The differences in hazard response time and driving styles of violation-involved and violation-free taxi drivers

The present study aimed to investigate the relationships between taxi drivers’ traffic violations in past driving and two domains: driving skill (hazard perception skill) and driving style. Five hundred and fifty taxi drivers aged 25 – 59 were recruited to finish a video-based hazard perception test and the Chinese version of the Multidimensional Driving Style Inventory (MDSI). The relationships between hazard response time, driving style and traffic violations were examined, and the differences in hazard response times and driving styles of violation-involved drivers (n = 220) and violation-free drivers (n = 330) were compared. The results showed that taxi drivers’ traffic violations are closely related to their driving styles and hazard response time. Violation-involved drivers scored significantly higher in hazard response time and maladaptive driving styles (i.e., anxious, risky and angry styles) and lower in careful driving style than violation-free drivers. More importantly, drivers’ hazard response time and driving styles can effectively predict their violation involvement in the last 12 months with an overall classification accuracy of 66.4%. The findings provide evidence for the usefulness of video-based hazard perception tests and the MDSI in taxi driver testing and training.     

Identification of driving simulator sessions of depressed drivers: A comparison between aggregated and time-series classification

Depression has been found to significantly increase the probability of risky driving and involvement in traffic collisions. The majority of studies correlating depressive symptoms with driving, pursue to predict the differences in driving behavior if the driver has already been diagnosed. Little evidence can be found, however, on how mental and psychological disorders can be identified from driving data, and usually analyses utilize simple models and aggregated data. This study aims at utilizing microscopic data from a driving simulator to detect sessions belonging to “depressed” drivers by utilizing powerful machine learning classifiers. Driving simulator sessions from 11 older drivers with symptoms of depression and 65 healthy drivers were utilized towards that aim. Random Forests, an ensemble classifier, with proven efficiency among transportation applications, are then trained on highly disaggregated data describing the mean and standard deviation of speed and lateral or longitudinal acceleration of drivers in the simulator. The kinematic data were aggregated in 30-seconds, 1-minute and 5-minute intervals, but the corresponding time-series of the measurements were also taken into account. Furthermore, classifiers were treated with imbalanced learning techniques to address the scarcity of depressed drivers among the healthy. Time-series of mean speed and the standard deviation of longitudinal acceleration even with a duration of 30-seconds have proven to be the best predictors of driving sessions belonging to depressed drivers with a very low rate of false alarms. The results outperform previous approaches, and indicate that naturalistic driving data or deep learning could prove even more efficient in detecting depression.     

Compensating for failed attention while driving

While operating a motor vehicle, drivers must pay attention to other moving vehicles and the roadside environment in order to detect and process critical information related to the driving task. Using a driving simulator, this study investigated the effects of an unexpected event on driver performance in environments of more or less clutter and under situations of high attentional load. Attentional load was manipulated by varying the number of neighboring vehicles participants tracked for lane changes. After baseline-driving behavior was established, the unexpected event occurred: a pedestrian ran into the driver’s path. Tracking-accuracy, brake initiation, swerving, and verbal report of the unexpected pedestrian were used to assess driver performance. All participants verbally reported noticing the pedestrian. However, analyses of driving behavior revealed differences in the reactions to the pedestrian: drivers braked faster and had significantly less deviation in their steering heading with a lower attentional load, and participants in low clutter environments had a larger overall change in velocity. This research advances the understanding of how drivers allocate attention between various stimuli and the trade-offs between a driver’s focus on an assigned task and external objects within the roadway environment. Moreover, the results of this research lend insight into how to construct roadway environments that encourage driver attention toward the most immediate and relevant information to reduce both vehicle-to-vehicle and vehicle-to-pedestrian interactions.     

