摘要
有效表征复杂网联环境中各类交通风险,可以显著降低交通风险,提高道路通行能力。针对目前交通风险指标涉及风险因素较少,对环境信息表征不够全面,使用参数较为单一的不足,通过总结各类场源的物理规律与数学特征,构建了复杂风险势场模型。通过对各类风险势场去矢量化,构建了可叠加的复杂风险势场指标。并基于该指标构建一套智能可控的辅助控制策略。为了验证上述指标和策略的有效性,基于数值仿真方法,构建了交通事故发生后的车辆减速停止与换道避让两类实验场景。实验结果表明,复杂风险势场指标可以有效表征交通风险高低和变化情况。同时也证明了该辅助控制策略可以有效规避事故的发生,降低交通风险,提高道路通行能力。
The effective representation of various traffic risks in a complex connected vehivles environment can significantly reduce traffic risks and enhance road capacity.Addressing the limitations of existing traffic risk indica-tors,such as limited factors,incomplete representation of environmental information,and the use of single parameters,this paper constructs a mutiple risk potential field model by summarizing the physical laws and mathematical charac-teristics of various sources.By devectorizing various risk potential fields,a superimposable Multiple Risk Potential-field-based Indicator(MRPI)is established.Based on MRPI,an intelligent controllable MRPI-based Auxiliary Con-trol Strategy(MACS)is developed.To validate the effectiveness of MRPI and MACS,numerical simulation methods are employed to create two experimental scenarios:vehicle deceleration and stoppage after a traffic accident,and a-voidance by lane-changing.The experimental results demonstrate that the complex risk potential field index can effec-tively characterize the level and changes of traffic risks.At the same time,it also proves that this auxiliary control strategy can effectively avoid the occurrence of accidents,reduce traffic risks,and improve road capacity.
作者
尹嘉诚
曹鹏
李林恒
崔舜来
YIN Jia-cheng;CAO Peng;LI Lin-heng;CUI Shun-lai(School of Transportation and Logistics,Southwest Jiaotong University,Chengdu Sichuan 610031,China;National United Engineering Laboratory of Integrated and Intelligent Transportation,Southwest Jiaotong University,Chengdu Sichuan 610031,China;Yibin Research Institute,Southwest Jiaotong University,Yibin Sichuan 644000,China;School of Transportation,Southeast University,Nanjing Jiangsu 211189,China)
出处
《计算机仿真》
2025年第9期233-238,536,共7页
Computer Simulation
基金
四川省自然科学基金(2022NSFSC0476,2022NSFSC1889)。
关键词
交通工程
交通风险指标
势场理论
风险表征
复杂网联环境
Traffic engineering
Traffic risk indicators
Potential field theory
Risk characterization
Complex con-nected vehicles environment
