reaching for/answering/locating. The associations among environmental factors and modes of cellphone usage significantly influence the manner of collisions. Single-vehicle crashes are associated with cellphone manipulation while driving on weekends in cloudy weather, whereas sideswipe collisions are frequent in evening hours during reaching for/answering/locating the cellphones. In relation to texting/browsing/dialing, novice teenagers operating vans/SUVs are strongly associated with traffic control violations.Conclusions: The findings are expected to be beneficial for policymakers and other safety officials to develop strategic planning and implementable countermeasures when dealing with cellphone-distracted novice teenagers. The association of factors identified from the analysis exhibits real-world crash scenarios critical to strengthening driver education programs to mitigate teen driver crashes. Moreover, cellphone crashes and related casualties can be reduced by eliminating or improving one of the attributes involved in the crash patterns. [ABSTRACT FROM AUTHOR]

Vehicular driver behaviour is an important factor for vehicular speed and safety at horizontal curves, few studies have attempted to understand this aspect. In this regard, the objective of the present study is to evaluate the vehicular speed characteristics with the effect of driver behaviour at horizontal curves. The study uses real traffic environments where vehicle speed, driver behaviour (lane change or not) and number of vehicles in the opposite lane (approaching vehicles in the opposite lane) data were recorded by video graphic technique. A total of four horizontal curves with different radiuses on two-lane undivided two-way roadways have been studied. Further, the curve characteristics (radius, length of curve, etc.) data were collected from a preliminary survey. The data was analyzed with a multiple linear regression model by considering vehicle speed as the dependent variable and radius of curve, driver lane change behaviour, number of vehicles in the opposite lane, type of vehicle, and shoulder width as independent variables. The study discovered that driver lane change behavior, number of vehicles in the opposite lane, vehicle type in the opposite lane, and shoulder width all have significant effects on vehicle speed characteristics at horizontal curves, in addition to the radius of the curve. These findings are useful for the design of horizontal alignment and evaluating countermeasures for vehicular driver safety at horizontal curves. [ABSTRACT FROM AUTHOR]

Several research studies conducted in North America and Europe have consistently shown that converting signalized intersections into roundabouts leads to safety benefits. These studies have led North American and European transportation agencies to convert hundreds of signalized intersections into roundabouts over the last few decades. Meanwhile, the Emirate of Abu Dhabi, the largest emirate in the United Arab Emirates (UAE), has replaced many of its long-standing roundabouts with signalized intersections (i.e., controlled by traffic lights) despite the fact that no UAE-based scientific study comparing the safety performance of these two intersection types can be found in the literature. Hence, the objectives of this paper are to (i) identify factors that significantly contribute to fatal intersection-related crashes and (ii) assess the in-service safety performance of signalized intersections and roundabouts. It is anticipated that the findings from this research will provide road designers and decision-makers with much needed scientific guidance on which factors contribute to fatal intersection crashes as well as on whether converting existing roundabouts into signalized intersections improves public safety or not in Abu Dhabi. The findings from this research should also benefit neighboring Gulf Cooperation Council (GCC) countries considering their similarities in road design, traffic characteristics, and driving culture. [ABSTRACT FROM AUTHOR]

Autonomous driving decision is a critical component of automatic driving system, which informs and updates the unmanned vehicle of object movements. However, end‐to‐end autonomous driving decision is still a great challenge due to the different scales of traffic target in the wild dynamic traffic scenes. To solve these problems, this paper proposes a novel model with attention mechanism and spatiotemporal features extraction. Specifically, for the important spatial information of traffic targets with scale differences, the spatial dimensions of height H, width W and channel C are independent of each other to build sparse spatial attention map. Moreover, different sparse masks are trained for spatial network by pruning elements of feature maps at the end of each block of backbone, which improves the accuracy of the two subnetworks of spatial network by 2.3% and 3.9%, respectively. Then the extracted spatial information is introduced jointly to the time sequence network with previous speed as input to obtain the vehicle steering angle and speed. Experiments on public virtual datasets show that the prediction accuracy of the model reaches 85.8%. Compared with other state‐of‐the‐art models, our model increased by 4.8% and 2.2%, respectively. [ABSTRACT FROM AUTHOR]

Perception response time (PRT), the time required for drivers to respond to roadway events, is a concept that is derived from scientific psychology. The concept is now fundamental to human factors and ergonomics (HFE), to the design of transportation systems, and is often called upon in forensic analyses of traffic crashes. Yet the application of PRT is neither simple nor straightforward, especially when evaluating human performance under difficult conditions, which is typically the situation in forensic analysis of traffic crashes. This article revisits these fundamental limitations by reviewing the scientific history of PRT, highlighting its utility and evolution as well as important constraints on its application. Common violations of these constraints and their ramifications for providing accurate and defensible information in forensic practice are discussed. We conclude that driving behavior is both complex and variable, and no single PRT value, adjusted or not, will ever be universally applicable. [ABSTRACT FROM AUTHOR]