A study of the compliance level of connected vehicle warning information in a fog warning system based on a driving simulation

The accidents in the freeway are frequent and more serious on foggy days. Connected vehicle (CV) technology as a new technology can inform drivers of fog conditions in advance so the drivers can adjust their driving behaviors through Human Machine Interface (HMI) and Dynamic Message Sign (DMS) in the fog warning system. The level of driver's compliance with a fog warning system is the key to assessing the effectiveness of the fog warning system. To evaluate the compliance level of fog warning system, the study established a CV system testing platform based on driving simulator, and analyzed the changes in driving behavior and influencing factors for drivers under three different visibility conditions (No fog, light fog and heavy fog) based on the platform, finally, comprehensive evaluation of the optimal fog warning system under different foggy conditions based on the compliance level were made. Research indicators are divided into three aspects: 1) the response degree, including the mean speed, the minimum speed in the fog zone, the difference of the speeds when entering and leaving the fog zone, the proportion of speed following, and the speed reduction proportion prompt; 2) the response start time, which is the time to start slowing down to the speed limit; and 3) the response time duration, namely, the time in which the speed limit is followed. The results show that the response degree of the driver to the fog warning system is high, the fog warning system can effectively reduce the driving speed of the drivers and improve the speed following proportion of the drivers, the deceleration ratio of the driver at each warning point is relatively high, and the influencing factors of various indicators are complex but are mostly related to visibility and technical level. Comprehensive evaluation results show that the warning mode of the combined HMI and DMS has the highest level of compliance under light fog conditions, and when fog concentration increases, compliance level of fog warning system with HMI only is higher than others. The study establishes a reference platform for CV system and provides methods and index system for the compliance level of CV research.     

The effect of fatigue driving on car following behavior

Existing fatigued driving analysis methods mainly focus on lateral driving performance by using the measurements related to the steering wheel or lane position. There is a lack of research on longitudinal car following behavior. In this study, 40 professional drivers are invited to participate in field expressway driving experiment, lasting at least for 6 h. During the test, their performance is measured in terms of their self-reported fatigued driving level according to the Karolinska Sleepiness Scale (KSS), the PERcentage of eye CLOSures (PERCLOS) and the Time Headway (THW). Then the effects of the fatigued driving level on car following behavior are evaluated. The results indicate that the fatigue level (for both KSS and PERCLOS) has significantly impact on THW parameters, including the mean, standard deviation and minimum THW. An increase in KSS and PERCLOS leads to a lower mean and minimum THW. Meanwhile, the standard deviation of THW increases with the increase of KSS and PERCLOS. In conclusion, this study found that a higher fatigue level leads to the driver keeping a smaller THW when following another vehicle and choosing shorter THW to make lane change. More deviation of car following performance was also found with the increase of fatigue level. Therefore, the findings of this study can be used to explain fatigue as one of the major reasons for rear-end collisions. Also, the research findings demonstrate the impact of fatigue on driving behavior in terms of car following performance, which can be used as a measurement for monitoring fatigued drivers.     

Diverging diamond interchanges: A driving simulator study

This study assessed driver performance while navigating a Diverging Diamond Interchange (DDI) compared to a standard intersection in a driving simulator. A total of 201 Western Australian (WA) drivers aged 18–80 years completed the simulator drive and questionnaire. Measures of driving simulator performance assessed included time spent out of lane, number of lane excursions, compliance to the speed limit, crashes and near misses. Other driving measures, which were recorded by the researcher, included driver errors/violations such as red-light violations, wrong way violations and navigation errors. Qualitative information was also obtained in a post exit interview with each participant regarding the difficulties they experienced when driving through the DDI. A repeated-measure analysis of variance (r-ANOVA) was undertaken to examine differences in intersection type (DDI versus standard intersection) and driving performance measures from the driving simulator. The only significant result was compliance to the speed limit (F (1, 656) = 160.11, p < 0.001) on the driving simulator. A higher proportion of red-light violations were observed by the researcher as participants navigated through the DDI, compared to the standard intersection. Qualitative comments from participants also highlighted the need for better signage and road markings. Recommendations when DDIs are implemented include community education on speed limit compliance, avoidance of red-light violations and design improvements regarding signage and road markings.     

