隔离交叉口带可逆车道的两阶段稳健优化交通信号控制

IF 2.3 4区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IET Intelligent Transport Systems Pub Date : 2023-12-14 DOI:10.1049/itr2.12465
Zhiyuan Sun, Zhicheng Wang, Xin Qi, Duo Wang, Yue Li, Huapu Lu
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引用次数: 0

摘要

交通信号控制(TSC)与可逆车道(RL)的综合设计因其充分利用时空交通设施的优势,成为解决孤立交叉口不确定性潮汐拥堵问题的有效方法。考虑到动态 TSC 方案与固定 RL 方案在一个时期内的矛盾,针对历史和实时不确定交通流的孤立交叉口,提出了一种基于改进的平均标准偏差(MSD)模型的两阶段优化方法。在第一阶段,应用多天的同周期历史数据,提出基于 MSD 模型(MSD-RTR 模型)的带可逆车道的鲁棒最优交通信号控制模型,从而得到固定 RL 方案和兼容的初始 TSC 方案。设计了一种双层嵌套遗传算法(DN-GA)来求解该模型。第二阶段,应用实时时段数据和多日同时段历史数据,提出基于 MSD 模型的鲁棒最优动态交通信号控制模型(MSD-RDT 模型),得到动态 TSC 方案。为了提高模型的稳定性,提出了 MSD-RDT 模型中反映历史时段和实时时段不同权重的三种模式,并设计了多模式遗传算法(MM-GA)。最后,介绍了一个案例研究,以证明所提模型和算法的效率和适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A two-stage robust optimal traffic signal control with reversible lane for isolated intersections

The integrated design of traffic signal control (TSC) and reversible lane (RL) is an effective way to solve the problem of tidal congestion with uncertainty at isolated intersections, because of its advantage in making full use of temporal-spatial transportation facilities. Considering the contradiction between the dynamic TSC scheme and the fixed RL scheme in one period, a two-stage optimization method based on improved mean-standard deviation (MSD) model for isolated intersections with historical and real-time uncertain traffic flow is proposed. In the first stage, applying the same-period historical data of multiple days, a robust optimal traffic signal control model with reversible lane based on MSD model (MSD-RTR model) is put forward to obtain the fixed RL scheme and the compatible initial TSC scheme. A double-layer nested genetic algorithm (DN-GA) is designed to solve this model. In the second stage, applying real-time period data and multi-day same-period historical data, a robust optimal dynamic traffic signal control model based on MSD model (MSD-RDT model) is put forward to obtain the dynamic TSC scheme. Three modes which reflect the different weights of historical period and real-time period in this MSD-RDT model are presented to improve the model stability, and a multi-mode genetic algorithm (MM-GA) is designed. Finally, a case study is presented to demonstrate the efficiency and applicability of the proposed models and algorithms.

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来源期刊
IET Intelligent Transport Systems
IET Intelligent Transport Systems 工程技术-运输科技
CiteScore
6.50
自引率
7.40%
发文量
159
审稿时长
3 months
期刊介绍: IET Intelligent Transport Systems is an interdisciplinary journal devoted to research into the practical applications of ITS and infrastructures. The scope of the journal includes the following: Sustainable traffic solutions Deployments with enabling technologies Pervasive monitoring Applications; demonstrations and evaluation Economic and behavioural analyses of ITS services and scenario Data Integration and analytics Information collection and processing; image processing applications in ITS ITS aspects of electric vehicles Autonomous vehicles; connected vehicle systems; In-vehicle ITS, safety and vulnerable road user aspects Mobility as a service systems Traffic management and control Public transport systems technologies Fleet and public transport logistics Emergency and incident management Demand management and electronic payment systems Traffic related air pollution management Policy and institutional issues Interoperability, standards and architectures Funding scenarios Enforcement Human machine interaction Education, training and outreach Current Special Issue Call for papers: Intelligent Transportation Systems in Smart Cities for Sustainable Environment - https://digital-library.theiet.org/files/IET_ITS_CFP_ITSSCSE.pdf Sustainably Intelligent Mobility (SIM) - https://digital-library.theiet.org/files/IET_ITS_CFP_SIM.pdf Traffic Theory and Modelling in the Era of Artificial Intelligence and Big Data (in collaboration with World Congress for Transport Research, WCTR 2019) - https://digital-library.theiet.org/files/IET_ITS_CFP_WCTR.pdf
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