The complex environment at grade crossings and the severe collision consequences give rise to the concern of safety condition at crossings among traffic control authorities. Optimizing conventional devices and applying emerging technologies are worthwhile measures to improve the safety conditions at grade crossings. In this study, a flashing-light running (FLR) warning system was proposed to reduce crossing violation and improve performances of drivers at flashing-light-controlled grade crossings (FLCGCs). Forty-four fully licensed drivers aged between 30 and 48 years participated in a driving simulator study to investigate the efficacy of two countermeasures of the system: proposed design of signs and pavement markings (PSM) for grade crossing, and two-stage in-vehicle audio warning (IVAW) technology. A range of flashing light trigger timing and two foggy conditions were designed in this experiment to test the system applicability. Drivers' gender and vocation were considered as well to examine drivers' adaptation to the new proposed system. Five variables were collected and analyzed in this study to investigate the effectiveness of the system, i.e., drivers' compliance, approaching mean speed, brake reaction time, deceleration, and red-to-crossing time. Results showed that drivers' driving performances were improved in both PSM only condition and PSM + W condition. The FLR warning system could eliminate the negative effects of foggy weather and reduce gender differences in driver behaviors to some extent. These findings suggested that the FLR warning system has a potential to reduce the probability of grade crossing collisions. [ABSTRACT FROM AUTHOR]

In research on traffic injury prevention, young male drivers willing to take risks are known as "young problem drivers" and have been identified as the greatest road safety challenge. This intersectional study draws on interviews and participant observation, and employs a masculinity perspective to explore how 12 young, male drivers who were injured in severe accidents assess driving after their accidents and ways in which they construct their identities as disabled men. While the participants cited their accidents as a turning point that prompted a change in their attitudes and practices regarding driving, they often continued to engage in deviant driving practices, especially speeding. In addition, the men tended to distance themselves from the social category of disability. We propose that the field of traffic injury prevention would benefit from supplementing the biological approach in the research literature with cultural perspectives on the internal logics and prevailing masculinity discourses that guide the choices of young, male drivers. Also, we argue that the men's negotiation of disability illustrates the stigma still attached to the social category of disability. [ABSTRACT FROM AUTHOR]

Considering the influence of slope sections and random degradation of the communication function of cooperative adaptive cruise control vehicles and the effect of the cooperative adaptive cruise control vehicle group driving, a linear stability criterion for heterogeneous traffic flow composed of cooperative adaptive cruise control vehicles and humanly-driven vehicles on slopes is derived, and a parameter sensitivity analysis is carried out. On this foundation, the safety of traffic flow on two-lane roads up and down hills is simulated while considering the lane-changing behavior of automobiles. The stability study shows increased cooperative adaptive cruise control vehicle penetration and uphill gradient will help improve traffic flow stability. In contrast, the increase in the downhill slope will intensify the transmission amplitude of the disturbance. When vehicle starting sensitivity is 2.5, and the gradient is 60, the minimum cooperative adaptive cruise control vehicle penetration required for mixed traffic flow to maintain stability on a downhill at any initial equilibrium speed is 85%, and the minimum penetration required on an uphill is 73%, and this proportion decreases with the increase in the uphill gradient and increases with the rise in the downhill slope. According to the safety study, increasing cooperative adaptive cruise control vehicle penetration and implementing lane-changing rules will improve traffic flow safety. Compared with the straight section, under the same conditions, the traffic flow safety of the uphill section is the best, and the safety of the downhill section is poor, which is consistent with the stability analysis results. This study is of great significance for future traffic control strategies for mountain roads. [ABSTRACT FROM AUTHOR]

Realistic microscopic traffic simulation is essential for prospective evaluation of the potential impacts of new traffic control strategies. Freeway corridors with interacting bottlenecks and dedicated lanes generate complex traffic flow phenomena and congestion patterns, which are difficult to reproduce with existing microscopic simulation models. This paper discusses two alternative driving behavior models that are capable of modeling freeways with multiple bottlenecks and dedicated lanes over an extended period with varying demand levels. The models have been calibrated using archived data from a complicated 13-mile long section of the northbound SR99 freeway near Sacramento, California, for an 8-hour time period in which the traffic fluctuated from free-flow to congested conditions. The corridor includes multiple bottlenecks, multiple entry and exit ramps, and an HOV lane. Calibration results show extremely good agreement between field data and model predictions. The models have been cross-validated and produced similar macroscopic traffic performance. The main behavior that should be captured for successful modeling of such a complex corridor includes the anticipative and cooperative driver behavior near merges, lane preference in presence of dedicated lanes, and variations in desired headway along the corridor. [ABSTRACT FROM AUTHOR]

