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双向双车道超车行为的智能车队间隙控制优化
引用本文:陈俊杰,蔡伯根,上官伟,王剑,柴琳果.双向双车道超车行为的智能车队间隙控制优化[J].交通运输工程学报,2019,19(2):178-190.
作者姓名:陈俊杰  蔡伯根  上官伟  王剑  柴琳果
作者单位:北京交通大学电子信息工程学院,北京100044;北京交通大学北京市轨道交通电磁兼容与卫星导航工程技术研究中心,北京 100044;北京交通大学电子信息工程学院,北京100044;北京交通大学北京市轨道交通电磁兼容与卫星导航工程技术研究中心,北京 100044;北京交通大学轨道交通控制与安全国家重点实验室,北京 100044
基金项目:国家重点研发计划项目2018YFB1600600中央高校基本科研业务费专项资金项目2018YJS019国家自然科学基金项目61773049国家自然科学基金项目61490705
摘    要:建立了双向双车道环境下单车超越车队模型, 分析了影响双向双车道超车危险区域范围的主要因素; 设计了分步式单车超越车队算法, 研究了安全间隙前后车速度、超车车辆入队速度与车队安全间隙范围四者之间的关系, 提出了车辆入队所需最小安全间隙的速度匹配方案; 建立了单车超越车队算法的目标函数, 设定最大允许超车时间内超车车辆与车队行驶距离最大, 超车车辆超越车队车辆数最多, 前、后车形成安全间隙过程中加速度、减速度最小; 提出了基于改进粒子群的分级约束多目标优化方法, 为单车超越车队算法中的三级车速引导提供了优化的速度引导方案。研究结果表明: 双向双车道环境下超车危险区域范围与车队车辆数及对向车辆行驶速度成正相关关系; 改进的粒子群优化算法相比传统算法具有更强的鲁棒性和更快的收敛速度, 平均收敛时间缩短39.2%;在分步式单车超越车队过程中, 车队车辆平均速度提升9.04%, 即在车队间隙生成过程中, 虽然部分车辆速度减小, 但车队整体平均速度得到提升; 超车车辆平均速度提升16.8%, 即在超车过程中, 不仅超车车辆的安全性得到保证, 其运行效率也得到提升。 

关 键 词:交通信息工程  双向双车道  智能车队  单车超越车队算法  安全间隙  间隙优化  分步式超车
收稿时间:2018-11-03

Slot control optimization of intelligent platoon for dual-lane two-way overtaking behavior
CHEN Jun-jie,CAI Bo-gen,SHANGGUAN Wei,WANG Jian,CHAI Lin-guo.Slot control optimization of intelligent platoon for dual-lane two-way overtaking behavior[J].Journal of Traffic and Transportation Engineering,2019,19(2):178-190.
Authors:CHEN Jun-jie  CAI Bo-gen  SHANGGUAN Wei  WANG Jian  CHAI Lin-guo
Institution:1.School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044, China2.Beijing Engineering Research Center of EMC and GNSS Technology for Rail Transportation, Beijing Jiaotong University, Beijing 100044, China3.State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China
Abstract:A model of single vehicle overtaking a platoon on the dual-lane two-way road was established, and the key factors affecting the range of dangerous overtaking zone were analyzed. The step-by-step algorithm was designed when single vehicle overtakes the platoon. The relationship among the speeds of the vehicles before and after the safety slot, the speed of the overtaking vehicle entering the platoon and the safety slot range of the platoon was studied. The speed matching scheme with the minimum safety slot required for the vehicle to overtake the platoon was proposed. The objective function of the algorithm was established, and the following assumptions were made in the maximum allowable overtaking time: the overtaking vehicle and platoon travelled the longest distance, the overtaking vehicle overtaked the platoon by the most vehicles, and the acceleration and deceleration of front and rear vehicles were the minimum in the forming process of safety slot. The hierarchical constrained multi-objective optimization method based on the improved particle swarm was proposed to provide the algorithm with the optimized three-level speed guidance strategy. Analysis result shows that the overtaking dangerous zone on dual-lane two-way road is positively correlated with the number of vehicles in the platoon and the velocities of the opposite vehicles. The improved particle swarm optimization algorithm has stronger robustness and faster convergence than the traditional algorithm, and the average convergence time reduces by 39.2%. In the step-by-step process that the single vehicle overtakes the platoon, the average speed of the vehicles in the platoon increase by 9.04%, which means that in the forming process of safety slot, although the speeds of some vehicles decrease, the overall average speed of the platoon increases. The average speed of overtaking vehicle increases by 16.8%, which means that in the overtaking process, not only is the safety of overtaking vehicle guaranteed, but also its operating efficiency is improved. 
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