Driver Behaviour Research Articles

How to resolve the contradiction between driving safety and lighting energy conservation in a highway tunnel? − An experiment on linear guiding system

High rates of traffic accidents and lighting energy consumption are significant problems in highway tunnels. To address these problems, this study proposes a linear guiding system that uses line-shaped visual guiding facilities to improve the local luminance and contrast, and outlines the tunnel contour and road alignment. In addition, the principle, function, setting method, and composition of the linear guiding system are discussed. Using the existing highway tunnels as prototypes, we built simulation scenarios with different luminance and conducted driving simulation experiments and questionnaire surveys. We analysed the human factor demands of tunnel driving, studied the change rule of various human factor indicators under different luminance levels, and comprehensively evaluated the impact of linear guiding system on driving safety from multiple perspectives of the driver’s vision, psychology, and behaviour. We introduce the concept of equivalent luminance, quantify the impact of linear guiding system on the driver, and explore the role of linear guiding system in energy conservation. The results showed that the linear guiding system has a positive effect on driver vision, psychology, and behaviour, particularly in low-luminance environments. A linear guiding system can optimise a driver’s visual reference frame, enhance driver visual perception in a tunnel environment, and alleviate driver tension. It helps drivers to accurately perceive their own spatial position and speed, providing a good sense of position, speed, and comfort. A 2.3 cd/m2 luminance highway tunnel with a linear guiding system is equivalent to a 4 cd/m2 luminance traditional tunnel. For highway tunnels with luminance values of 4, 5, 6, and 7 cd/m2, the equivalent luminance values of the linear guiding system are 1.7, 1.8, 1.8, and 2.1 cd/m2 respectively, which can reduce the energy consumption by 30–42 %.

Examining risky driving behaviours: A comparative analysis of SUVs and other car types

The aim of the study was to analyze whether the driving behaviour changes with different types of cars (Hatchback, Sedan and Sports Utility Vehicle (SUV)), particularly on expressways. To achieve the study's objective, an exclusive DBQ was designed. Self-reported frequency of instances related to violations, mistakes and lapses were gathered which can collectively be used to study driver's behaviour in different circumstances. A total of 546 samples were collected through an online survey from drivers across India who possessed a valid driving license. Results of exploratory factor analysis confirmed two factor solution (errors and violations) and the same was verified by confirmatory factor analysis. With the help of structural equation modelling, individual risky driving score of each driver was calculated. Based on the calculated scores, drivers were clustered into different risk levels using K-Means clustering technique. Further, ANOVA test revealed that SUV drivers performed riskier behaviour more compared to other types of cars. To compare the relationships among different risk levels with drivers' demographics and driving characteristics, two ordered logit models were developed for SUV and Standard car drivers. The results indicated that drivers' age, crash history, and speeding behaviour were statistically significant predictors of risky driving behaviour. Comparison of risk levels between SUV and Standard cars with respect to different predictor variables presented various interesting findings. These findings would be helpful in understanding the differences among risky driving behaviour performed by drivers of different types of cars and to identify the potential road safety countermeasures.

Analysis of driver behavior at grade-separated intersections to support design

Understanding driver behaviors in varied traffic scenarios is critical to the design of safe and efficient roadways and traffic control device. This research presents an analysis of driver cognitive workload, situation awareness (SA) and performance for three different scenarios, including a standard intersection and contraflow grade-separated intersections (C-GSI) and quadrant GSI (Q-GSI) with lane assignment sign manipulations. The study used a simulator-based driving experiment with application of the NASA Task Load Index and Situation Awareness Global Assessment Technique to assess the influence of the scenarios on driver behavioral responses. The findings reveal challenges for drivers navigating the C-GSI, characterized by diminished SA and elevated workload. These states were associated with behaviors such as delayed lane changes, missed opportunities for appropriate lane changes, heightened acceleration behavior within deceleration segments, and frequent speeding. In contrast, while drivers in the Q-GSI scenario faced elevated workloads, their SA remained steady, largely due to lane-specific signs facilitating early lane changes. Although the Q-GSI led to increased speed variability and slight increases in deceleration, the use of supplementary speed signage revealed a promising alternative to the S-intersection. Correlation analysis highlighted a significant relationship between mental workload and acceleration responses, indicating that increased acceleration was associated with higher mental workload. In addition, a significant negative correlation between driver perceived performance and absolute lane deviations indicated that drivers with higher self-assessed performance were more accurate in lane-keeping. The study underscores the need for GSIs and signage designs that support driver SA, manage cognitive workload to improve driver performance and increase road safety.

