Driver Behaviour Research Articles

Route planning for electric vehicles

This work addresses the multi-objective route planning and charging problem for Battery Electric Vehicles (BEVs). The proposed solution is based on the NSGA-II algorithm to derive the Pareto-optimal set of eco-routes with the minimum travel and charging time, distance, energy consumption and charging costs while complying with the constraints related to the battery State of Charge (SoC) and the status of charging stations. Influencing factors, such as, vehicle and battery parameters, weather conditions, driver behaviour, road grade, Time Of Use (TOU) electricity cost, and Charging Stations (CS) status and type, are taken into account. The final results of the proposed method are compared with the well-established simulator SUMO.

Multimodal driver state modeling through unsupervised learning

Naturalistic driving data (NDD) can help understand drivers’ reactions to each driving scenario and provide personalized context to driving behavior. However, NDD requires a high amount of manual labor to label certain driver’s state and behavioral patterns. Unsupervised analysis of NDD can be used to automatically detect different patterns from the driver and vehicle data. In this paper, we propose a methodology to understand changes in driver’s physiological responses within different driving patterns. Our methodology first decomposes a driving scenario by using a Bayesian Change Point detection model. We then apply the Latent Dirichlet Allocation method on both driver state and behavior data to detect patterns. We present two case studies in which vehicles were equipped to collect exterior, interior, and driver behavioral data. Four patterns of driving behaviors (i.e., harsh brake, normal brake, curved driving, and highway driving), as well as two patterns of driver’s heart rate (HR) (i.e., normal vs. abnormal high HR), and gaze entropy (i.e., low versus high), were detected in these two case studies. The findings of these case studies indicated that among our participants, the drivers’ HR had a higher fraction of abnormal patterns during harsh brakes, accelerating and curved driving. Additionally, free-flow driving with close to zero accelerations on the highway was accompanied by more fraction of normal HR as well as a lower gaze entropy pattern. With the proposed methodology we can better understand variations in driver’s psychophysiological states within different driving scenarios. The findings of this work, has the potential to guide future autonomous vehicles to take actions that are fit to each specific driver.

Effects of safe driving climate among friends on prosocial and aggressive driving behaviors of young drivers: The moderating role of traffic locus of control

Introduction: This study focused on the impact of safe driving climate among friends on prosocial and aggressive driving behaviors for young Chinese drivers, arguing for the moderating role of traffic locus of control. Method: Three hundred and fifty-two young Chinese drivers aged 18 to 25 years agreed to participate in this study and completed the questionnaire, which included items related to safe driving climate among friends, traffic locus of control, and prosocial and aggressive driving behaviors. Results: Safe driving climate among friends and traffic locus of control had direct effects on prosocial and aggressive driving behaviors. More importantly, internal locus of control moderated the relationship between communication on prosocial driving behavior and the relationship between shared commitment to safe driving and aggressive driving behavior. External locus of control moderated the relationship between social costs and prosocial driving behavior and the relationships between shared commitment to safe driving and prosocial and aggressive driving behaviors. It can be inferred that the effects of safe driving climate on prosocial and aggressive driving behaviors varied with their levels of traffic locus of control. Practical Applications: This study enriches current theoretical frameworks and may be applied in the development of interventions and training for young drivers from the perspective of safe driving climate among friends and traffic locus of control.

The Impact of Fatigue and Behaviour of Driver on Probability of Accidents Severity in Motorcyclists

This study focuses on the influence of fatigue factors and driving behaviour on the probability of severely and mildly injured to motorcyclists. The respondents of this study were motorcyclists who had suffered an injury. The results of the analysis of 282 respondents with Bayes Theory and GeNie 2.0 Software showed that the probability of severely injured was 16% and mildly injured was 84%. Furthermore, the validation of the model use 100 respondents. The results of the validation show that the Mean Absolute Deviation (MAD) value was 10.11%. Meaning that accuracy of model is high. After that, several scenarios were performed with the aim to know the effect of each variable on the accidents severity at the time of an accident, such as: effect of driving license ownership to accident severity, effect of long duration of driving and condition of road to the fatigue, effect of machine capacity of vehicle to accident severity. This condition will give an initial description to policy makers in an effort to minimise the victim of fatality and severely injured.