Keep on cruising: Changes in lifestyle and driving style among male drivers between the age of 18 and 23

Despite recent improvements in general road safety levels, young male drivers in most western countries continue to be overrepresented in road traffic accidents. Lifestyle related motivational factors are a key element in the young male driver problem. Based on 379 posted questionnaires completed by the same male drivers at the age of 18 and again at the age of 23, this study examined changes in the relationship between lifestyle and driving style over a 5 year period. A number of changes in car use, driving style and engagement in different leisure time activities were found. Cruising was related to an extrovert social life as well as problem behaviours such as drink driving. At the age of 18 cruising was a part of the normal social life of the majority of the participants. However, while most drivers reduced their level of cruising as well as related problem behaviour over time, a smaller group still showed a similar life style at the age of 23. The study confirmed the importance of lifestyle related motivational factors for driving behaviour among young drivers.     

Can infrastructure improvements mitigate unsafe traffic safety culture: A driving simulator study exploring cross cultural differences

This paper presents the results of a cross-cultural study to investigate the influence of traffic safety culture and infrastructure improvements on driver behaviour. To achieve this, the driving style of UK drivers was compared with that of Nigerians with and without experience of driving in the UK. A driving simulator experiment compared the actual driving style of these three groups of drivers in different safety critical scenarios. The simulated road environment varied depending on how much infrastructure was provided (low or high infrastructure). In addition, the Driver Behaviour Questionnaire was used to collect self-reported data on violations, errors and lapses. It was hypothesised that Nigerian drivers with no experience of driving in a UK road system would report and engage in more unsafe driving behaviour compared to the other two groups, and that increasing infrastructure would have little positive benefit. Overall, the results supported these hypotheses, indicating that the behaviours of drivers are interpretable in relation to their traffic safety culture, compared to changes in their driving environment.     

Characterisation of motorway driving style using naturalistic driving data

The study of measurable differences between drivers has ramifications for several sub-fields in traffic and transportation research. Better understanding of the variability in individual driving styles would be especially useful for understanding driver preferences, psychological mechanisms for vehicle control and for developing more realistic traffic simulations. In our study based on a large naturalistic data set, we investigated the driving style of 76 individuals driving in a motorway setting. We discovered that the majority of between-driver variation in keeping longitudinal and lateral safety margins, lane changing frequency, acceleration and speed preference, can be reduced to two dimensions, which we interpret as habitualised motives centred around mental effort and expediency.     

The impact of leaving a voicemail,environment familiarity,and pedestrian predictability on driving behavior

Talking on a cell phone can impair driving performance, but the dynamics of this effect are not fully understood. We examined the effects of leaving a voicemail message on driving when there are critical driving targets to attend to (crosswalks and pedestrians). Participants engaged in an ecologically-valid “voicemail” task while navigating a virtual environment using a driving simulator. We also examined the potential weakening or strengthening of effects of leaving a voicemail message on driving as the familiarity and predictability of critical targets changed. Participants completed four experimental runs through the same driving environment in a driving simulator. There were two crosswalks, one with a pedestrian entering the roadway and one without a pedestrian and the location of the pedestrian was predictable (the same pedestrian consistently used the same crosswalk) for the first three runs and then unpredictable for the fourth. Half of the participants left voicemail messages using a hands-free headset, while the other half drove in silence. Leaving a voicemail message increased steering deviation and velocity. Drivers who were leaving a voicemail message decelerated for pedestrians in the roadway to a similar speed as drivers who were not leaving a voicemail message, but they were delayed in braking. Drivers who were leaving a voicemail message also had worse memory for roadway landmarks. These effects were relatively stable across runs through the same driving environment, suggesting that familiarity and predictability did not impact the effects of leaving a voicemail message while driving. Therefore, leaving a voicemail message leads to poorer driving behavior; faster speed, variable steering, and worse memory for roadway landmarks. Interestingly, although drivers who were leaving a voicemail message were slower to react to local targets, they slowed as much as drivers who were not leaving a voicemail message and familiarity with the driving environment did not impact the effects of leaving a voicemail message on driving.     