Driving under the influence is a major threat to road safety in South Africa. Various psychoactive substances (both licit and illicit) have the potential to adversely affect driving performance and increase the probability of a road traffic accident. While it is common practice in South Africa to test drivers for alcohol levels, testing for additional impairing substances (including drugs of abuse) is rarely performed. In terms of current South African legislation, only driving under the influence of alcohol and a 'drug having a "narcotic" effect' is prohibited. This excludes several impairing psychoactive drugs which are not classified as narcotic substances. The aim of this article is to highlight issues and/or limitations surrounding drugged driving and to propose appropriate considerations for revision of the National Road Traffic Act. We also recommend revising existing legislation to include a comprehensive statutory definition and detailed provisions for drug testing to deter impaired driving. [ABSTRACT FROM AUTHOR]

Purpose: Glaucoma affects different aspects of vision including visual field. This prospective observational study aims to collect details of driving license (DL) renewal procedure (in an urban metro in India) among patients with diagnosed glaucoma and the method of reporting of vision-related requirements during renewal.Methods: One-hundred patients with diagnosed glaucoma above 40 years, having valid DL (with at least one renewal cycle), were included. Patients with other ocular comorbidities were excluded. Driving Habits Questionnaire and a questionnaire about license renewal were administered. Driving eligibility was compared to international guidelines.Results: Study population included patients with 69% early, 29% moderate, and 2% advanced glaucoma. Sixteen percent of patients had stopped driving. Legal license renewal procedure was bypassed by 45%. Form-1 was not submitted by 43% and 49% did not submit Form-1A at the time of renewal. Only 7.01% mentioned about glaucoma in the self-declaration form. None were asked about their visual field during renewal. Among 61 patients who submitted a medical certificate, the undersigning doctor was an ophthalmologist in only six patients. Thirty percent patients with valid Indian DL would not have satisfied International College of Ophthalmologists guidelines. Driving difficulties were experienced by 44%, more so in advanced glaucoma (F (1, 82) = 22.12, P < 0.001).Conclusion: Vision-related testing at the time of renewal of DL is inadequate in India. Chronic eye diseases such as glaucoma are commonly not self-declared or detected at pre-renewal testing. Clear-cut guidelines about visual requirements and implementation are required to prevent road traffic events because of vision-related errors. [ABSTRACT FROM AUTHOR]

Highlights • Trajectories play a critical role in CF model calibration and validation. • Developed a pattern recognition algorithm to differentiate driving regimes. • Developed a method to distinguish between free flow and CF sections. • Applied the algorithm to US-101 and reconstructed I-80 data. • Most trajectories in these datasets belong to acceleration, deceleration, and following. Abstract Vehicular trajectories are widely used for car-following (CF) model calibration and validation, as they embody characteristics of individual driving behaviour (each trajectory reflects an individual driver). Previous studies have highlighted that the trajectories should contain all the major vehicular interactions (driving regimes) between the leader and the follower for reliable CF model calibration and validation. Based on Dynamic Time Warping and Bottom-Up algorithms, this paper develops a pattern recognition algorithm for vehicle trajectories (PRAVT) to objectively, accurately, and automatically differentiate different driving regimes in a trajectory and then select the most complete trajectories (i.e. trajectories containing a maximum number of regimes). PRAVT is rigorously tested using synthetic data and then applied to the NGSIM data. We have observed that the NGSIM data are dominated by the trajectories which contain only three regimes, namely acceleration, deceleration, and following, 77% of the trajectories lack the standstill regime, and no trajectory in the NGSIM data is complete. These findings' impact on how to properly utilize NGSIM data can be profound. Given the extensive use of the NGSIM data in the traffic flow community, this paper also provides insights about the types of regimes contained in each trajectory of the NGSIM data. [ABSTRACT FROM AUTHOR]

This driving simulator study investigated the impact of perceptual countermeasures on driving behavior by creating perceptual effects via pavement markings. Two different marking schemes (i.e. Optical Circles and Optical Bars) were tested separately for road transitions between rural and urban areas where the speed limit reduces from 70 kph to 50 kph. The tested treatments were intended to achieve combined perceptual effects (i.e. increase drivers' attention, perceptual speed and perceptual road narrowing effect) independently. Data were analyzed for 44 participants (30 men and 14 female). The study results showed that the speed was reduced significantly for both road marking treatments, however, the Optical Circle scenario in which circles with increasing size were implemented was the most effective solution. Moreover, standard deviation of acceleration/deceleration and lateral position were not found to be significant due to the treatments. This indicates that drivers did not decelerate or evade vehicles unsafely when confronting the road markings. The obtained results recommend Optical Circles to policy makers for further evaluation as a low-cost speed management tool. [ABSTRACT FROM AUTHOR]

