基于SWARM优化算法的山地城市干线协调管控优化方法
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重庆交通大学

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Coordinated Management and Control Optimization Method of Mountain City Trunk Line Based on SWARM Algorithm
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    摘要:

    山地城市干线承担城市主要交通出行量,具有交通流特性差异大,交通分布不均衡等特点,对交通管控提出了新要求,为提升城市干线交通效率,本文以山地城市干线系统为研究对象,基于SWARM算法,建立山地城市干线协调管控优化方法。在协调控制层面,建立基于子区延误最小的拥堵源头追溯协调控制方法;在单点控制层面,建立基于分层递阶反馈优化控制,最终结合协调层面和单点层面的调节率生成协调控制方案。实例验证显示:针对干线多车道汇入系统,SWARM优化算法场景相对于无管控场景平均延误和平均停车次数分别降低了22.06%,28.42%;相对于现行管控方案场景,干线多车道汇入系统的平均延误,平均停车次数和平均旅行时间分别降低了23.04%,24.08%,19.38%。研究表明,SWARM优化算法对山地城市干线多车道汇入系统的管控效果良好。

    Abstract:

    Mountain city trunk line undertakes the main traffic volume of the city, which has the characteristics of large differences in traffic flow characteristics and uneven traffic distribution, which puts forward new requirements for traffic control. In order to improve the traffic efficiency of urban trunk line, this paper takes the mountain city trunk line system as the research object and establishes the optimization method of coordinated control of mountain city trunk line based on swarm algorithm. At the level of coordinated control, a coordinated control method for tracing the source of congestion based on the minimum delay in the sub area is established; At the single point control level, the optimal control based on hierarchical feedback is established, and finally the coordinated control scheme is generated by combining the regulation rate at the coordination level and the single point level. The example verification shows that for the trunk multi Lane merging system, the average delay and average parking times of swarm optimization algorithm scene are reduced by 22.06% and 28.42% respectively compared with the uncontrolled scene; Compared with the current control scheme scenario, the average delay, average parking times and average travel time of trunk multi Lane merging system have been reduced by 23.04%, 24.08% and 19.38% respectively. It can be proved that the swarm optimization algorithm has a good control effect on the multi Lane merging system of trunk lines in mountainous cities.

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  • 收稿日期:2022-03-01
  • 最后修改日期:2022-03-30
  • 录用日期:2022-03-31
  • 在线发布日期: 2022-11-04
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