Effect of chevron design on driver behaviour when encountering and passing through a dangerous curve

Horizontal curves are locations on the road network with a high road accident risk. In order to provide drivers with timely and proper information about the upcoming curve, road authorities often use chevron signs. Although the main design of chevrons is similar in most countries (one colour for the background and another for the arrow), the combination of colours differs. The aim of this simulator study is to investigate how different colour combinations affect drivers when they encounter and drive through horizontal curves on rural roads at daytime. Overall, each of the tested chevrons reduced the driving speed (between 25 and 29 km/h), although not to the speed limit level (60 km/h). However, for curves marked with chevrons with fluorescent or white background the driving speed was the lowest at all measuring points, regardless of the curve direction. The observation of lateral movement shows that there are no significant differences in the way the vehicle is positioned when approaching and driving through curves marked with different chevrons. Based on the obtained results, practical recommendations and potential future research activities are presented.

A Comprehensive Review on the Behaviour of Motorcyclists: Motivations, Issues, Challenges, Substantial Analysis and Recommendations.

With the continuous emergence of new technologies and the adaptation of smart systems in transportation, motorcyclist driving behaviour plays an important role in the transition towards intelligent transportation systems (ITS). Studying motorcyclist driving behaviour requires accurate models with accurate and complete datasets for better road safety and traffic management. As accuracy is needed in modelling, motorcyclist driving behaviour analyses can be performed using sensors that collect driving behaviour characteristics during real-time experiments. This review article systematically investigates the literature on motorcyclist driving behaviour to present many findings related to the issues, problems, challenges, and research gaps that have existed over the last 10 years (2011–2021). A number of digital databases (i.e., IEEE Xplore®, ScienceDirect, Scopus, and Web of Science) were searched and explored to collect reliable peer-reviewed articles. Out of the 2214 collected articles, only 174 articles formed the final set of articles used in the analysis of the motorcyclist research area. The filtration process consisted of two stages that were implemented on the collected articles. Inclusion criteria were the core of the first stage of the filtration process keeping articles only if they were a study or review written in English or were articles that mainly incorporated the driving style of motorcyclists. The second phase of the filtration process is based on more rules for article inclusion. The criteria of inclusion for the second phase of filtration examined the deployment of motorcyclist driver behaviour characterisation procedures using a real-time-based data acquisition system (DAS) or a questionnaire. The final number of articles was divided into three main groups: reviews (7/174), experimental studies (41/174), and social studies-based articles (126/174). This taxonomy of the literature was developed to group the literature into articles with similar types of experimental conditions. Recommendation topics are also presented to enable and enhance the pace of the development in this research area. Research gaps are presented by implementing a substantial analysis of the previously proposed methodologies. The analysis mainly identified the gaps in the development of data acquisition systems, model accuracy, and data types incorporated in the proposed models. Finally, research directions towards ITS are provided by exploring key topics necessary in the advancement of this research area.

Evaluating Rainy Weather Effects on Driving Behaviour Dimensions of Driving Behaviour Questionnaire

This study aims to develop a modified version of the existing driving behaviour questionnaire (DBQ) by including items related to driving behaviour under rainy conditions to evaluate driving behaviour changes and their implications. A survey of 680 drivers in Iran was conducted with the modified DBQ considering rainy conditions. Exploratory and confirmatory factor analysis concluded a four-factor solution (high velocity with a law violation, slips, positive and cautious behaviours, and aggressive driving behaviours) with a 52% explanation of variance. One of the most affected driving behaviours during rainfall is the tendency of high velocity with law violation behaviours. Compared to male drivers, female drivers showed lower high-velocity behaviours with law violation when driving in dry weather and in rainy weather. Married drivers have not only less tendency to drive fast or violate the law compared to single drivers but are also less susceptible to these actions during rain. It was observed that young drivers under 25 did not change their aggressive driving behaviours in rainy conditions. The results from this study are valuable resources to help transportation agencies to understand drivers’ likely behaviour in rainy conditions and develop appropriate countermeasures to minimize the risky behaviours. Also, since aggressive driving, high acceleration, and speed variance have been reported to result in high fuel consumption and emissions, the findings from this study are valuable resources to understand the relationship between weather, driver behaviour, and emissions in future studies.

