项目名称: 智能车路协同环境下快速路动态通行能力建模与优化控制
项目编号: No.61273238
项目类型: 面上项目
立项/批准年度: 2013
项目学科: 自动化技术、计算机技术
项目作者: 胡坚明
作者单位: 清华大学
项目金额: 78万元
中文摘要: 城市快速路以其通行效率高、通行能力大成为各主要城市的交通命脉,但同时也是各类交通事件的常发区域,一直是国内外智能交通研究的热点。本项目以智能车路协同条件下城市快速路动态通行能力提升为应用背景,从快速路交通信息采集与交通事件检测方法、交通事件演化分析及快速路动态通行能力建模、快速路动态通行能力提升优化控制以及仿真验证等四个方面开展研究工作。重点突破车路协同条件下全时空交通信息获取、交通事件演化趋势预测、动态通行能力建模、快速路动态通行能力提升优化控制等关键问题。本项目是信息科学、系统优化与智能交通领域结合的研究项目,成果将直接面向新一代智能交通系统的运行管理与实际应用,提升快速路服务水平,具有重要的工程应用价值。同时在交通事件与动态通行能力的作用机理分析及其建模、网络交通状态时空演化,以及快速路优化控制策略等方面的研究成果也将丰富智能交通的基本理论和研究方法,具有重要的科学意义和 学术价值。
中文关键词: 动态通行能力;交通状态感知;可变限速控制;智能车路协同系统;主动交通管理
英文摘要: Owing to its high efficiency and large capacity, freeway system has become the transportation lifeline in major cities. At the same time, however, it is also the region of various types of traffic incidents due to the tremendous traffic flows, especially in rush hours. Therefore, freeway system has always attracted great attentions for both the urban traffic administrators and researchers all over the world for many years. This application is aiming at improving the dynamic capacity of urban freeway system under the circumstances of Intelligent Vehicle and Infrastructure Cooperation System (IVICS), a so-called new generation of intelligent transportation systems. It will mainly focus on four aspects, i.e., traffic information collection and traffic incident detection method, the evolution analysis of traffic incident and the modeling of dynamic capacity, optimization and control strategy for the promotion of dynamic capacity, and simulation research. We will emphasize to deal with such key issues as full spatial-temporal traffic information acquisition under IVICS, evolution trend prediction for traffic incidents, modeling of dynamic capacity, and control strategies. This project is a combination of information science, systems engineering and intelligent transportation systems. The research results are supposed
英文关键词: Dynamic capacity;Traffic state perception;Variable speed limit control;Intelligent vehicle infrastructure cooperative sys;Active traffic management