Journal of Transportation Systems Engineering and Information Technology

Journal of Transportation Systems Engineering and Information Technology ›› 2012, Vol. 12 ›› Issue (增1): 62-67.

• Intelligent system of urban road • Previous Articles     Next Articles

Probe Vehicle System Configuration Optimization Based on Traffic Information Coverage

WANG Xu-tao 1,YAO En-jian 1, QIU Feng-cui 1, LI Jian-jun 2   

  1. 1.MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China; 2.CENAVI Technologies Co., Ltd, Beijing 100028, China
  • Received:2011-12-16 Revised:2012-02-14 Online:2012-12-28 Published:2012-06-06

基于交通信息路网覆盖率的浮动车配置优化研究

王许涛1，姚恩建*1，邱奉翠1,李建军2   

  1. 1．北京交通大学 城市交通复杂系统理论与技术教育部重点实验室，北京 100044；2．北京世纪高通科技有限公司，北京 100028
  • 作者简介:王许涛（1987-），男，山东青岛人，硕士生.
  • 基金资助:

    北京交通大学科技基金 （T10J00020）.

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Abstract: From traffic information coverage perspective, the configuration optimization of probe vehicle system is explored.First, the coverage status is analyzed based on the reviewing of existing studies.Then, a coverage model and the optimization model of the number of probe vehicle is developed considering the minimum coverage requirement, the coverage marginal contribution rate of the number of vehicles and other restrictions.Finally, the model is used to optimize the probe vehicle system of Shenyang city of China.The result shows that the model works with high reliability and portability, which leads to a prediction accuracy of 96.1%.The optimization guarantees the lowest cost and the basic requirement of the traffic information coverage, which is of great reference value for the configuration of probe vehicle system.

Key words: intelligent transportation, probe vehicle system, road network coverage, number of probe vehicles, configuration optimization

摘要： 本文从交通信息路网覆盖率角度出发，对浮动车系统进行配置优化研究.在回顾国内外相关研究的基础上对覆盖率现状进行分析，建立浮动车系统交通信息路网覆盖率模型；考虑最低覆盖率要求和车辆数对覆盖率的边际贡献率等限制条件下，建立浮动车数量优化模型；最后运用此模型对沈阳市浮动车配置进行优化分析.结果表明，覆盖率预测结果精度达96.1%，模型具有较高的可靠性和推广性.浮动车数量的优化结果在满足交通信息所需覆盖率的同时，也保证了浮动车系统运营费用的影响，对于浮动车系统配置具有重要参考价值.

关键词: 智能交通, 浮动车系统, 路网覆盖率, 浮动车数量, 系统配置优化

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