The perception of public transport drivers (PTDs) on preventing road traffic injury (RTIs) in Vanuatu: a qualitative study

ABSTRACT Purpose Road Traffic Injury (RTI) is major public health concern globally and is excessively affecting vulnerable road users in the pacific Island nations. This study aimed to explore and understand the perception of Public Transport Drivers (PTDs) on risk factors and the existing prevention strategy of RTI in Vanuatu. Methods This study employed qualitative methods that used 31 In-Depth Interviews (IDIs) to gather data from PTDs from 14 October to 30 November 2020. Purposive sampling was used to recruit PTDs from three main municipalities, Luganville, Port Vila and Lenakel. Semi-structured open-ended questionnaire were used to gather data. Interview data was transcribed and manual thematic analysis was performed to analysis the data. Results Data saturation was reach from interviewing 31 PTDs who were all male. Five main themes were generated from the study including the trend of RTI, the determinants of RTI, high-risk road users, traffic law enforcement and public education. The respondents perceived that the best measures for preventing RTI include community education, enforcement of road traffic control laws and addressing specific road infrastructure issues. Conclusions Changing driver behaviours, community education on road safety and enforcement of traffic laws are essential for preventing RTI in Vanuatu.

Modelling minicab drivers' disordered behaviour for choosing passenger and destination in Akure, Nigeria

<p><span>This study investigated the disordered behaviour of minicab drivers for choosing passenger and destination in Akure using the multinomial model and nested logit model respectively. Information was gathered by the distribution of questionnaires to minicab drivers plying Federal University of Technology Akure (FUTA) North gate to Oja-Oba axis in Akure, Nigeria. The objectives were to validate the performance of logit models; to identify the major parameters for selecting passenger and destination by disordered minicab drivers, and to examine the interrelationships of variables employed. Primary data was obtained from 314 respondents. The study found that the nested logit model gives better utility value than the multinomial logit model with ρ<sub>0</sub><sup>2</sup> = 0.48 more than ρ<sub>c</sub><sup>2</sup> = 0.46 which justifies the assertion. Also, the major parameters for selecting passengers and destination by disordered minicab drivers in Akure are transport rates variable, distance variable, and travel time variable. The study recommends that an accurate pricing policy of minicab operation should be efficiently formulated, implemented, and enacted to prevent overcharge and undercharge.</span></p>

Comprehensive driver behaviour review: Taxonomy, issues and challenges, motivations and research direction towards achieving a smart transportation environment

The aim of this article is to review and analyse previous academic articles associated with car behaviour analysis for the period of 2010 to June 10, 2021 and understand the benefits of using data collection devices. Articles related to car driver behaviour and sensor utilisation are systematically searched. Three major databases – ScienceDirect, IEEE Xplore and Web of Science – were searched. A set of inclusion and exclusion criteria were developed for the search protocol. All articles were coherently classified via taxonomy. Also. The motives that have led researchers to continue their investigations are explored. The challenges and issues of driver behaviour analysis are illustrated with respect to power consumption, data analysis, detection, cost, security and privacy, sensor usage and individual challenges. The research direction of this review points towards different aspects based on the critical analysis of the different scenarios of driver behaviour studies in real time situations. Here, the critical behaviour analysis of intelligent transportation system development is addressed. The gaps in the reviewed articles include the following: sensors used during experiments, the effect of thresholds on labelling processes or data balancing and classification accuracy, the thresholds in identifying driving styles in the car-following model, insufficient experiment size (large scale or small scale) and limitations in data pre-processing. An implementation map depicting the steps of the case study is provided to give insights into the procedures and the problems they address. This review is expected to offer valid and clear points, contributing to the enhancement of driver behaviour research.

The Indicator of GDI Engine Operating Mode and Its Influence on Eco-Driving

Elements of car construction, especially the information available on a dashboard, can stimulate the way of driving. The experiment described in the paper aimed to examine how the information provided by the indicator, which informs about the operational mode of a gasoline direct injection (GDI) engine, can contribute to eco-driving and the possible learning of acceleration pedal operation by a driver. The analysis of the fuel injection process affected by driver behaviour was an essential part of the experiment. The experiment was divided into two parts. The first one (nine tests) consisted of driving without access to the indicator information. In the second part, the information on the mode of the engine run was available for the driver. The results confirmed that the information about the type of fuel mixture used for the supply of the GDI engine facilitates an economical driving style (about 10% fuel savings) and motivates the driver to engage in eco-driving.