Energy Efficient and Adaptive Design for Wireless Power Transfer in Electric Vehicles

Wireless power transfer (WPT) has the potential to revolutionise global transportation and to catalyse the rise of the market for electric vehicles (EVs) by providing a compelling alternative to the conventional ways of charging that involve the use of cables. Nevertheless, coil misalignment, which is caused by the behaviours of drivers who park their vehicles, is a substantial challenge since it has a detrimental impact on power transfer efficiency (PTE). This work presents a unique coil design that is coupled with adaptive hardware in order to improve power transfer efficiency (PTE) in magnetic resonant coupling waste power transfer (WPT) systems and reduce the impacts of coil misalignment, which is a significant impediment that is preventing the broad implementation of WPT for electric vehicles (EVs). Simulation with ADS was used to validate the effectiveness of the new design, which exhibited a high degree of congruence with the theoretical analysis. In addition, receiver and transmitter circuitry that was specifically constructed for the purpose of simulating real-world vehicle and parking bay settings was utilised. This allowed for the collecting of PTE data in a controlled environment that was on a smaller scale. Experiments showed that there was a significant thirty percent improvement in the power transfer efficiency (PTE) at the centre of the coil array, and an astonishing ninety percent improvement was recorded when the array was misaligned by three quarters of its radius. When compared to single coil designs that serve as benchmarks, the suggested new coil array displays improved property transfer efficiency (PTE).

Trajectory outlier detection method based on group division

Trajectory-outlier detection can be used to discover the fraudulent behaviour of taxi drivers during operations. Existing detection methods typically consider each trajectory as a whole, resulting in low accuracy and slow speed. In this study, a trajectory outlier detection method based on group division is proposed. First, the urban vector region is divided into a series of grids of fixed size, and the grid density is calculated based on the urban road network. Second, according to the grid density, the grids were divided into high- and low-density grids, and the code sequence for each trajectory was obtained using grid coding and density. Third, the trajectory dataset is divided into several groups based on the number of low-density grids through which each trajectory passes. Finally, based on the high-density grid sequences, a regular subtrajectory dataset was obtained within each trajectory group, which was used to calculate the trajectory deviation to detect outlying trajectories. Based on experimental results using real trajectory datasets, it has been found that the proposed method performs better at detecting abnormal trajectories than other similar methods.

Lane Reduction and Queue Length Relationship on Arterial and Collector Roads

Geometric diversity of roads for an example is the narrowing of road segments. The purpose of this research is to determine whether lane reduction leads to significant queue lengths, observe the behaviour of drivers on those road segments, and compare the actual queue length to the queue length generated by PTV Vissim. The data used in this study consists of direct observations during peak hours in the morning, afternoon, and evening, along with simulations using PTV Vissim. The queue results obtained from PTV Vissim were validated using two types of tests. The research findings indicate a significant relationship between queue length and lane reduction during peak hours on workdays. However, during the evening peak hours on weekends, the queue length is not significantly affected by lane reduction. As a potential solution, widening each road segment in PTV Vissim was tested, which increased road capacity and slightly reduced the queues that occurred.

Life style, health seeking behaviour and nutritional status of commercial vehicle drivers in Port Harcourt, Nigeria