The objective of this paper is to investigate about the driving style in different types of roads, with the final aim to establish some domains of road safety based on speeds and accelerations. We identify a tool that can provide an objective indicator of driving behaviour, represented by the percentage of points outside the domain: the more the percentage of points outside the domain is, the more the driving risk is. The proposed work is supported by an experimental survey consisting in the monitoring of real paths ran by drivers. For each path, the instantaneous speed and acceleration along the pattern were registered by means of GPS-enabled smartphones. Three different roads placed in the South of Italy were analysed, and specifically, a minor rural arterial road, a principal rural arterial road, and a freeway. The registered parameters were used for defining a safety domain which establishes if the driver had a safe behaviour or an unsafe one. The proposed methodology starts from the dynamic equilibrium of the vehicle, and arrives to establish a curve expressing the relationship between the speed and the acceleration vectors, which represent the domain within which the driver behaviour can be considered as safe. Having different formulations concerning the friction factor for the three different kinds of road, we obtained three different curves, or domains. Interesting findings were obtained by comparing the results from the proposed methodology for the different types of roads. As expected, the limits of the domain are quite different among the roads, because each road has its own characteristics. [ABSTRACT FROM AUTHOR]

Objective: A rotated head posture at the time of a rear-end impact is associated with a higher risk of acute and chronic whiplash injury. The objective of this study was to quantify the amplitude and duration of rotated head postures observed in drivers during naturalistic driving.Methods: Twenty volunteers (14 males: 36 ± 12 years, 6 females: 27 ± 5 years) drove a 2010 Subaru Impreza on public roads while their 3D head angular position relative to the car was recorded using inertial measurement units. An experimenter rode in the passenger seat (right side) and logged when subjects performed one of 6 head movements: Bilateral shoulder and side mirror checks, looking at the rearview mirror, and looking at the front seat passenger. Video of the subjects was used to confirm the logged head movements and identify movements that the experimenter missed. The duration and amplitude of all 6 head movements were tabulated and then compared between periods when the car was moving and when the car was stationary.Results: During a 68 ± 5-min drive, subjects performed a median (range) of 15 (5-39) left shoulder checks, 82.5 (29-167) left mirror checks, 40.5 (10-168) rearview mirror checks, 27.5 (3-113) right mirror checks, 60 (0-185) passenger looks, and 12.5 (1-28) right shoulder checks. Peak yaw angles of the head relative to the vehicle for these 6 movements averaged -81.5°, -34.3°, 16.2°, 42.1°, 58.2°, and 84.3°, respectively. Drivers spent a larger proportion of time in nonneutral postures when the vehicle was stopped (17.5%) compared to moving (8.2%) (Z = 3.92, P < .0001). Drivers also moved their head further from neutral during the movements when the car was stationary compared to moving (t19 = 5.90, P < .0001).Conclusions: Drivers use larger and longer duration head movements when stationary than when driving. Given an increased risk of whiplash injury for initially rotated head postures, these findings provide a possible explanation for why drivers are more likely to be injured when hit from behind while their vehicle is stationary. Further, the head postures characterized in this study can be used as initial conditions in volunteer and computational studies to improve our understanding of why nonneutral head postures are associated with increased whiplash injury risk. [ABSTRACT FROM AUTHOR]

Objective: The aims of this study were to extend the current literature on school climate that is focused on understanding how teacher, administrator, and student perceptions about driving-focused aspects of the social, educational, and institutional climate of schools can affect students' achievement, behavior, and adjustment toward the development of the concept of a school safe driving climate (SSDC) and initiate the development of tools and processes for assessing SSDC.Methods: A mixed methods approach was used to develop an initial version of a survey-based measure of SSDC that involved self-report surveys (students) and in-depth interviews (teachers). Exploratory factor analytic procedures identified SSDC constructs and a regression framework was used to examine associations among SSDC constructs and self-reported driving behaviors. Qualitative data were subjected to inductive analysis, with a goal of elucidating teachers' perspectives on SSDC and an SSDC intervention.Results: The study sample consisted of 947 adolescents (48% male) from one large high school and 44 teacher advisors. Participants were recruited from a school participating in a state-wide effort to promote transportation safety through peer-led programming. Two SSDC factors were identified-Administrative contributions to school safety and value of school safety-that were associated with adolescents' perceptions of their driving behaviors. Adolescents perceived that the intervention affected administrative safety. Teacher interviews contextualized these results and provided guidance on program revisions.Conclusions: Safe driving climate may be an important, modifiable, and measurable aspect of school climate. Additional research is needed to refine the assessment tool and to use it in longitudinal and experimental studies. [ABSTRACT FROM AUTHOR]