A Preliminary Assessment of Rider/Driver Gaze Behaviour in Slovenian Urban Areas

Motorcycle riders are an increasing group of road users. The intrinsic characteristics of powered two wheelers (PTW) allow them to be particularly flexible, both in urban and extra-urban environments. Nevertheless, crash statistics indicate that riders involved in road accidents are highly likely to suffer severe injuries, underlining the vulnerability of this group of road users. An element that can greatly affect the safety of PTW users is road design, as roads are usually designed for two-track vehicles (cars, buses, and lorries) and do not consider the needs of PTWs. Additionally, handling a motorcycle is quite different from driving a car; thus, the behaviour of riders is different to that of drivers. The aim of this paper is to compare how different road designs are perceived by riders and drivers and to preliminarily assess if riders’ behaviour and attention allocation are related. For the purpose of this research, an eye-tracking experiment was developed outdoors. Both drivers and riders travelled along a route comprising four different road designs and various road layouts, and the output was analysed both qualitatively and quantitatively. Although it was not possible to carry out a statistical analysis due to the limited number of participants, the results demonstrate that there is a difference in the gaze behaviour of drivers and riders, with the latter being far more focused on the left-hand side of the road and concentrating on defined elements of road design. Furthermore, the experiment demonstrated that a higher number of fixations is related to lower speeds. Finally, it was noted that both kinds of road users focus fairly well on the carriageway, leading to the conclusion that the indications given through road markings may be much more effective than vertical signalisation, which has rarely been observed.

Driving risks of young drivers with symptoms of attention deficit hyperactivity disorder: association with the dopamine transporter gene VNTR polymorphism

Background Road traffic injuries are a leading cause of death for young adults, and young drivers with higher expression of symptoms of attention deficit-hyperactivity disorder (ADHD) could pose an even greater risk in traffic. Dopaminergic dysfunction has been found to occur in ADHD, with the dopamine transporter (DAT) gene VNTR polymorphism (DAT1 VNTR; rs28363170) being one of the most consistent genetic markers. Thus, we aimed at clarifying how the ADHD symptoms and the DAT1 VNTR relate to risk-taking behaviour in traffic, impulsivity and driving anger in young drivers. Method We used data of two traffic behaviour study samples (n = 741, mean age = 23.3 ± 7.2 years; n = 995, mean age = 22.9 ± 8.1 years) and the Estonian Children Personality Behaviour and Health Study (ECPBHS; traffic behaviour data n = 1,016, mean age = 25.2 ± 2.1 years). ADHD symptoms were assessed by self-report with the Adult ADHD Self-Report Scale (ASRS v1.1) and impulsivity with the Adaptive and Maladaptive Impulsivity Scale. Traffic behavioural measures were either self-reported (Driver Behaviour Questionnaire, Driving Anger Scale) or obtained from databases (registered accidents and violations). Results Drivers with more self-reported ADHD symptoms also reported more risk-taking in traffic and had more of recorded traffic accidents and violations. DAT1 9 R carriers had a higher probability of high traffic risk behaviour only if they also had ADHD symptoms. Conclusion Higher level of ADHD symptoms is a significant risk factor in traffic, and carrying of the DAT1 9 R allele appears to aggravate these risks.

A novel conceptual framework investigating the relationship between roadside advertising and road safety: The driver behaviour and roadside advertising conceptual framework

This paper proposes a conceptual framework to understand the relationship between roadside advertising signs, driver behaviour, and road safety outcomes. Roadside advertising signs are external distractions that may take a driver's attention away from safety-critical driving tasks, potentially increasing crash risk through driver distraction and inattention. Although studies report safety concerns, as a whole, the body of research in the field is inconclusive with inconsistent quality, making it difficult to draw firm conclusions. Definitive links between roadside advertising and road trauma are not yet evident, which has major consequences for road regulators' capacity to develop evidence-based policy to safely administer public roads. However, a lack of consistent evidence does not indicate an absence of risk but underscores its complexity. To address this problem, the Driver Behaviour and Roadside Advertising Conceptual Framework (DBRA framework) was developed to strategically investigate and conceptualise the phenomena of roadside advertising. A new term – “extended engagement” – has also been proposed to account for situations of prolonged attentional engagement with a roadside advertising sign. Further, it is posited that important variations in driving performance may be associated with a driver's extended engagement with a roadside advertising sign. Built on extant theories of driver behaviour and empirical research, the DBRA framework is designed to be a robust tool that encourages a common agenda for future roadside advertising research.

