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- Title
基于安全裕度的网联自主汽车换道行为 风险量化及动态平衡模型.
- Authors
陈意成; 曲大义; 邵德栋; 杨子奕
- Abstract
Along with the development of connected vehicle technology, the road traffic flow presents the mixed coexistence development of intelligent networked self-driving vehicles and traditional human-driven vehicles, and it is extremely important to study the risk characteristics of lane change driving behavior of the new networked mixed traffic flow. Based on the safety margin theory, a risk quantification model of lane changing behavior was established, and the fault tree analysis method was used to derive the temporal and spatial risks of lane changing and to quantify the risk assessment of temporal and spatial fusion to determine whether the vehicle was in a safe lane changing state and to provide early warning of the possible risks of vehicle lane changing behavior. The simulation validation analysis of the established quantitative model using SUMO software shows that the mean values of reciprocal of time to collision and instantaneous risk coefficient γ decrease by about 0. 1 and 0. 05, respectively, while the change trend tends to be stable. The safety margin risk quantification model enables the risk of lane change to be effectively controlled while the stability of traffic flow is greatly improved, which can guarantee the steady-state operation of autonomous vehicles queues in the future net connected environment and thus improve traffic capacity and traffic efficiency.
- Publication
Science Technology & Engineering, 2024, Vol 24, Issue 12, p5204
- ISSN
1671-1815
- Publication type
Article
- DOI
10.12404/jissn.1671-1815.2304695