交通运输系统工程与信息 ›› 2017, Vol. 17 ›› Issue (2): 60-67.

• 智能交通系统与信息技术 • 上一篇    下一篇

基于移动导航数据的信号配时反推

谭墍元1,尹凯莉1,李萌*2,郭伟伟1,王力1,黄怡斌1   

  1. 1. 北方工业大学城市道路交通智能控制技术北京市重点实验室,北京100144;2. 清华大学土木工程系,北京100084
  • 收稿日期:2016-09-23 修回日期:2016-12-03 出版日期:2017-04-25 发布日期:2017-04-25
  • 作者简介:谭墍元(1986-),男,河南许昌人,讲师.
  • 基金资助:

    北京市自然科学基金/Beijing Natural Science Foundation(4164083);国家自然科学基金/National Natural Science Foundation of China(61603005);科技成果转化-提升计划项目/Scientific and Technological Achievement–development Project (PXM2016_014212_000036).

Signal Timing Estimation Using Mobile Navigation Data

TAN Ji-yuan1, YIN Kai-li 1, LI Meng 2,GUOWei-wei 1,WANG Li1 , HUANG Yi-bin 1   

  1. 1. Beijing Key Lab of Urban Intelligent Traffic Control Technology, North China University of Technology, Beijing 100144, China; 2. The Department of Civil Engineering, Tsinghua University, Beijing 100084, China
  • Received:2016-09-23 Revised:2016-12-03 Online:2017-04-25 Published:2017-04-25

摘要:

在交通管理和评价时,信号配时对监测评价路口运行状态,评价路口配时方案至关重要.但是,大范围的实时信号配时方案的获取尚缺乏简明有效的途径.本文提出两种基于移动导航数据计算固定配时路口信号配时的方法.第一种方法是在不考虑驾驶员驾驶行为差异性时,得到路口红灯和车均延误的关系模型,从而计算某相位的红灯时长. 另外一种方法是基于车辆通过停止线的时间,结合本文提出的上升梯度法,得到某阶段红灯时长.本文通过实际的路口案例计算,将预测结果和已知路口的信号配时比较,表明此方法计算得到的红绿灯时长准确度较高,为后续进行路口运行状态和通行能力研究提供了数据支持.

关键词: 城市交通, 信号配时反推, 车辆行驶轨迹, 车均延误, 通过停止线时间, 移动导航数据

Abstract:

When manage and value the traffic network, signal parameters is important to monitor and evaluation the operating state and the junction intersection traffic capacity. However, a wide range of realtime signal timing scheme for a lack of clear and effective way. In this paper, we propose two methods based mobile navigation data to calculate the signal parameters. The first method is to establish the relationship between red and delay without considering the differences of the drivers’behavior, then calculate the red parameters. The another method is based the time when vehicle passing the stop line, then combined with the rising gradient method we proposed in this paper, obtain the min red of a stage. Through the actual case to calculate the red parameters, then compared to the known signal parameters. The result demonstrates the method we proposed in this paper has high accuracy, and provides the data support for the research of the traffic management.

Key words: urban traffic, signal parameters estimation, vehicle trajectory, delay, passing time, mobile navigation data

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