摘要
在网联与非网联车混行交通流条件下,针对冰雪条件下信号交叉口通行能力下降的问题,从冰雪条件对交通参数的影响和网联人工驾驶车辆实时传输交通信息的特性入手,分析不同冰雪条件下交通流的变化,通过研究网联自动驾驶汽车与人工驾驶汽车驾驶特性区别,以及冰雪条件对人车和道路的影响,推断头车启动时间、期望车头时距、平均行驶速度等交通参数,采用停车线延误计算方法对其进行修正。再得到修正后的停车线延误模型,以最短延误为目标计算最佳周期,利用MATLAB对其求解,依据网联车实时传输的交通信息调整信号配时方案,通过VISSIM软件进行仿真。最后得到的配时方案和原方案相比,延误时间缩短了16.6%,行程时间减少14.63%,平均停车次数也明显减少,模型配时方案更符合当前道路状况,对提高信号交叉口车流速度,减少交叉口冲突有显著的效果,适用于冰雪条件下的信号交叉口信号配时。
In order to solve the problem that the capacity of intersection under the mixed traffic flow of intelligent connected vehicles and human-driven vehicles decreases because of the ice-snow environments,this paper starts with the influence of ice-snow environments on traffic parameters and the characteristics of real-time transmission of traffic information of mixed traffic flow and analyzes the changes of traffic flow under different ice-snow environments.The starting time,expected headway,average speed and other traffic parameters are deduced from the differences of driving characteristics between intelligent connected vehicles and human-driven vehicles and the influence of snow-ice environments,and the stop-line delay calculation method is used to correct them.Then,the modified stop-line delay model is obtained,and the optimal cycle is calculated by the software MATLAB with the shortest delay as the goal.The signal optimization is adjusted according to the traffic information transmitted by the intelligent connected vehicles in real time.VISSIM software is used for simulation.Finally,compared with the original scheme,the delay time is shortened by 16.6%,the travel time is reduced by 14.63%,and the average number of stops is also significantly reduced.The new timing scheme is more in line with the current road conditions,which has more obvious effect on improving the traffic flow speed of signalized intersection and reducing the intersection conflict.Therefore,it is more suitable for signalized intersection signal optimization under ice-snow environments.
作者
米日扎提·艾克拜尔
王琪
李兴佳
魏遥
潘玉叶
陈绍元
Mirizhati·Aikebaier;WANG Qi;LI Xing-jia;WEI Yao;PAN Yu-ye;CHEN Shao-yuan(School of Transportation,Jilin University,Changchun,Jilin 130000,China)
出处
《黑龙江交通科技》
2023年第12期119-125,共7页
Communications Science and Technology Heilongjiang
基金
吉林省教委科研基金(JJKH20221020KJ)。
关键词
交通信息工程
冰雪条件
网联车与非网联车混行
停车线延误模型
信号交叉口
配时优化
traffic information engineering
ice-snow environments
mixed traffic flow
stop-line delay model
signalized intersection
timing optimization
