Large Car-following Data Based on Lyft level-5 Open Dataset: Following Autonomous Vehicles vs. Human-driven Vehicles

Car-Following (CF), as a fundamental driving behaviour, has significant influences on the safety and efficiency of traffic flow. Investigating how human drivers react differently when following autonomous vs. human-driven vehicles (HV) is thus critical for mixed traffic flow. Research in this field can be expedited with trajectory datasets...

Fusion of Gaze and Scene Information for Driving Behaviour Recognition: A Graph-Neural-Network- Based Framework

Accurate recognition of driver behaviours is the basis for a reliable driver assistance system. This paper proposes a novel fusion framework for driver behaviour recognition that utilises the traffic scene and driver gaze information. The proposed framework is based on the graph neural network (GNN) and contains three modules, namely, the...

Machine learning approaches exploring the optimal number of driver profiles based on naturalistic driving data

Driver behavior analytics is an important concept that plays a significant role in the understanding of road crashes. This paper investigates the optimal number of driver profiles to understand the most important characteristics that differentiate drivers and extract useful insights on the value of using different clustering approaches in...

A Bayesian correlated grouped random parameters duration model with heterogeneity in the means for understanding braking behaviour in a connected environment

Driver's response to a pedestrian crossing requires braking, whereby both excess and inadequate braking is directly associated with crash risk. The highly anticipated connected environment aims to increase drivers’ situational awareness by providing advanced information and assisting them during critical driving tasks such as braking....

A generic multi-scale framework for microscopic traffic simulation part II: Anticipation Reliance as compensation mechanism for potential task overload

The inclusion of human factors (HF) in mathematical models is proving crucial to allow complex driving behaviour and interactions to be explicitly considered to capture driving phenomena. An important area where such integration is required is for the role of anticipation by drivers to compensate for critical traffic situations. In this paper...

A home-based approach to understanding seatbelt use in single-occupant vehicles in Tennessee: Application of a latent class binary logit model

Although the enforcement of seatbelt use is considered to be an effective strategy in reducing road injuries and fatalities, lack of seatbelt use still accounts for a substantial proportion of fatal crashes in Tennessee, United States. This problem has raised the need to better understand factors influencing seatbelt use. These factors may...

Design guidelines for turbulence in traffic on Dutch motorways

Over the years the characteristics of traffic on Dutch motorways has changed, but its design guidelines did not develop as rapidly and large parts remain unchanged since the first guidelines from the 1970s. During the latest revision of the Dutch motorway design guidelines it became clear that a solid and comprehensive theoretical, or...

The relationship between the Driver Behavior Questionnaire, Sensation Seeking Scale, and recorded crashes: A brief comment on Martinussen et al. (2017) and new data from SHRP2

We provide a brief comment on the work of Martinussen et al. (2017), who studied the relationships between self-reported driving behavior, registered traffic offences, and registered crash involvement. It is argued that if the number of crashes is small, then the correlation with crashes is also small. Our analysis of the SHRP2 naturalistic...

National correlates of self-reported traffic violations across 41 countries

Less developed countries are overrepresented in traffic accidents, but knowledge on national differences in aberrant driving behaviours is scarce. This study investigated relationships between traffic violations measured with a 7-item Driver Behaviour Questionnaire and traffic accident involvement for an international crowdsourced sample. At...

Empirical longitudinal driving behaviour in case of authority transitions between adaptive cruise control and manual driving

Automated vehicles are expected to have a substantial impact on traffic flow efficiency, safety levels and levels of emissions. However, Fields Operational Tests suggest that drivers may prefer to disengage Adaptive Cruise Control (ACC) and resume manual control in dense traffic conditions and before performing manoeuvres such as lane changing....

Do in-car devices affect experienced users' driving performance?

Distracted driving is considered to be an important factor in road safety. To investigate how experienced user's driving behaviour is affected by in-vehicle technology, a fixed-base driving simulator was used. 20 participants drove twice in a rich simulated traffic environment while performing secondary, i.e. mobile phone and navigation system...

Investigation of driving behaviour transition during evacuation and its implication for traffic flow operations based on an open-source traffic simulation platform

Earlier studies have shown how driving behaviour during emergency evacuation is different from that under “normal” conditions. At the same time, most evacuation studies (where the driving performance is explicitly accounted for) were conducted under the assumption of a fully activated emergency environment. However, the transition phase in...