基于低频浮动车数据的交叉口域行程时间估计研究

项目名称： 基于低频浮动车数据的交叉口域行程时间估计研究

项目编号： No.61503006

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 自动化技术、计算机技术

项目作者： 王志建

作者单位： 北方工业大学

项目金额： 20万元

中文摘要： 行程时间估计是浮动车信息采集系统中的核心技术。本课题在低频浮动车数据源条件下研究浮动车路段行程时间估计问题的数学理论和方法，在分析凝练浮动车采样周期长、车辆行驶轨迹难判断等问题的基础上，分析低频采样浮动车车辆属性和定位数据特征，以概率统计理论和交通流理论为基础，揭示浮动车驾驶员在选择行驶路线时的影响因素和个人偏好，综合考虑路线距离、路线交叉口数量和信号控制延误时间等因素，建立最优路的层次分析模型并基于综合模糊评判算法判断车辆行驶路线；将浮动车路段行驶和交叉口行驶合理分离，重新划分GIS路网模型，建立路口行驶域的概念，在考虑交叉口延误条件下建立基于时空移动平均的路口域行程时间估计模型，并采用差值法计算求解，有效解决基于低频浮动车数据的交叉口域行程时间估计的难题。

中文关键词： 浮动车；低频采样；轨迹判断；信号控制；行程时间估计

英文摘要： Link travel time estimate for urban roads is the core technology of the GPS floating car information collection system. This study researches the mathematical theories and methods of the link travel time estimate under the condition of low-frequency floating car data sources. The study analyzed vehicle attributes and location data features of the low-frequency sampling floating car on the basis of analyzing the problems of floating car long-period sampling and vehicle trajectory judge. This paper also revealed the factors and personal preferences of floating car driver in the choice of travel routes based on probability theory and traffic flow theory .Considering comprehensively the route distance, intersection number, signal control delays and other factors, the paper established the analytic hierarchy process model of optimal path and determine the actual vehicle route based on the fuzzy comprehensive evaluation algorithm. This article also proposed the concept of the intersection domain to reasonably separate intersections from the link and reconstructed GIS network model. In consideration of intersection delay, this paper established the intersection domain travel time estimates model based on spatial moving average structure and calculated the link travel time estimates using the difference method. This study using the above algorithm effectively solves the problem of the link travel time estimates of intersection domain based on the low-frequency floating car data.

英文关键词： probe vehicle ;Low frequency sampling;path inference ;traffic control;travel time estination