A Dynamic Lane-Changing Driving Strategy for CAV in Diverging Areas Based on MPC System.

Sensors(2023)

引用 2|浏览25
暂无评分
摘要
Freeway-diverging areas are prone to low traffic efficiency, congestion, and frequent accidents. Because of the fluctuation of the surrounding traffic flow distribution, the individual decision-making of vehicles in diverging areas is typically unable to plan a departure trajectory that balances safety and efficiency well. Consequently, it is critical that vehicles in freeway-diverging regions develop a lane-changing driving strategy that strives to improve both the safety and efficiency of divergence areas. For CAV leaving the diverging area, this study suggested a full-time horizon optimum solution. Since it is a dynamic strategy, an MPC system based on rolling time horizon optimization was constructed as the primary algorithm of the strategy. A simulation experiment was created to verify the viability of the proposed methodology based on a mixed-flow environment. The results show that, in comparison with the feasible strategies exiting to off-ramp, the proposed strategy can take over 60% reduction in lost time traveling through a diverging area under the premise of safety and comfort without playing a negative impact on the surrounding traffic flow. Thus, the MPC system designed for the subject vehicle is capable of performing an optimal driving strategy in diverging areas within the full-time and space horizon.
更多
查看译文
关键词
connected and automated vehicle (CAV),freeway diverging area,mixed traffic flow,model prediction control (MPC),moving horizon optimization,optimal lane change driving strategy
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要