How left-turning vehicles deal with conflicts at intersections: A driving behavior model based on relative motion risk quantification

Jun Hua, Bin Li, Lin Wang and Guangquan Lu

Physica A: Statistical Mechanics and its Applications, 2025, vol. 661, issue C

Abstract: Unprotected left turns at intersections in right-hand traffic are a critical factor affecting traffic safety. Traditional risk assessment indicators, which typically rely on vehicle relative positions, fall short in supporting yield/go decisions by left-turning drivers across different types of conflicts, and the corresponding driving behavior models struggle to capture the underlying behavioral mechanisms. To address these limitations, this paper introduces an improved risk assessment indicator based on risk field theory. By quantifying the relative motion risk between interactive vehicles, the proposed indicator offers a unified standard for intuitively determining whether a conflict has been resolved. Building on this, a Perception-decision-action behavioral framework, grounded in the preview-follower theory and risk homeostasis theory, is employed to model decision-making behaviors. This behavioral mechanism-driven model is validated through numerical simulations of vehicle trajectories, achieving a 92.59 % accuracy rate in replicating the decision-making behavior of left-turning vehicles, comparable to the performance of previous data-driven classification models. Furthermore, several cases are analyzed and discussed under different risk preferences and preview times, demonstrating that the model has potential for personalized trajectory planning. Overall, this paper provides a valuable reference model for enhancing intersection safety and advancing trajectory planning in autonomous driving systems.

Keywords: Traffic safety; Left-turning vehicle; Risk field model; Decision-making behavior; Behavioral mechanism (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437125000457
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:661:y:2025:i:c:s0378437125000457

DOI: 10.1016/j.physa.2025.130393

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().