Psychometric properties of driver self-image inventory for Chinese drivers and its associations with personality and driving style

This study aimed to adapt the Driver Self-image Inventory (DSII, Taubman-Ben-Ari, 2008) to Chinese drivers and examine its relationship with personality traits and driving style. Six hundred forty drivers aged 18–55 years agreed to participate in this study. Measurements included the DSII, a personality scale and a validated Chinese version of the Multidimensional Driving Style Inventory (MDSI). The results of exploratory factor analysis (n = 302) and confirmatory factor analysis (n = 305) yielded a three-factor scale with satisfactory reliability. Significant gender differences were found on the DSII factors, with male drivers scoring higher on the impulsive driver factor and lower on the cautious driver factor than female drivers. The validity of the DSII was supported by significant associations between the DSII factors and personality traits, driving style and number of traffic violations and accidents in the previous 12 months. Moreover, drivers with traffic accidents scored significantly lower on the cautious driver factor and higher on the impulsive driver factor than those without traffic accidents. These findings indicate that the reliability and validity of the Chinese version of the DSII are acceptable.     

Analysis of vehicle-based lateral performance measures during distracted driving due to phone use

Distracted driving due to mobile phone use has been identified as a major contributor to accidents; therefore, it is required to develop ways for detecting driver distraction due to phone use. Though prior literature has documented various visual behavioural and physiological techniques to identify driver distraction, comparatively little is known about vehicle based performance features which can identify driver’s distracted state during phone conversation and texting while driving. Therefore, this study examined the effects of simple conversation, complex conversation, simple texting and complex texting tasks on vehicle based performance parameters such as standard deviation of lane positioning, number of lane excursions, mean and standard deviation of lateral acceleration, mean and standard deviation of steering wheel angle and steering reversal rates (for 1°, 5° and 10° angle differences). All these performance measures were collected for 100 licensed drivers, belonging to three age groups (young, mid-age and old age), with the help of a driving simulator. Effects of all the phone use conditions and driver demographics (age, gender and phone use habits) on the measures were analysed by repeated measures ANOVA tests. Results showed that 1°, 5° SRRs are able to identify all the distracted conditions except for simple conversation; while, 10° SSR can detect all the distracted conditions (including simple conversation). The results suggest that 10° SRR can be included in intelligent in-vehicle devices in order to detect distraction and alert drivers of their distracted state. This can prevent mobile phone use during driving and therefore can help in reducing the road accidents due to mobile phone distractions.     

Distraction while driving: The case of older drivers

As the impairment of older drivers is especially found in perception and attention, one could assume that they are especially prone to distraction effects of secondary tasks performed while driving. The aim of the study was to examine the effect of age on driving performance as well as the compensation strategies of older drivers under distraction. 10 middle-aged and 10 older drivers drove in a simulator with and without a secondary task. To assess driving performance the Lane Change Task (Mattes, 2003) was used. This method aims at estimating driver demand while a secondary task is being performed, by measuring performance degradation on a primary driving-like task in a standardized manner. The secondary task – a self-developed computer-based version of “d2 Test of Attention” was presented both with and without time pressure. The results show that older participants’ overall driving performance (mean deviation from an ideal path) was worse in all conditions as compared to the younger ones. With regard to lane change reaction time both age groups were influenced by distraction in a comparable manner. However, when the lane keeping performance (standard deviation of the lateral position) was examined, the older participants were more affected than the younger ones. This pattern could be explained by compensation strategies of the older drivers. They focused on the most relevant part of the driving task, the lane change manoeuvres and were able to maintain their performance level in a similar way as did younger drivers. The driving performance of the older participants was not additionally impaired when the secondary task imposed time pressure. Overall, subjective rating of driving performance, perceived workload and perceived distraction was found to be similar for both age groups. The observed trends and patterns associated with distraction while driving should contribute to the further research or practical work regarding in-vehicle technologies and older drivers.     

