Traffic climate, driver behaviour and dangerous driving among taxi drivers

Understanding key behavioral factors affecting road traffic citation and crash involvement of professional bus and passenger van drivers using a modified driver behavior questionnaire: an Indian perspective

A customized 27-item driver behavior questionnaire (DBQ) for professional long-distance bus and passenger van drivers in Bihar, India was tested separately and the underlying factor structures identified. In total, 156 bus and 149 passenger van drivers were surveyed and their self-reported aberrations, measured using the DBQ, were recorded along with their self-reported traffic citation and crash involvement in the past 3 years. A 21-item seven-factor DBQ and a 19-item five-factor DBQ were obtained for bus and passenger van drivers respectively through exploratory and confirmatory factor analysis. Structural equation modeling was used to find relations between DBQ factors and drivers' number of crashes and traffic citations involvements. Only speed issues could significantly explain traffic citation involvement but no factor could significantly explain crash involvement for bus drivers. For passenger van drivers, only aggressive violations could explain traffic citation involvement while unmindfulness, aggressive violations and errors could explain crash involvement.

Task and Resting-State Functional Connectivity Predict Driving Violations

Aberrant driving behaviors cause accidents; however, there is a lack of understanding of the neural mechanisms underlying these behaviors. To address this issue, a task and resting-state functional connectivity was used to predict aberrant driving behavior and associated personality traits. The study included 29 right-handed participants with driving licenses issued for more than 1 year. During the functional magnetic resonance imaging experiment, participants first recorded their resting state and then watched a driving video while continuously rating the risk and speed on each block. Functional connectome-based predictive modeling was employed for whole brain tasks and resting-state functional connectivity to predict driving behavior (violation, error, and lapses), sensation-seeking, and impulsivity. Resting state and task-based functional connectivity were found to significantly predict driving violations, with resting state significantly predicting lapses and task-based functional connectivity showing a tendency to predict errors. Conversely, neither impulsivity nor sensation-seeking was associated with functional connectivity. The results suggest a significant association between aberrant driving behavior, but a nonsignificant association between impulsivity and sensation-seeking, and task-based or resting state functional connectivity. This could provide a deeper understanding of the neural processing underlying reckless driving that may ultimately be used to prevent accidents.

Effect of psychosocial interventions on risky driving behaviours among offender drivers by using simulated and real driving: study protocol for a non-randomised controlled trial

BACKGROUND

Risky driving behaviour including anger while driving has led to millions of global road traffic crashes, thousands of mortalities and injuries. These losses are much more in middle-income countries, such as Iran. This paper explains methods of data collection in a controlled trial study for evaluating the effect of psychosocial interventions on risky driving by using simulated and real driving.

METHODS

This non-randomised controlled trial study will include 180 offender drivers. They will refer to the simulation laboratory by traffic police after their driving licences were suspended. At baseline, all participants will fill five questionnaires including demographic, Driving Anger Scale, Driving Anger Expression Scale, Spielberger's Anger and Manchester Driving Behavioural, and then they will be tested with a driving simulator. Afterwards, they will be allocated to one of three-intervention training arms (mindfulness, meta-cognition and social marketing) or a control arm without any training. Risky driving behaviours will be assessed in three follow-ups after intervention. The primary outcome of interest will be driving offences, recorded by traffic police in two time points: at 6 months and 1 year after the intervention.

DISCUSSION

This study examines the effect of three interventions in reducing driving offence. The results can end in a new therapeutic training or a new legislation that should be added to current obligatory training for getting driving licence and can lead to long-term safe driving among Iranian drivers. Future research is recommended to study the cost-effectiveness of these interventions in actual driving in Iran.

TRIAL REGISTRATION NUMBER

UMIN000039493.

Drivers’ Decelerating Behaviors in Expressway Accident Segments under Different Speed Limit Schemes

Traffic accidents occurring on expressways tend to give rise to traffic bottlenecks. To ensure the vehicles safely and smoothly pass through the accident segments, speed limits are generally taken to regulate the vehicles’ movements. This study aims to explore the decelerating behaviors of drivers under different speed limit schemes. We designed traffic accident scenarios under four speed limit schemes using the driving simulator. A total of 60 subjects drove the simulator passing the accident segments according to their habits. The vehicles’ kinematic data and the subjects’ operating data were recorded. To further analyze the drivers’ decelerating behaviors in different speed limit scenarios, driving experience was also taken into account. The results show that the speed limit schemes have significant effects on drivers’ decelerating behaviors. The more speed limit signs there are, the smoother the decelerating process will be. Driving experience significantly affects some of the decelerating parameters, including the location of deceleration starting point, average deceleration, and locations of decelerating to the initial and final speed limits. These results provide a theoretical basis for traffic safety and driving behavior management.