BackgroundHealth seeking behaviour, lifestyle characteristics and the working conditions of commercial vehicle drivers often foster unhealthy habits and increase their vulnerability to health inequalities, including overweight, obesity, cardiovascular and metabolic disorders.ObjectiveThe objective of this study was to examine the life style, dietary habit, health seeking behaviour and nutritional status of commercial vehicle drivers in Port Harcourt, Nigeria.MethodsThis descriptive and cross-sectional study adopted a simple random sampling technique to recruit 202 commercial vehicle drivers in Port Harcourt, Nigeria. A semi-structured interviewer-administered questionnaire was used to obtain information on demographics, life style and health care characteristics of the commercial vehicle drivers. The anthropometric indices (weight and Height) of the drivers were obtained and their body mass index (BMI) was determined using WHO classification. Data were analysed using descriptive and inferential statistics, and level of significance was set at p= 0.05.ResultsMean age of the drivers was 43 ± 5.2 years and majority (86%) of them have completed secondary education. The majority (59%) consume soft drinks at least once per week and 85% eat at least one meal outside their home daily, while 16% and 49% patronize herbal medicine/concoction and visit the pharmacy or chemist store to purchase drugs respectively as first point of care when sick. The prevalence of overweight and obesity among the commercial drivers was 20% and 33% respectively. There was a statistically significant relationship between elevated BMI and respondent’s age (p<0.05), level of education (P=0.05), physical inactivity (P<0.01) and frequency of alcohol consumption (P<0.05).ConclusionsThis study confirms high prevalence of overweight and obesity among the commercial vehicle drivers and its associated factors of poor nutritional habits, health and life style characteristics. Therefore, a comprehensive nutritional programme including behavioural change and communication that is context-specific targeted at commercial drivers should be implemented.

Attitudes Towards the Stress Created by Ever Increasing Traffic in the Maltese Islands

The relatively large and rapid increase in population in the Maltese Islands over the past decade has placed significant strain on the infrastructure of the country. These factors, together with the fact that issues with the public transport system have never been completely sorted, has led to an over-reliance on private cars as the main means of transport in most cases. Increased transport has been shown to increase stress and aggressive behaviour in drivers, amongst other possible negative consequences, leading to a negative effect on personal wellbeing. In order to assess the perceptions of the Maltese about the stress created by traffic, a cross-sectional study was conducted by means of telephone interviews with a stratified sample of 400 Maltese participants. A purposely designed questionnaire with twelve items scored on a seven-point Likert scale was used for this purpose. While more than four fifths of participants stated that they owned at least one car, and most agreed that traffic increases stress, both in the short and long term, less than one third of participants strongly agreed to preferring to use public transport rather than their private vehicle, even if public transport were more reliable. Females showed more anxiety than males with reference to the traffic situation and 18–29 year-olds showed the lowest level of agreement overall with the statements in the survey – a surprising result given this age group’s awareness of the negative effects of climate change on wellbeing.

The prevention of road accidents in non-expert drivers: Exploring the influence of Theory of Mind and driving style

BackgroundDrivers consider external and hypothetical behaviours of other drivers, but internal factors also impact road safety. ObjectivesThis study aims to examine the connection between Cognitive and Affective Theory of Mind (ToM) and Driving Style in road safety. It hypothesizes that a higher level of ToM corresponds to a greater ability to avoid accidents and to assume virtuous driving behaviour. The study investigates how ToM impacts driving behaviour, directly correlating with assessing potential accidents' probability and severity. Method207 non-expert drivers, including 164 females, participated in assessing Cognitive and Affective ToM through two tasks. They also completed self-measured questionnaires to assess their driving style and behaviours. In addition, they evaluated 12 videos depicting cars, motorcycles, trucks, and pedestrians to determine the probability of a road accident and the level of danger in each scenario. ResultsThe results of the mediation models clearly indicate a relationship between ToM and the reduction of road accidents. Specifically, Cognitive ToM plays a crucial role in assessing the probability of risky and dangerous situations related to Risky and Angry Driving Styles. However, it was observed that Cognitive ToM does not significantly affect the prediction of actual driving behaviours. ConclusionsFindings are discussed within the theoretical framework of the Task-Capability Interface Model and the Embodied Simulation Model based on mirror neuron research. Our results suggest the importance of creating drive-assistance systems considering both the Cognitive ToM and Driving Style to reduce road accidents among non-expert drivers.

Event-related driver stress detection with smartphones in an urban environment: a naturalistic driving study

Driving in urban areas can be challenging and encounter acute stress. To detect driver stress, collecting data on real roads without interfering the driver is preferred. A smartphone-based data collection protocol was developed to support a naturalistic driving study. Sixty-one participants drove on predetermined real road routes, and driving information as well as physiological, psychological, and facial data were collected. The algorithm identified potentially stressful events based on the collected data. Participants classified these events as low, medium, or highly stressful events by watching recorded videos after the experiment. These events were then used to train prediction models. The best model achieved an accuracy of 92.5% in classifying low/medium/highly stressful events. The contribution of physiological, psychological, and facial expression indices and individual profile information was evaluated. The method can be applied to visualise the geographical distribution of stressors, monitor driver behaviour, and help drivers regulate their driving habits.