Understanding and modelling risky driving behaviour on high-speed corridors

This study explores the relationships among various factors influencing risky driving behaviours, particularly on high-speed corridors (expressways). A total of 546 samples are collected from licenced drivers through an online survey. Exploratory factor analysis confirms the four-factor solution and the same is verified using confirmatory factor analysis. These factors are individual aberrant driving behaviour (violations and errors), risky driving behaviour performed by surrounding vehicles and dangerous manoeuvres due to prevailing road environment. Structural equation modelling is used to establish the relationships amongst the aforementioned factors. The results of the study describe that observed risky driving behaviour on expressways is mostly affected by drivers’ individual aberrant driving (γ = 0.62) followed by risky driving behaviour performed by surrounding vehicles (γ = 0.39) and least affected by the road environment (γ = 0.36). The individual driving behaviour is mostly affected by violations (γ = 0.47) followed by errors (γ = 0.38). Furthermore, differences in Driving Behaviour Questionnaire (DBQ) scales are analysed with respect to the demographic variables. Results suggest that male and young drivers report more violations than female and older drivers, respectively, however, female drivers are more error prone than male drivers. The findings of the study can be useful to identify the potential road safety countermeasures to improve the driving style as well as the driving environment.     

The role of drivers’ social interactions in their driving behavior: Empirical evidence and implications for car-following and traffic flow

Models for describing the microscopic driving behavior rarely consider the “social effects” on drivers’ driving decisions. However, social effect can be generated due to interactions with surrounding vehicles and affect drivers’ driving behavior, e.g., the interactions result in imitating the behavior of peer drivers. Therefore, social environment and peer influence can impact the drivers’ instantaneous behavior and shift the individuals’ driving state. This study aims to explore empirical evidence for existence of a social effect, i.e., when a fast-moving vehicle passes a subject vehicle, does the driver mimic the behavior of passing vehicle? High-resolution Basic Safety Message data set (N = 151,380,578) from the Safety Pilot Model Deployment program in Ann Arbor, Michigan, is used to explore the issue. The data relates to positions, speeds, and accelerations of 63 host vehicles traveling in connected vehicles with detailed information on surrounding environment at a frequency of 10 Hz. Rigorous random parameter logit models are estimated to capture the heterogeneity among the observations and to explore if the correlates of social effect can vary both positively and negatively. Results show that subject drivers do mimic the behavior of passing vehicles –in 16 percent of passing events (N = 18,099 total passings occurred in freeways), subject vehicle drivers are observed to follow the passing vehicles accelerating. We found that only 1.2 percent of drivers normally sped up (10 km/hr in 10 s) during their trips, when they were not passed by other vehicles. However, if passed by a high speed vehicle the percentage of drivers who sped up is 16.0 percent. The speed change of at least 10 km/hr within 10 s duration is considered as accelerating threshold. Furthermore, the acceleration of subject vehicle is more likely if the speed of subject driver is higher and more surrounding vehicles are present. Interestingly, if the difference with passing vehicle speed is high, the likelihood of subject driver’s acceleration is lower, consistent with expectation that if such differences are too high, the subject driver may be minimally affected. The study provides new evidence that drivers’ social interactions can change traffic flow and implications of the study results are discussed.     

Investigating sex,masculinity and femininity in relation to impulsive driving and driving anger expression

