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A junction-by-junction feedback-based strategy with convergence analysis for dynamic traffic assignment

基于结点反馈策略的动态交通分配收敛性分析

  • Research Paper
  • Special Focus on Distributed Control of Nonlinear Multi-Agent Systems and Applications
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Abstract

By considering the traffic assignment problem as a control problem, this paper develops a new realtime route guidance strategy for accurate convergence of the traffic flows to user equilibrium (UE) or system optimum (SO), in the presence of drivers’ response uncertainties. With the new guidance strategy, the drivers make routing decisions based on the route guidance information from junction to junction. Specifically, instead of total travel cost of every route from origin to destination, the travel cost of every alternative link plus the average cost to destination from the next junction corresponding to the alternative link is sent to the drivers at each specific junction. The drivers’ response to the route guidance information is directly modeled by the splitting rates at the junctions, which are simply negatively correlated with the comparison of related cost information and are able to take into account the drivers’ response uncertainties. With the proposed route guidance strategy, in the case of fixed travel demands, the accurate convergence of the traffic flows to a UE is guaranteed in the presence of drivers’ response uncertainties by using LaSalle’s invariance principle. When marginal travel cost information, instead of travel cost information, is sent to the drivers, a system optimum can be achieved under a mild condition on the marginal cost function.

创新点

本文提出了一个新的基于结点动态交通分配策略的轻松驾驶响应模型。具体地,驾驶员对路径引导信息的响应是直接有结点的分裂率表示的,它与相关成本信息进行比较,满足简单的负相关性。文中提到的动态交通分配策略,利用 LaSalle 不变性原理保证了交通流量趋于一个用户平衡。当边际出行成本信息用来代替出行成本信息时,目标函数在温和的条件下可以获得系统优化。

在实际的系统中,信息传输和驾驶员的响应造成的时间延迟引起是不能被忽略。未来工作将研究在何种程度上的时间延迟的影响是可以被减弱的。其他问题,如交通信息不准确也是有趣研究方向。在我们最近的论文中,我们研究了在出行需求的时变是在一定限制范围内变化的情况,且得到了鲁棒收敛性的结果。对于时变的出行需求应用本文的提到的策略时,其鲁棒性的研究是一件很有意义的时。未来的工作将会把更多的非线性控制方法应用到此问题中。

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Authors and Affiliations

  1. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, 110819, China

    Tengfei Liu & Zhong-Ping Jiang

  2. Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT, 06269, USA

    Xuesong Lu

  3. Department of Electrical and Computer Engineering, Polytechnic School of Engineering, New York University, Brooklyn, NY, 11201, USA

    Zhong-Ping Jiang

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  1. Tengfei Liu
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  2. Xuesong Lu
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  3. Zhong-Ping Jiang
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Correspondence to Tengfei Liu, Xuesong Lu or Zhong-Ping Jiang.

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Liu, T., Lu, X. & Jiang, ZP. A junction-by-junction feedback-based strategy with convergence analysis for dynamic traffic assignment. Sci. China Inf. Sci. 59, 1–17 (2016). https://doi.org/10.1007/s11432-015-5444-1

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