Objective: This study intended to investigate the interactions between accident rate and traffic signs on state roads located in Croatia and accommodate the heterogeneity attributed to unobserved factors. Data from 130 state roads between 2012 and 2016 were collected from Traffic Accident Database System maintained by the Republic of Croatia's Ministry of the Interior.Methods: To address the heterogeneity, a panel quantile regression model was proposed, in which a quantile regression model offers a more complete view and a highly comprehensive analysis of the relationship between accident rate and traffic signs, and the panel data model accommodates the heterogeneity attributed to unobserved factors.Results: Results revealed that (1) low visibility of material damage (MD) and death or injury (DI) increased the accident rate; (2) the number of mandatory signs and the number of warning signs were more likely to reduce the accident rate; (3) the average speed limit and the number of invalid traffic signs per kilometer exhibited a high accident rate.Conclusions: To our knowledge, this study is the first attempt to analyze the interactions between accident consequences and traffic signs by employing a panel quantile regression model; by including visibility, the present study demonstrates that low visibility causes a relatively higher risk of MD and DI. It is noteworthy that average speed limit positively corresponds with accident rate; the number of mandatory signs and the number of warning signs are more likely to reduce the accident rate; and the number of invalid traffic signs per kilometer is significant for the accident rate; thus, regular maintenance should be performed for a safer roadway environment. [ABSTRACT FROM AUTHOR]

When driving a vehicle, the driver must allocate adequate attention to the demands of driving in order to be safe. Based on analyses of vehicle data, driving environment data, and videos of the road ahead, a driving task demand prediction model based on real-time road traffic data was established in this study. Assessments of driving task demands allowed for the validation of this model. In addition, intervention strategies were proposed for distractions from in-vehicle secondary tasks at different levels of demand. The analysis showed that at a high driving task demand, the control of all in-vehicle information systems (IVIS), except for the playing of radio or CD, should be warned against or forbidden. Meanwhile, distractions from secondary tasks originated from 91% of the in-vehicle foreign objects, and 67% of the in-vehicle facilities can be avoided by formulating precaution strategies. This study provides methods and technical support for the management of driver distraction precaution. [ABSTRACT FROM AUTHOR]

In traffic systems, cooperative driving has attracted the researchers’ attention. A lot of works attempt to understand the effects of cooperative driving behavior and/or time delays on traffic flow dynamics for specific traffic flow models. This paper is a new attempt to investigate analyses of linear stability and weak nonlinearity for the general car-following model with consideration of cooperation and time delays. We derive linear stability condition and study how the combinations of cooperation and time delays affect the stability of traffic flow. Burgers’ equation and Korteweg de Vries’ (KdV) equation for car-following model considering cooperation and time delays are derived. Their solitary wave solutions and constraint conditions are concluded. We investigate the property of cooperative optimal velocity (OV) model which estimates the combinations of cooperation and time delays about the evolution of traffic waves using both analytic and numerical methods. The results indicate that delays and cooperation are model-dependent, and cooperative behavior could inhibit the stabilization of traffic flow. Moreover, delays of sensing relative motion are easy to trigger the traffic waves; delays of sensing host vehicle are beneficial to relieve the instability effect to a certain extent. [ABSTRACT FROM AUTHOR]

Novice drivers are considered as the riskiest group of drivers due to caused accidents and injuries related to inexperience and propensity to take risks on the road. Thus, prospective analysis of importance of driving learning history for the novice drivers' future involvement in traffic violations or road accidents is extremely encouraged. This study is aimed to evaluate the importance of learning to drive experience and driving test (theory and on-road) performance for the prediction of objective traffic rules violations and later accident involvement in Lithuanian novice drivers. 598 learner drivers who obtained their driving licence for the first time participated in the longitudinal study. Information concerning their learning to drive experience before taking driving test, theory test and on-road driving test performance was obtained in the first stage of the study. Later information on the number of recorded traffic offenses committed by participants and number of accidents during the first year of their independent driving was obtained from the police records. The results showed that worse driving theory test performance, but not on-road driving test performance was related to the fact of being fined for traffic rules violations. While age and experience of learning to drive were not important predictors of being a traffic offender. Gender and length of independent driving were also important predictors for later traffic violations. This research was funded by a grant from the Research Council of Lithuania (grant No. GER- 005/2015). [ABSTRACT FROM AUTHOR]

