基于分级多目标决策的干线公交速度引导模型

交通运输系统工程与信息 ›› 2021, Vol. 21 ›› Issue (2): 145-150.

基于分级多目标决策的干线公交速度引导模型

尚春琳¹，刘小明^*1，田玉林¹，董路熙¹，唐少虎²

1. 北方工业大学，城市道路智能交通控制技术北京市重点实验室，北京 100144； 2. 北京联合大学，城市轨道交通与物流学院，北京 100101

收稿日期:2020-11-28 修回日期:2020-12-29 出版日期:2021-04-25 发布日期:2021-04-25
作者简介:尚春琳(1989- )，男，山东日照人，博士生。
基金资助:
国家重点研发计划/National Key Research and Development Program of China(2018YFB1601003)；北京市自然科学基金/ Natural Science Foundation of Beijing, China(8172018)；北京市教委科技计划项目/ Scientific Research Project of Beijing Educational Committee(KM202111417003)。

Hierarchical Multi-objective Model for Arterial Dedicated Bus Speed Optimization

SHANG Chun-lin¹ , LIU Xiao-ming^*1 , TIAN Yu-lin¹ , DONG Lu-xi¹ , TANG Shao-hu²

1. Beijing Key Lab of Urban Road Traffic Intelligent Technology, North China University of Technology, Beijing 100144, China; 2. College of Urban Rail Transit and Logistics, Beijing Union University, Beijing 100101, China

Received:2020-11-28 Revised:2020-12-29 Online:2021-04-25 Published:2021-04-25

摘要/Abstract

摘要：

为解决干线公交速度引导存在多要素关联约束强，全局效果差的问题，本文提出基于分级多目标决策的干线公交速度引导模型。基于公交线路运行特性的全局优化指标优势分析，设计以公交线路综合准点率为主，交叉口停车次数和分段引导速度均衡为辅的线路全局优化目标体系，并考虑多目标间的关联约束和优先控制差异，构建基于拉格朗日乘子法和遗传算法分层组合的干线公交速度引导分级多目标递阶决策模型；最后，通过实际场景测试，验证模型的有效性。测试结果表明：模型能够克服非全局指标优化的局部最优问题，将全线路各班次综合准点率和交叉口停车次数由非全局指标的69.67%和2.37次 ⋅ 班-1 提升到90.53%和1.23次 ⋅ 班-1；并且综合准点率比全局多目标加权方法提升8.65%，能够较好保障综合准点率目标的优先性，有效提升干线公交的通行效率和服务可靠性。

关键词: 智能交通, 专用道公交优先, 分级多目标优化, 速度引导, 拉格朗日乘子法

Abstract:

In order to solve the problems of strong multi-factor linkage constraints and poor overall effect in arterial bus speed guidance, this paper proposes a hierarchical multi-objective speed guidance optimization model. A multiobjective optimization framework is designed to maximize the punctuality rate as the first-priority objective while the number of stops at intersections and the consistency of speed taking as the secondary objectives. With the associated constraints and priority among the multiple objectives, a hierarchical multi- objective decision- making approach is constructed by a combination of the Lagrangian multiplier method and genetic algorithm. Finally, an experiment based on actual scenarios is adopted to verify the effectiveness of the proposed model. The experiment results show that the model can guarantee the improvement of multiple performance indexes. It increases the overall punctuality rate from 69.67% to 90.53% and decreases the number of stops at intersections from 2.37 to 1.23 for each bus. Compared with the non-hierarchical multi-objective optimization method, the overall punctuality rate is improved by 8.65% in this hierarchical optimization method. The hierarchical optimization method provides the priority of the overall punctuality rate, and effectively improve the traffic efficiency and service reliability of dedicated buses.

Key words: intelligent transportation, dedicated bus priority, hierarchical multi-objective optimization, speed guidance, Lagrange multiplier method

中图分类号:

U491

尚春琳，刘小明，田玉林，董路熙，唐少虎. 基于分级多目标决策的干线公交速度引导模型[J]. 交通运输系统工程与信息, 2021, 21(2): 145-150.

SHANG Chun-lin, LIU Xiao-ming,TIAN Yu-lin, DONG Lu-xi, TANG Shao-hu. Hierarchical Multi-objective Model for Arterial Dedicated Bus Speed Optimization[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(2): 145-150.

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链接本文: http://www.tseit.org.cn/CN/abstract/abstract30222.shtml

http://www.tseit.org.cn/CN/Y2021/V21/I2/145

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