信号交叉口智能网联车车队速度引导策略研究

doi:10.3969/j.issn.1674-0696.2021.02.08

摘要/Abstract

摘要： 为降低交叉口车辆油耗，提高交叉口通行效率，以智能网联车车队作为引导对象，提出固定引导时长的车队车速引导策略。考虑车队初始速度和车队内车辆数的随机性，采用蒙特卡洛仿真获取单车平均油耗和平均行程时间。通过构建路段综合出行费用，对固定引导距离和固定引导时长两种策略进行了比较。研究结果表明：固定引导距离策略中，引导距离为350 m时综合出行费用最低；固定引导时间策略中，引导时间为6 s时综合出行费用最低；两种最优方案相比，后者油耗比前者低16.3%，后者行程时间比前者低7.2%，路段综合出行费用后者比前者低了10.2%；固定引导时长的车队车速引导策略可有效减少交叉口的车辆延误和燃油消耗。

关键词: 交通运输工程, 智能网联车, 车速引导, 车辆队列, 蒙特卡洛仿真, 出行费用

Abstract: In order to reduce the fuel consumption of vehicles and improve traffic efficiency at intersections, the speed guidance strategy with fixed guidance time was proposed by taking the intelligent connected vehicle platoon as the guidance object. Considering the randomness of the initial speed and the number of vehicles in the platoon, Monte Carlo simulation was used to obtain the average fuel consumption and average travel time of a single vehicle. By constructing the comprehensive travel cost of the road section, two strategies of fixed guiding distance and fixed guiding time were compared. The research results show that: in the fixed guiding distance strategy, the comprehensive travel cost is the lowest when the guiding distance is 350 m; in the fixed guiding time strategy, the comprehensive travel cost is the lowest when the guiding time is 6 s. Compared with the two optimal schemes, the fuel consumption of the latter is 16.3% lower than that of the former, the travel time of the latter is 7.2% lower than that of the former, and the comprehensive travel cost of the latter is 10.2% lower than that of the former. The vehicle speed guidance strategy with fixed guidance time can effectively reduce vehicle delay at intersection and reduce fuel consumption.

Key words: traffic and transportation engineering, intelligent connected vehicle, speed guidance, vehicle platoon, Monte Carlo simulation, travel cost

中图分类号:

U491.54

石琴，陈沪江，陈一锴. 信号交叉口智能网联车车队速度引导策略研究[J]. 重庆交通大学学报（自然科学版）, 2021, 40(02): 47-53.

SHI Qin, CHEN Hujiang, CHEN Yikai. Speed Guidance Strategy of Intelligent Connected Vehicle Platoon at Signalized Intersection[J]. Journal of Chongqing Jiaotong University(Natural Science), 2021, 40(02): 47-53.

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