R2DRV: study protocol for longitudinal assessment of driving after mild TBI in young drivers

BackgroundMild traumatic brain injury (mTBI) and traffic-related injuries are two major public health problems disproportionately affecting young people. Young drivers, whose driving skills are still developing, are particularly vulnerable to impaired driving due to brain injuries. Despite this, there is a paucity of research on how mTBI impacts driving and when it is safe to return to drive after an mTBI. This paper describes the protocol of the study, R2DRV, Longitudinal Assessment of Driving After Mild TBI in Young Drivers, which examines the trajectory of simulated driving performance and self-reported driving behaviors from acutely post-injury to symptom resolution among young drivers with mTBI compared to matched healthy drivers. Additionally, this study investigates the associations of acute post-injury neurocognitive function and cognitive load with driving among young drivers with and without mTBI.MethodsA total of 200 young drivers (ages 16 to 24) are enrolled from two study sites, including 100 (50 per site) with a physician-confirmed isolated mTBI, along with 100 (50 per site) healthy drivers without a history of TBI matched 1:1 for age, sex, driving experience, and athlete status. The study assesses primary driving outcomes using two approaches: (1) high-fidelity driving simulators to evaluate driving performance across four experimental study conditions at multiple time points (within 96 h of injury and weekly until symptom resolution or 8 weeks post-injury); (2) daily self-report surveys on real-world driving behaviors completed by all participants.DiscussionThis study will fill critical knowledge gaps by longitudinally assessing driving performance and behaviors in young drivers with mTBI, as compared to matched healthy drivers, from acutely post-injury to symptom resolution. The research strategy enables evaluating how increased cognitive load may exacerbate the effects of mTBI on driving, and how post-mTBI neurocognitive deficits may impact the driving ability of young drivers. Findings will be shared through scientific conferences, peer-reviewed journals, and media outreach to care providers and the public.

The role of Advance Amber Warning Signal in enhancing driver decision-making: A comparative study in Brunei Darussalam

The current study examines the impact of Advance Amber Warning Signal (AAWS) on driver behaviour and decision-making processes at two junctions on a roadway. Through on-road observations and decision tree analysis, data was collected to assess the effects of AAWS on driver responses to a yellow dilemma. The results indicated that AAWS led to a significant increase in the percentage of drivers who accelerated before stopping at the junction, while reducing uncertain changes between braking and accelerating. Moreover, AAWS resulted in improved stopping propensity, and a substantial reduction in red light violations. These findings demonstrate the positive influence of AAWS on driver behaviour, improved decision-making, and enhanced compliance with traffic regulations. The presence of AAWS equips drivers with the necessary tools to navigate challenging scenarios on the road and make safe decisions during critical moments. As a result, the implementation of AAWS has the potential to significantly enhance junction safety, optimise driver behaviour, and contribute to overall road safety measures.

Psychosocial factors, psychological well-being and safety incidents among long-distance bus drivers in Ghana: A cross-sectional survey

BackgroundCommercial bus drivers account for most road traffic crashes and related mortality. The psychosocial working conditions of these drivers have been found precarious. However, road safety initiatives in Ghana still focus on correcting risky driving behaviours, ignoring the conditions under which these drivers operate. Hence, the purpose of this study was to examine whether psychosocial work factors can predict the psychological well-being and risky driving behaviours of long-distance bus drivers in Ghana. MethodsThis quantitative cross-sectional survey recruited 7315 long-distance bus drivers that operate from Accra to other parts of Ghana and cities in other West African countries. Hypotheses were tested using Partial Least Squares Structural Equation Modelling (PLS-SEM). ResultsWe found that job demands and job resources are direct and significant predictors of psychological well-being and safety incidents among these drivers. Moreover, psychological well-being of the drivers had a significant inverse relationship with their safety incidents. Psychosocial safety climate (PSC) had a negative association with safety incidents, and a positive but non-significant association with psychological well-being. PSC had a negative and significant association with job resources contrary to the notion of the PSC theory. ConclusionPsychosocial work factors are predictors of psychological well-being and safety incidents of long-distance bus drivers. Owners and managers of bus transport businesses in Ghana, driver unions and station masters need to highly prioritise psychological health and safety of this bus drivers by providing suitable job resources and adopting bottom-up communication that might help the drivers effectively cope with their job demands.

