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作 者:陈润禾 王辛岩[1] CHEN Runhe;WANG Xinyan*(College of Engineering,Tibet University,Lhasa 850000,China)
出 处:《汽车实用技术》2024年第21期63-68,121,共7页Automobile Applied Technology
基 金:大学生创新创业训练项目基于路口态势感知对应急车辆优先通行的系统设计(2024XCX014)。
摘 要:随着经济社会发展,城市交通饱和现象引起道路堵塞情况日益增多,阻碍应急车辆通行。为提高应急车辆通行效率,以拉萨市为案例地,在YOLOX算法和DeepSORT算法的基础上,对现有的信号控制系统进行辅助优化,构建车辆统计监测系统架构。再以预计到达时间(ETA)算法计算并预估到达时间,实现应急车辆与交通信号灯智能联网联控。最终建立多目标交通信号配时数学模型,通过降低应急车辆行驶路径上的道路饱和度,从而使应急车辆能够快速行驶。实例表明在交通流量高峰时段,使用系统后可以使应急车辆平均延误降低41.28%。该系统为城市的交通流量优化、治理水平提高提供新思路,为城市交通智能化的发展提供动力。With the development of economy and society,road congestion caused by urban traffic saturation is increasing,which hinders the passage of emergency vehicles.In order to improve the efficiency of emergency vehicle traffic,taking Lhasa as a case,the existing signal control system is assisted and optimized on the basis of YOLOX algorithm and DeepSORT algorithm,and the vehicle statistical monitoring system architecture is constructed.Then the estimated time to arrival(ETA)algorithm is used to calculate and estimate the arrival time,so as to realize the intelligent networking control of emergency vehicles and traffic lights.Finally,a mathematical model of multi-objective traffic signal timing is established.By reducing the road saturation on the driving path of emergency vehicles,other vehicles in front of the vehicle have space to make way for emergency vehicles,so that emergency vehicles can drive at high speed.The results show that during the peak period of traffic flow,the average delay of vehicles can be reduced by 33.9%and the traffic capacity of vehicles can be increased by 42.9%after using the system.The system provides new ideas for the optimization of urban traffic flow and the improvement of governance level,and provides impetus for the development of urban traffic intelligence.
关 键 词:应急车辆 YOLOX算法 DeepSORT算法 车辆统计监测系统 ETA算法
分 类 号:U492.7[交通运输工程—交通运输规划与管理]
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