Understanding the mechanism of lane changing process and dynamics using microscopic traffic data

The lane changing manoeuvre is a fundamental driver behaviour that determines vehicle distribution across lanes. Lane-changing behaviour has a significant effect on traffic flow and may cause traffic oscillations, relaxation, moving bottleneck, and capacity drop/breakdown. This study aims to identify the lane change window and classify the lane change behaviour of vehicles using NGSIM data. Determination of the starting and ending points (time window) of lane change operation has a significant impact on the lane change duration and dynamics. In this study, a new approach is proposed to identify the time window of lane change operation using the absolute value of the derivative of the cumulative lateral speed which reduces unintended drifts of vehicles in lateral direction. Then, the lane changes are classified into free, forced and cooperative using Hidas definition (Hidas, 2005) which does not closely replicate the field conditions. This study proposes three different methods for the classification of lane changes based on microscopic traffic variables and vehicle kinematics in the vicinity of lane changing process and these methods are verified quantitatively. Statistical tests are performed to check if the types of lane changes are statistically different. Finally, two types of classification are considered such as free lane change and constraint lane change, and a log-normal distribution is fitted for the lane change duration of these two types.

Analysis of visual risk perception model for braking control behaviour of human drivers: A literature review

In the interest of driving safety, it is essential to understand driver risk assessment to develop human-centred automated driving systems. Visual perception plays a core role in observing, analysing, and predicting driving crash risks. Furthermore, comprehensive progress of visual perception has been achieved in the development of risk perception metrics. However, it is still of interest to understand driver control behaviours, which depend on visual perception. Therefore, the objective of this literature review is to assess the potential of coupling time-remaining cues for risk perception and braking control behaviour. First, conventional risk perception metrics are classified based on trajectory, contact, and state principles, along with new analysis metrics that have been derived from conventional ones. Then, the analysis metrics are discussed based on visual perception information. Next, driver risk assessment is summarised according to the environment, driver, and object characteristics. Moreover, braking behaviour models are compared in relation to visual perception variables, action affordances, and behaviour dynamics. The current review further discusses the possibility of applying driver behaviour modelling to perception, navigation, and spatial awareness in autonomous vehicles. This human-centred approach has the potential to improve interaction between drivers and automation.

Factors related to severe single-vehicle tree crashes: In-depth crash study.

Vehicle-tree collisions are the most common type of road crash with fixed obstacle in Czech Republic. Based on the literature review and using real world in-depth crash data, this paper aims to define factors, which significantly influence the injury severity of single vehicle-tree crashes. In-depth data provide a comprehensive view to the failure on the system infrastructure—human—vehicle related to crash, the in-depth crash database include very detailed information related to infrastructure, vehicle, human failure and crash participants characteristics and their medical condition and also crash reconstruction. Multinomial logistic regression and generalized linear mixed model were used to determine the individual effect of each predictor. The statistically significant variables were the day period, trunk diameter and impact speed. Using multinomial logistic regression shows also vehicle age as statistically significant. Obtained results can help to efficiently direct countermeasures not only on the road infrastructure—e.g. speed reduction in selected locations with specified tree character. However, the emphasis should be also focused on driver behaviour.