Evaluating the Efficacy of Real-Time Connected Vehicle Basic Safety Messages in Mitigating Aberrant Driving Behaviour and Risk of Vehicle Crashes: Preliminary Insights from Highway Scenarios

Connected vehicle (CV) technology has revolutionised the intelligent transportation management system by providing new perspectives and opportunities. To further improve risk perception and early warning capabilities in intricate traffic scenarios, a comprehensive field test was conducted within a CV framework. Initially, data for basic safety messages (BSM) were systematically gathered within a real-world vehicle test platform. Subsequently, an innovative approach was introduced that combined multimodal interactive filtering with an advanced vehicle dynamics model to integrate BSM vehicle motion data with observations from roadside units. In addition, a driving condition perception methodology was developed, leveraging rough sets and an enhanced support vector machine (SVM), to identify aberrant driver behaviours and potential driving risks effectively. Furthermore, this study integrated BSM data from various scenarios, including car-following, lane changes, and free driving within the CV environment, to formulate multidimensional driving state sequence patterns for short-term predictions (0.5 s) utilising the long short-term memory (LSTM) model framework. The results demonstrated the effectiveness of the proposed approach in accurately identifying potentially hazardous driving conditions and promptly predicting collision risks. The findings from this research hold substantial promise in advancing road traffic safety management.

Factors influencing the road accidents in low and middle-income countries: a systematic literature review

This paper studies the main factors affecting road traffic accidents (RTAs) using a systematic review. The primary focus is on factors related to road characteristics and driver behaviours. This review also addresses the socioeconomic and demographic factors to provide a clear overview of which groups suffer the most from RTAs. Several factors were found to affect RTAs, notably road characteristics: highways, high-speed roads, unplanned intersections and two-way roads without dividers; driver behaviours: reckless/aggressive driving and riding, excessive speeding, unawareness of traffic laws, and not using safety equipment; and vehicle types: four and two-wheeled. This review found that male and economically productive people with less education were mostly associated with RTAs. In addition, for most of the low and middle-income countries analyzed, there is a lack of quality data relating to RTAs. Nevertheless, this review provides researchers and policy makers with a better understanding of road accidents for improving road safety.

A practical method for assessing sustainable traffic levels of roundabouts in urban areas using the macroscopic fundamental diagram

In traffic engineering, queue lengths, waiting times, and delay values are denoted as measures of effectiveness (MOEs). In the case of roundabouts, MOEs are generally calculated starting from the gap-acceptance theory in which the driver behaviour needs to be properly modelled. This research presents an unconventional technique, based on Macroscopic Fundamental Diagrams (MFDs), to describe sustainable traffic levels and (MOEs) of roundabouts, in terms of capacity, speed, density and delay. The deduction of MFDs is based on relatively simplified theoretical hypotheses, but the outcomes could be of interest in several practical applications. MFDs are estimated in the cases of single and double-lane roundabouts, modelled by microscopic simulations starting from a real-world case study in Italy. MFDs are obtained for a wider sample size of origin-destination traffic matrices taking into consideration time intervals of 5 min and 1 h. The results of this research demonstrate that the traffic distribution between arms can influence the shape of a roundabout-MFD. However, the proposed procedure allows us to evaluate the performance of a roundabout as a whole, taking into account numerous MOEs including the total capacity, the critical density and the Level of Service (LOS). Therefore, the use of MFDs could represent a complementary procedure for evaluating the performance of roundabouts.

