Reduction strategy of rear-end collision risks for connected and automated vehicles on freeways with different weather conditions

Yufeng Jiang, Yanyan Qin, Li Zhu, Gen Li and Hao Wang

Physica A: Statistical Mechanics and its Applications, 2025, vol. 674, issue C

Abstract: Car-following behavior is significantly influenced by weather conditions. Adverse weather conditions, in particular, negatively affect this behavior and increase rear-end collision risks. Equipped with advanced technologies, connected and automated vehicles (CAVs) have potential in reducing collision risks. To mitigate the collision risks of mixed fleet with CAVs and human-driven vehicles (HVs) on freeways with various weather conditions, this paper proposes a distance-based control strategy for CAVs. Specifically, the Gipps model was employed to represent car-following behavior of HVs under different weather conditions. Based on this, a car-following strategy for CAVs is developed to enhance their adaptability to distance situations with the vehicle ahead. To validate the effectiveness of the proposed CAV strategy, simulation experiments under both speed homogeneity and heterogeneity conditions were conducted, which analyzed the effects of weather condition, vehicle speed, and CAV penetration rate on rear-end collision risks. Furthermore, we examined how distribution patterns of CAVs in mixed fleet influenced the rear-end collision risk. The results demonstrate that the proposed CAV strategy can effectively enhance fleet stability and reduce rear-end collision risks caused by emergency braking under clear, rainy, and foggy freeway conditions. When compared to a fleet of pure HVs, reduction in surrogate measures of ITC and DRAC exceeds 75 % and 60 %, respectively, at different speed levels for a fleet of pure CAVs. Additionally, during the early stages of CAVs adoption on freeways, it is recommended to place CAVs in the middle of the mixed fleet across different weather conditions. As CAVs become more widely adopted, they are suggested to be positioned at the front of the mixed fleet to minimize the overall rear-end collision risks. While the speed heterogeneity weakens this trend, the minimum collision risk occurs when CAVs position in the front of the mixed fleet.

Keywords: Connected and automated vehicle; Car-following strategy; Collision risk; Mixed traffic; Weather condition (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:674:y:2025:i:c:s0378437125004133

DOI: 10.1016/j.physa.2025.130761

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