基于CTM模型的入口匝道模型预测控制
Model predictive control of expressway on-ramp based on cell transmission model
杨雪驰 1孔文翔1
作者信息
- 1. 上海理工大学 光电信息与计算机工程学院,上海 200093
- 折叠
摘要
入口匝道车流的无序汇入会影响快速路主线车辆的正常行驶,造成交通拥堵甚至交通事故.为了使城市快速路交通流保持稳定有序,提出一种基于元胞传输模型(Cell Transmission Model,CTM)的入口匝道模型预测控制方法.最优控制模型采用CTM交通流模型作为过程模型,综合考虑通行效率、匝道队列和控制信号波动构建目标函数,使用粒子群优化算法(Particle Swarm Optimization,PSO)求解.仿真结果表明,相比于无控制算法,提出的匝道模型预测控制方法可以有效缓解交通拥堵、减少通行时间,使快速路系统取得良好的交通表现.
Abstract
The disordered merging of on-ramp traffic will affect the normal running of the expressway mainstream,resulting in traffic congestion or even traffic accidents.In order to keep the traffic flow of urban expressway stable and orderly,a predictive control method based on Cell Transmission Model(CTM)was proposed.CTM traffic flow model was adopted as the process model,and the objective function was constructed by considering traffic efficiency,ramp queue and control signal fluctuation.Particle Swarm Optimization(PSO)was used to solve the problem.The simulation results showed that,compared with no-control scenario,the proposed on-ramp model predictive control method could effectively relieve congestion and reduce travel time,so that the expressway system could achieve good traffic performance.
关键词
城市快速路/匝道控制/交通流模型/模型预测控制/粒子群算法Key words
urban expressway/ramp metering/traffic flow model/model predictive control/particle swarm optimization引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
维普
万方数据