Human factors constitute a class of prominent road safety related factors. In the present study, human factors of driving were studied by investigating sex differences and gender roles in relation to impulsive driving and driving anger expression. A total of 425 drivers between the ages of 18 and 56 (M = 25.46, SD = 7.58) participated to the study and completed a series of questionnaires including a demographic information form, the Bem Sex Roles Inventory, the Impulsive Driver Behaviour Scale and the Driving Anger Expression Inventory. According to the ANCOVA results, male drivers showed higher functional impulsivity, lack of premeditation and use of the vehicle to express anger than female drivers. Additionally, hierarchical regression analyses showed that masculinity was positively associated with functional impulsivity, urgency and the dimensions of aggressive anger expression. However, femininity was positively associated with functional impulsivity and adaptive/constructive anger expression, but negatively associated with the dimensions of dysfunctional impulsivity and aggressive anger expression. Overall, the results showed the significant solo effects of masculinity and femininity on impulsive driver behaviours and driving anger expression, over and above the effects of sex, and the interaction between sex and gender roles. In the present study, previously reported findings indicating the relationships between sex and gender roles and driving anger expression were supported and extended by providing the literature with the contribution of answering the question how sex and gender roles are related to impulsive driver behaviours. The findings of the two related concepts of impulsive driving and driving anger expression were discussed in light of the current literature. Contributions, implications and future research directions concerning road safety practices were presented.     

Behavioural adaptation to driving with an adaptive cruise control (ACC)

The present paper describes a study that aims at assessment of driver behaviour in response to new technology, particularly Adaptive Cruise Control Systems (ACCs), as a function of driving style. In this study possible benefits and drawbacks of Adaptive Cruise Control Systems (ACCs) were assessed by having participants drive in a simulator. The four groups of participants taking part differed on reported driving styles concerning Speed (driving fast) and Focus (the ability to ignore distractions), and drove in ways which were consistent with these opinions. The results show behavioural adaptation with an ACC in terms of higher speed, smaller minimum time headway and larger brake force. Driving style group made little difference to these behavioural adaptations. Most drivers evaluated the ACC system very positively, but the undesirable behavioural adaptations observed should encourage caution about the potential safety of such systems.     

Evaluating driver comprehension of the roadway environment to retain accountability of safety during driving automation

Driver comprehension is a substantial component of situation awareness that involves the ability of an individual to understand the significance of an object, traffic sign, or hazard while driving. An increase in crashes related to autonomous driving systems has raised a concern regarding the safety of other roadway users due to the diminishing accountability resulting from a general lack of understanding of the limitations or disregard of the safety protocols by users. To keep drivers vigilant when engaged in partial automated systems, a methodology to monitor real-time driver comprehension was proposed. A driving simulator study consisting of 90 participants, equally split between males and females, was executed to establish driver comprehension in six different variations of driving difficulty. Joint probability density functions were created by considering percent time spent gazing, answers to probe questions, and driving performance. Based on these density functions, five levels of comprehension were devised and assigned thresholds. Overall, as task difficulty increased, a non-linear deterioration in driving speed along with an increase in total gaze duration was observed before comprehension was attained. A two-step validation protocol was also proposed to ensure similar levels of comprehension to non-automated driving from the human driver, when engaged in early forms of automation. The proposed real-time driver comprehension monitoring constitutes a first step toward developing a methodology to reinstate the accountability of safety of other roadway users when engaged in driver-in-the-loop automation systems.     

An online hazard perception training course reduces heavy braking,speeding, and over-revving rates during everyday driving

In essence, driver training involves learning the skills required to drive safely and avoid dangerous events. However, in traditional on-road driver instruction, drivers virtually never accrue experience of the most significant types of events that they are learning to avoid: crashes. One means of providing this experience safely is to present novice drivers with video clips of real crashes, as part of structured learning exercises. A six-week automated online hazard perception training course for drivers, incorporating evidence-based training methods and over a hundred crash clips, was previously found to improve novice drivers’ hazard perception skill, which is known to be an important attribute for avoiding crashes. However, since hazard perception was measured using computer-based methods, the possibility remained that the training effect might not transfer to actual driving. We report a randomized control trial in which novice drivers were recruited to assess everyday driving behaviour objectively, using g-force triggered dashcams and GPS trackers installed in their vehicles. On-road data were collected for a one-month baseline period, and for a further two months after half of the sample completed the hazard perception training course. Drivers who completed the course significantly reduced their rate of heavy-braking events, their speeding behaviour, and their rate of over-revving events. These findings support the proposal that a relatively inexpensive and highly scalable hazard perception training intervention can improve on-road driving behaviour, with the clear potential to impact real-world driver safety.