Driving patterns in connected environments

Driving patterns in connected environments: A case study of intersection-approaching behavior of professional and non-professional drivers

Zhang, H. (TU Delft Transport and Planning; Chang'an University)
Fu, Rui (Chang'an University)
Wang, Jianqiang (Tsinghua University)
Calvert, S.C. (TU Delft Transport and Planning)
van Lint, J.W.C. (TU Delft Transport and Planning)

2024

The in-vehicle communication provides promising opportunities to improve the road safety and traffic efficiency. Previous studies demonstrated that the professional drivers have better driving skills than the non-professional drivers who allocate more attention to secondary tasks. However, they may not be sensitive to the new in-vehicle technology. In addition, these qualitative studies failed to elaborate on the visual and response behavior differences among different driver groups (professional drivers such as taxi, bus, motorcoach, and non-professional drivers), and lacked the quantitative analysis of driving patterns in a new environment. This paper explores the differences in visual interaction, response characteristics, driving performance, and behavior patterns between the professional and non-professional drivers in the connected environment through a case study of intersection-approaching behavior using a driving simulator. More precisely, two driving scenarios (baseline and human–machine interface (HMI)) were designed in the driving simulator, and 65 participants, including 34 professional drivers and 31 non-professional drivers, completed the experiment. In the HMI scenario, the driver was provided with the signal light phase and phase transition remaining time of the current intersection. This paper also proposes a driving pattern extraction model based on the Bayesian non-parametric method combined with a text clustering algorithm to perform a quantitative description of the driving patterns. The results show that the professional drivers tend to interact less with the HMI compared with the non-professional drivers. Moreover, the professional drivers’ first gaze at the HMI occurs and responds earlier. The proposed driving model can effectively describe 7 patterns of intersection-approaching behavior. The connected information can significantly improve the efficiency of the intersection traffic and the driving behavior. However, the professional drivers are more responsive and behave more consistently. This study can provide insights into the development of personalized assisted driving systems, as the two driving populations differ in their interactions, responses, and behavioral patterns.

Connected vehicle
Driving patterns
HMI
Intersection
Response mechanism

http://resolver.tudelft.nl/uuid:35a592ac-b275-4706-9393-8f6d54a442c3

https://doi.org/10.1016/j.trf.2024.04.014

2024-10-25

1369-8478

Transportation Research. Part F: Traffic Psychology and Behaviour, 103, 230-259

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2024 H. Zhang, Rui Fu, Jianqiang Wang, S.C. Calvert, J.W.C. van Lint