同济大学学报（自然科学版）2024，Vol.52Issue(12)：1909-1918,10.DOI:10.11908/j.issn.0253-374x.23360
城市生态道路混合交通流节能驾驶策略优化
Optimization of Energy-Saving Driving Strategy on Urban Ecological Road with Mixed Traffic Flows
摘要
Abstract
This paper addresses energy-efficient driving strategies for autonomous connected vehicles on ecological roads under mixed traffic flow conditions.A wildlife passage scenario,which significantly impacts energy-saving driving,is extracted,and an application framework for wildlife passages within the Internet of Vehicles(IoV)is developed.A driving model for vehicles on ecological roads under the IoV environment is also constructed,utilizing dynamic programming for discretized analysis and state division.An energy-efficient driving model for vehicles within mixed traffic flow is optimized and established.The Q-learning algorithm is applied to optimize and solve the energy-saving driving model for a single vehicle.Based on the ecological roads in Shanghai,a simulation scenario considering the risk of wildlife crossing is created to validate the energy-saving driving strategies in the IoV environment.The results show that the proposed energy-saving strategy can reduce vehicle fuel consumption by 6%to 11%.Additionally,the energy-saving effect improves with increasing traffic density of vehicles,verifying both the reasonableness of the model and the effectiveness of the algorithm.关键词
交通工程/生态道路/车联网/节能驾驶/强化学习Key words
traffic engineering/ecological roads/Internet of Vehicles/energy-saving driving/reinforcement learning分类
交通工程引用本文复制引用
曾小清,朱明昌,郭开易,王奕曾,冯栋梁..城市生态道路混合交通流节能驾驶策略优化[J].同济大学学报（自然科学版）,2024,52(12):1909-1918,10.基金项目
上海市科学技术委员会项目(22DZ1208505、19DZ1204200、20DZ1202900) （22DZ1208505、19DZ1204200、20DZ1202900）