This paper presents the design and results for field tests regarding the environmental benefits in stop-and-go traffic of an algorithmic green driving strategy based on inter-vehicle communication (IVC), which was proposed in Yang and Jin (2014). The green driving strategy dynamically calculates advisory speed limits for vehicles equipped with IVC devices so as to smooth their speed profiles and reduce their emissions and fuel consumption. For the field tests, we develop a smartphone-based IVC system, in which vehicles’ speeds and locations are collected by GPS and accelerometer sensors embedded in smartphones, and communications among vehicles are enabled by specially designed smartphone applications, a central server, and 4G cellular networks. Six field tests are carried out on an uninterrupted ring road under slow or fast stop-and-go traffic conditions. We compare the performances of three alternatives: no green driving, heuristic green driving, and the IVC-based algorithmic green driving. Results show that heuristic green driving has better smoothing and environmental effects than no green driving, but the IVC-based algorithmic green driving outperforms both. In the future, we are interested in field tests under more realistic traffic conditions. [ABSTRACT FROM AUTHOR]

An extensive body of research has found that angry and aggressive driving are both significantly related to crash involvement. There has also been a large body of research investigating the situational factors related to angry and aggressive driving, but one interesting question that has not yet been answered is whether the enforcement of traffic laws causes or reduces angry and aggressive driving. The independent region of Northern Kosovo represents a unique opportunity to investigate the impact of a lack of traffic enforcement on driving behaviour. Therefore, the present study set out to investigate whether the presence of traffic enforcement has a significant impact on the level of driver anger and aggressive driving. Registered owners of motor vehicles in Northern Kosovo and Serbia were both sent a questionnaire which contained the 28-item Dula Dangerous Driving Index (DDDI) and the 21-item UK Driving Anger Scale (UKDAS). This found that anger was higher in two of the four driving anger factors (direct hostility and progress impeded) and two of the three DDDI factors (risky driving & aggressive driving). Furthermore, the present study found that the lack of police enforcement was a significant predictor of both aggressive and risky driving, even after the driving anger and demographic variables had been partialled out. Therefore, it appears that introducing or increasing traffic enforcement may be one method of reducing aggressive and risky driving behaviour. [ABSTRACT FROM AUTHOR]

The design of a mountain expressway includes many special road sections, such as the combination of sharp bends and curved slopes, which may easily cause traffic accidents. Speed limit is an effective means of ensuring the safety of travellers. A novel speed limit formulation method was proposed in this study to improve the scientific level of the speed limit standard of a mountain expressway. First, the model of vehicle driving stability in the critical state of side rollover and sideslip was established. Second, the stabilities of vehicle side rollover and sideslip on the horizontal curve and slope curve were analyzed by considering the influence of vehicle dynamic characteristics. Finally, a specific speed limit implementation scheme for a multi-curve road section was proposed with an example. Results demonstrate that when the curvature radius of the road is large, the critical speed of vehicle side rollover and sideslip is high. In particular, the critical speed of vehicle side rollover is high when the gradient value of the transverse slope of the road section is considerable within a limited range. Meanwhile, the critical speed of vehicle sideslip is high when the frictional resistance coefficient of the pavement is high. The gradient value of the longitudinal slope of the curved slope section slightly affects the critical speed of vehicle rollover and sideslip. This study provides a strong theoretical basis for setting a safe driving speed limit in curve road sections. [ABSTRACT FROM AUTHOR]

Trust in automation is a key determinant for the adoption of automated systems and their appropriate use. Therefore, it constitutes an essential research area for the introduction of automated vehicles to road traffic. In this study, we investigated the influence of trust promoting (Trust promoted group) and trust lowering (Trust lowered group) introductory information on reported trust, reliance behavior and take-over performance. Forty participants encountered three situations in a 17-min highway drive in a conditionally automated vehicle (SAE Level 3). Situation 1 and Situation 3 were non-critical situations where a take-over was optional. Situation 2 represented a critical situation where a take-over was necessary to avoid a collision. A non-driving-related task (NDRT) was presented between the situations to record the allocation of visual attention. Participants reporting a higher trust level spent less time looking at the road or instrument cluster and more time looking at the NDRT. The manipulation of introductory information resulted in medium differences in reported trust and influenced participants' reliance behavior. Participants of the Trust promoted group looked less at the road or instrument cluster and more at the NDRT. The odds of participants of the Trust promoted group to overrule the automated driving system in the non-critical situations were 3.65 times (Situation 1) to 5 times (Situation 3) higher. In Situation 2, the Trust promoted group's mean take-over time was extended by 1154 ms and the mean minimum time-to-collision was 933 ms shorter. Six participants from the Trust promoted group compared to no participant of the Trust lowered group collided with the obstacle. The results demonstrate that the individual trust level influences how much drivers monitor the environment while performing an NDRT. Introductory information influences this trust level, reliance on an automated driving system, and if a critical take-over situation can be successfully solved. [ABSTRACT FROM AUTHOR]