An integrated driving safety-volatility-operational performance indicator

Understanding driver behaviour is important to improve road safety and it is essential that drivers become aware of their contribution to road traffic impacts through their driving styles. Driving on the edge of critical safety distances yields unsafety road conditions. Volatility can be defined as the extent of variations in driving, which can be characterized by sudden accelerating/braking, lane changing, and the unusually high speed for road conditions. The operational performance of the vehicle led by the driver also represents a key component regarding the efficiency of the driving. Therefore, the objective of this work is to develop an integrated indicator that objectively assesses driver behaviour based on three key components: (i) safety; (ii) volatility, and (iii) operational performance, using the respective variables: (i) time headway and stop distance, (ii) acceleration and vehicular jerk and (iii) Vehicle Specific Power mode. The indicator provides an assessment to the driver when performing a driving task and returns an overall evaluation, at the end of each trip. A microscopic traffic model VISSIM with a COM API interface was used. The case study involves a highway scenario. The model was calibrated based on the following data: a) traffic; b) vehicle dynamics from test vehicles on two highways with different specificities (e.g., slope and traffic volumes). After performing a trip, each driver receives a rating based on the proposed Driving Safety-Volatility-Operational Performance Indicator. Safety is evaluated using time headway and stop distance, volatility is assessed by acceleration and vehicular jerk, and operational performance is rated through Vehicle Specific Power mode. The experiments show the relevance of the developed indicator in evaluating the driving task.

Reported pushy driving against cyclists in Germany

Background: When cyclists and drivers share the road drivers sometimes try to make the cyclist give way. This study assessed which characteristics and attitudes are related to pushy driving. Methods: The sample included 695 drivers aged 18 to 85 years who answered a German online questionnaire on pushy driving. They saw a sketch with a cyclist in front of them whom they could not overtake easily. They reported how often they engage in different pushy driving behaviors and how legitimate and effective these are. They provided information about their mobility habits, goals, and attitudes. Results: Correlations between reported frequency, perceived legitimacy, and perceived effectiveness of pushy driving were between r = 0.78 and r = 0.80. Many correlations with pushy driving were of medium size: drivers with the goal to drive safe and friendly reported less pushy driving, drivers with the goal to get the cyclist out of the way reported more. The correlations between reported frequency of pushy driving and attitude toward cyclists, self-justification, victim blaming, and feeling bothered by cyclists in built-up areas were of medium size. Summary: The highest correlations with pushy driving were those with perceived legitimacy and perceived effectiveness of pushy driving. The results show that pushy drivers cannot be identified by demographic characteristics or mobility habits. General attitudes and the perception of pushy behaviors in specific situations and drivers' goals in these situations are more important. Discussion: There will always be roads that cyclists and drivers share. In order to reduce pushy driving, its legitimacy could be addressed by campaigns and its effectiveness by a lower speed limit and enforcement.

Extended reality in the automotive sector: A bibliometric analysis of publications from 2012 to 2022

The present study aims to present a bibliometric analysis of publications related to “Extended Reality” (XR) in the automotive sector. XR is revolutionizing the industry in all fields, and the automotive is one of the sectors that has had much to gain from this technology and its components (Virtual Reality, Augmented Reality, Mixed Reality). Articles on XR in the automotive field that were published from 2012 to 2022 were retrieved from the Scopus database. Extracted items were analysed in terms of the document type, document language, year of publication, country, authors, affiliations, sources, citations, keywords, and research domains. The open-source tool VOSviewer was used to visualize trends in research on XR applied to automotive. The analyses of 1584 documents revealed that the total number of publications has continually increased over the last 11 years. The country producing most of the articles in this field was Germany, followed by the United States and China. The most productive journal is Transportation Research Part F: Traffic Psychology and Behaviour and the institution that issued most of the articles is Technical University of Munich. From the analysis of author keywords, the prominent research areas currently involving the use of XR technologies in automotive can be highlighted: virtual prototyping, design, manufacturing, sales, training, driver or pedestrian behaviour analysis, and ergonomics. More recently, terms like artificial intelligence and autonomous vehicles have started to be used more frequently in studies in the field. The current study reveals an expanding corpus of literature on XR-based applications for the automotive sector using bibliometric methods. Researchers and stakeholders can use this study as a useful reference to comprehend the big picture and the state-of-the-art in this area.

Influence of Driver's Seat Front and Back Position on Safe Driving Behaviour

Influence of Driver's Seat Front and Back Position on Safe Driving Behaviour