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Rule-based transit signal priority control method using a real-time transit travel time prediction model

机译:基于实时公交行程时间预测模型的基于规则的公交信号优先控制方法

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摘要

An advanced rule-based Transit Signal Priority (TSP) control method is presented in this paper. An on-line transit travel time prediction model is the key component of the proposed method, which enables the selection of the most appropriate TSP plans for the prevailing traffic and transit condition. The new method also adopts a priority plan re-development feature that enables modifying or even switching the already implemented priority plan to accommodate changes in the traffic conditions. The proposed method utilizes conventional green extension and red truncation strategies and also two new strategies including green truncation and queue clearance. The new method is evaluated against a typical active TSP strategy and also the base case scenario assuming no TSP control in microsimulation. The evaluation results indicate that the proposed method can produce significant benefits in reducing the bus delay time and improving the service regularity with negligible adverse impacts on the non-transit street traffic.
机译:本文提出了一种基于规则的高级公交信号优先控制方法。在线过境旅行时间预测模型是所提出方法的关键组成部分,该模型可以针对当前的交通和过境条件选择最合适的TSP计划。新方法还采用了优先计划重新开发功能,该功能可以修改甚至切换已经实施的优先计划,以适应交通状况的变化。所提出的方法利用了传统的绿色扩展和红色截断策略,以及两种新的策略,包括绿色截断和队列清除。针对典型的主动TSP策略以及假设微仿真中没有TSP控制的基本情况,对新方法进行了评估。评估结果表明,该方法在减少公交车的延误时间和改善服务规律性方面具有显着的效益,对非公交街道交通的不利影响可忽略不计。

著录项

  • 作者单位
  • 年度 2013
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
  • 中图分类
  • 入库时间 2022-08-20 20:48:19

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