Vehicle onboard travel planning systems have been developed in recent years. Since the development of GPS-based devices equipped with digital mapping applications for many vehicles, route planning has become easier and more convenient for drivers. Although such systems are used by drivers, for delivery or courier companies, it is especially important to provide a high-quality service, which involves the timely delivery of goods. Traffic management authorities are also interested in acquiring data on road and traffic conditions to verify the effectiveness and smoothness of the flow of vehicles. This paper proposes a method for traffic data collection and an application for recording data of variable factors having impact on a vehicle speed in cities and agglomerations. Data acquisition and identification of factors having impact on reduction of vehicle speed in the cities has been presented for a case study of Gliwice. The results can be useful for traffic management authorities, municipal traffic, road planning departments and mobile apps designers. [ABSTRACT FROM AUTHOR]

Issues addressed Cyclists' perceptions of harassment from motorists discourages cycling. This study examined changes in cyclists' reporting of harassment pre- to post-introduction of the Queensland trial of the minimum passing distance road rule amendment (MPD-RRA). Methods Cross-sectional online surveys of cyclists in Queensland, Australia were conducted in 2009 (pre-trial; n=1758) and 2015 (post-trial commencement; n=1997). Cyclists were asked about their experiences of harassment from motorists while cycling. Logistic regression modelling was used to examine differences in the reporting of harassment between these time periods, after adjustments for demographic characteristics and cycling behaviour. Results At both time periods, the most reported types of harassment were deliberately driving too close (causing fear or anxiety), shouting abuse and making obscene gestures or engaging in sexual harassment. The percentage of cyclists who reported tailgating by motorists increased between 2009 and 2015 (15.1% to 19.5%; P<0.001). The percentage of cyclists reporting other types of harassment did not change significantly. Conclusions Cyclists in Queensland continue to perceive harassment while cycling on the road. The amendment to the minimum passing distance rule in Queensland appears to be having a negative effect on one type of harassment but no significant effects on others. So what? Minimum passing distance rules may not be improving cyclists' perceptions of motorists' behaviours. Additional strategies are required to create a supportive environment for cycling. [ABSTRACT FROM AUTHOR]

The present paper proposes a conceptual framework for the driver’s visual–spatial perceptual processes. Based on a theoretical analysis of driving proposed by Gibson and Crooks [(1938). A theoretical field-analysis of automobile-driving.The American Journal of Psychology,51, 453–471. doi:10.2307/1416145], the developed field of safe travel (FoST) framework suggests that at any moment the driver constructs a “field” by integrating two perceptual entities: (i) the possible available spatial fields for locomotion and (ii) the driver’s mental image of ego-vehicle outer-line and motion dynamics. This framework is used to reinterpret in a unified way a number of disparate research findings reported in the literature concerning specific driving sub-tasks (e.g. lane keeping and car following). It is argued that the FoST framework may be used to predict drivers’ behaviour in various traffic/situation environments based on their prioritisation between the above two perceptual entities. Implications of the proposed framework at a theoretical and practical level, in view of the future of driving with multiple levels of automation, are also discussed. [ABSTRACT FROM AUTHOR]

Dangerous driving behavior detection can be used in video surveillance systems to identify dangerous patterns, such as Abrupt Double Lane Change (ALC), Retrograde Driving (RD), and Illegal U-Turn (IT), for traffic design, traffic management, and law enforcement. The purpose of this study is to develop a detection method of dangerous driving behavior based on video surveillance. First, a novel method named trajectory histogram is proposed. A set of trajectory histograms (e.g., control points histogram and velocity histogram) is constructed to represent vehicle motion. Then, a frequently used feature selection method named Minimum Redundancy and Maximum Relevance (mRMR) is introduced to evaluate the most representative trajectory histograms for dangerous driving behavior detection. In addition, a hybrid algorithm, Particle Swarm Optimization-Support Vector Machine (PSO_SVM), is then developed to identify dangerous driving behavior. To validate the performance and effectiveness of the proposed method, several experiments are conducted. The results show that mRMR is better than other representative methods, namely Conditional Mutual Information Maximization (CMIM), Mutual Information Maximization (MIM), and ReliefF, for evaluating the most representative trajectory histograms. Based on the most representative trajectory histograms, the detection accuracy rate of dangerous driving behavior using PSO_SVM is superior to those of the most frequently used classifiers—Naïve Bayesian Classifier (NBC), k-Nearest Neighbor (kNN), and C4.5 decision tree. In addition, we find that the proposed method outperforms the two common approaches for dangerous driving behavior detection in video surveillance systems. Therefore, the proposed method can be widely applied to detect dangerous driving behavior in video surveillance systems. [ABSTRACT FROM PUBLISHER]

