深圳大学学报（理工版）2024，Vol.41Issue(4)：423-432,10.DOI:10.3724/SP.J.1249.2024.04423
基于改进Markov智能网联多车型混合流编队策略
Formation strategies of mixed flow with connected and automated multi-type vehicles based on an improved Markov chain model
摘要
Abstract
To enhance the roadway capacity of mixed traffic flow with connected and automated(CA)trucks and cars as well as manually driven trucks and cars,we propose strategies for individual and cooperative vehicle formations for CA vehicles based on platooning intensity and permeability.Two vehicle following modes of mixed-flow are designed for each strategy,respectively.The vehicle state transfer probabilities are derived using an improved Markov chain model,where CA vehicles permeability and platooning intensity are considered.Then,platooning distributions of two strategies are discussed and road capacity models for mixed traffic flow are established.The effectiveness of these strategies is validated through theoretical proofs and simulation experiments.Results show that compared to no-formation strategies,both individual and cooperative formation strategies can increase road capacity by 1.23% to 49.62% and 1.47% to 60.34%,respectively.The cooperative formation strategy further enhances road capacity by an additional 11% compared to the individual formation strategy.When CA vehicle permeability is larger than 50% and platooning intensity is above zero,road capacity can be significantly enhanced with the increasement(13.27%～60.34% )of the maximum platooning size.Under the individual formation strategy,maximum platooning sizes are 8 vehicles for CA cars and 6 vehicles for CA trucks,while under the cooperative formation strategy,the maximum platooning size for CA vehicles reaches 8.关键词
智能交通/智能网联混合交通流/编队策略/改进马尔科夫链模型/排强度/最大队列规模Key words
intelligent transportation/mixed traffic flow of connected and automated/formation strategy/improved Markov chain model/platooning intensity/maximum platooning size分类
交通工程引用本文复制引用
赵峥,庞明宝..基于改进Markov智能网联多车型混合流编队策略[J].深圳大学学报（理工版）,2024,41(4):423-432,10.基金项目
National Natural Science Foundation of China(50478088) （50478088）
Science and Technology Project of Hebei Education Department(ZD2021028) 国家自然科学基金资助项目(50478088) （ZD2021028）
河北省高等学校科学技术研究资助项目(ZD2021028) （ZD2021028）
