摘要
提出一种基于视频检测技术的自适应信号灯配时算法,首先利用光流场法对视频中进入交叉口的车辆进行识别,并统计交叉路口每个进口各车道中在一个初始信号周期内的车辆数、车辆行驶速度以及加速度,根据视频检测数据重新计算信号周期及支路绿灯时间等信号配时参数,并计算最小绿灯时间,最终根据最小绿灯时间和支路绿灯时间选择新的信号周期。仿真结果表明,该方法可极大程度降低交叉口延误,缩短排队长度,提高运行效率。
An adaptive signal lamp timing algorithm based on video detection technology is proposed in this paper. Firstly,the optical flow field method is used to identify the vehicles entering the intersection in the video,and the number of vehicles,vehicle speed and acceleration in an initial signal cycle in each entrance lane of the intersection are counted. According to the video detection data,the signal timing parameters such as signal period and branch green light time are recalculated,and the minimum green light time is calculated. Finally,a new signal period is selected according to the minimum green light time and branch green light time. Simulation result the results show that this method can greatly reduce the delay of intersection,shorten the queue length and improve the operation efficiency.
作者
吴大伟
Wu Dawei(School of Traffic and Transportation,Northeast Forestry University,Harbin 150040,China)
出处
《山西建筑》
2020年第5期196-198,共3页
Shanxi Architecture
关键词
视频检测技术
光流场法
车流量
智能交通
video detection technology
optical flow field method
vehicle flow
intelligent transportation