In rapidly developing economies, like urban India, where road traffic injury rates are among the world's highest, the corporate workplace offers a non-traditional venue for road safety interventions. In partnership with a major multinational corporation (MNC) with a large Indian workforce, this study aimed to elicit local employee perspectives on road safety to inform a global corporate health platform. The safety attitudes and behaviours of 75 employees were collected through self-report survey and focus groups in the MNC offices in Bangalore and Pune. Analysis of these data uncovered incongruity between employee knowledge of safety strategies and their enacted safety behaviours and identified local preference for interventions and policy-level actions. The methods modelled by this study offer a straightforward approach for eliciting employee perspective for local road safety interventions that fit within a global strategy to improve employee health. Study findings suggest that MNCs can employ a range of strategies to improve the road traffic safety of their employees in settings like urban India including: implementing corporate traffic safety policy, making local infrastructure changes to improve road and traffic conditions, advocating for road safety with government partners and providing employees with education and access to safety equipment and safe transportation options. [ABSTRACT FROM AUTHOR]

Conclusive evidence has justified great importance of energy management strategies in the performance and economy of plug-in hybrid electric vehicles (PHEVs). This article pays attention to improve adaptive equivalent consumption minimization strategy (A-ECMS) for parallel PHEV based on driving behavior recognition and real time traffic information prediction. Three main efforts have been made to distinguish our work from exiting research. Firstly, a hierarchical driving behavior model is constructed, providing in-depth knowledge about behavior generation, transmission, and consequence. Secondly, an online driving behavior classification method is designed. The proposed method is the coefficient result of offline driving behavior study based on self-report driving behavior questionnaire (DBQ) and online driving behavior discrimination by BP neural network. Thirdly, an improved adaptive equivalent consumption minimization strategy (IA-ECMS) is formulated based on identified driving behavior and predicted real time traffic information. The IA-ECMS can realize equivalent factor tuning instantaneously and reasonably. The simulation results indicate the proposed energy management strategy holds potential in fuel economy improvement than A-ECMS. [ABSTRACT FROM AUTHOR]

Under the traffic environment of the Internet of Vehicles, especially with the development of vehicle-to-vehicle technologies (i.e., V2V), drivers not only frequently perceive the vehicle information for preceding vehicles but also can actively check the real-time information of following vehicles with the assistance of V2V technologies. However, those traditional traffic flow models where driving behaviors are driven only by the preceding vehicle information are no longer suited to describing this situation. Therefore, a bidirectional cellular automaton model is proposed under active bidirectional looking (ABDL) context, which involves the actively obtained succeeding vehicle information and includes two special cases (i.e., the forward-looking only (FLO) and backward-looking only (BLO)). Meanwhile, a methodology of giving the sensitivity coefficients in the randomization probability of braking is introduced, which helps categorize drivers into three different sensitivity types (i.e., aggressive, normal, and conservative). Subsequently, various kinds of homogeneous and heterogeneous vehicle fleets are generated depending on the combinations of stimulation type (i.e., ABDL, FLO, and BLO) and the sensitivity types, whose safety performance can be evaluated by the average danger coefficients. Finally, through numerical experiments, it is concluded that considering both the preceding and succeeding vehicle information under V2V while driving is conducive to improving the safety performance, and the vehicular flow state, stimulation type, sensitivity type, and orders between different stimulation or sensitivity types have an important effect on the safety performance. [ABSTRACT FROM AUTHOR]

Measures of traffic organization and traffic management in school zones, key protection areas for traffic safety, have been increasingly discussed by government administrations at all levels and researchers as well. Juveniles' trips occur frequently near school areas, especially in primary and secondary school zones. The sensitive topic of these vulnerable road users encountering traffic accidents tends to draw the whole society's attention. In this regard, the paper analyzed different traffic characteristics of 20 primary school zones in Beijing. With the starting point of traffic safety in the area, the paper divided these school zones by type, which was then verified preliminarily reliable and proper, by means of field measurement and driving simulation test, with speed characteristics as the major basis for judgment. By doing this, the authors look forward to providing a theoretical basis for carrying out measures of traffic organization and traffic management. [ABSTRACT FROM AUTHOR]