Relating Driver Behaviour and Response to Messages through HMI in Autonomous and Connected Vehicular Environment

Mental, physical, and emotional workload is the main source for the driver’s stress, fatigue, and distraction, which affects the driving tasks performed by the driver in terms of responding to the surroundings and the delay in reacting to events. Driver behaviour is an uncertain element within Intelligent Transportation Systems (ITS). Thus, this work presents a mathematical model that accounts for three main elements in ADAS-assisted vehicles, autonomous vehicles, connected vehicles, and autonomous and connected vehicles. The model accounts for processing times by the On-Board Unit (OBU), driver time, which covers both perception and response times, and communication time, which covers exchanged messages between vehicles and/ or infrastructure. The model shows two distinct behaviours, power law trend in the case of ADAS and exponential trend in the case of autonomous and connected vehicles, with both power and exponential interacting in the case of connected vehicles. In all considered scenarios, the mathematical model presents a dynamically interacting usability function that contains probability, Gaussian interpolation, and value limiting functions. The work also shows the effect of each time component on the usability, and hence the effectiveness of avoiding incidents. The model helps in optimizing both HMI, electronics, and communication designs. Driver time, in the case of ADAS, connected vehicles, and under rare conditions in autonomous and connected vehicles is critical, hence HMI optimization is important even though in autonomous and connected vehicles is not always needed. The work shows that the best driving usability is in the case of autonomous and connected vehicles.

Driving Performance Evaluation of Shuttle Buses: A Case Study of Hong Kong-Zhuhai-Macau Bridge.

The risky behaviours of bus drivers are of great concern to public health and environmental sustainability, especially for the buses operated between cities. With this in mind, the present study examined the distribution of risky behaviours among bus drivers, and the contributing factors to risky performance. To achieve this, 1648 records of GPS trajectory data and 8281 records of advance warning message data from Hong Kong–Zhuhai–Macau Bridge shuttle buses were obtained. The temporal and spatial distribution of risky behaviours was analysed. A random parameters negative binomial model was developed to further investigate the relationship between speed-related factors and risky behaviours. The results indicated that the warning of safety distance, lane departure, forward collision, and distraction were more likely to occur on weekdays. The period between 14 and 16 o’clock obtained the highest frequency of safety distance and lane departure warnings. Regarding the model estimation results, indicators reflecting average speed, acceleration, and number of trips per day showed a statistically significant impact on safety distance and lane departure warnings. Also, the acceleration of bus drivers showed a mixed impact on lane departure warnings. Corresponding implications were discussed according to the findings to reduce the frequency of risky behaviours in shuttle bus operations.

The effects of cannabis and alcohol on driving performance and driver behaviour: a systematic review and meta-analysis.

Cannabis and alcohol are frequently detected in fatal and injury motor vehicle crashes. While epidemiological meta-analyses of cannabis and alcohol have found associations with an increase in crash risk, convergent evidence from driving performance measures is insufficiently quantitatively characterized. Our objectives were to quantify the magnitude of the effect of cannabis and alcohol-alone and in combination-on driving performance and behaviour. Systematic review and meta-analysis. We systematically searched Academic Search Complete, CINAHL, Embase, Scopus, Google Scholar, MEDLINE, PsycINFO, SPORTDiscus and TRID. Of the 616 studies that underwent full-text review, this meta-analysis represents 57 studies and 1725 participants. We extracted data for hazard response time, lateral position variability, lane deviations or excursions, time out of lane, driving speed, driving speed variability, speed violations, time speeding, headway, headway variability and crashes from experimental driving studies (i.e. driving simulator, closed-course, on-road) involving cannabis and/or alcohol administration. We reported meta-analyses of effect sizes using Hedges' g and r. Cannabis alone was associated with impaired lateral control [e.g. g = 0.331, 95% confidence interval (CI) = 0.212-0.451 for lateral position variability; g = 0.198, 95% CI = 0.001-0.395 for lane excursions) and decreased driving speed (g = -0.176, 95% CI = -0.298 to -0.053]. The combination of cannabis and alcohol was associated with greater driving performance decrements than either drug in isolation [e.g. g = 0.480, 95% CI = 0.096-0.865 for lateral position variability (combination versus alcohol); g = 0.525, 95% CI = 0.049-1.002 for time out of lane (versus alcohol); g = 0.336, 95% CI = 0.036-0.636 for lateral position variability (combination versus cannabis; g = 0.475, 95% CI = 0.002-0.949 for time out of lane (combination versus cannabis)]. Subgroup analyses indicated that the effects of cannabis on driving performance measures were similar to low blood alcohol concentrations. A scarcity of data and study heterogeneity limited the interpretation of some measures. This meta-analysis indicates that cannabis, like alcohol, impairs driving, and the combination of the two drugs is more detrimental to driving performance than either in isolation.