基于信息理论的车辆移动预测极限及方法研究

项目名称： 基于信息理论的车辆移动预测极限及方法研究

项目编号： No.61301080

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 无线电电子学、电信技术

项目作者： 李勇

作者单位： 清华大学

项目金额： 28万元

中文摘要： 随着城市机动车辆的急剧增加，交通堵塞和交通事故成为了全球范围内的重要社会问题。城市智能交通系统是解决交通问题的重要研究对象和手段之一。本项目将针对车载移动预测这一涉及智能交通系统中交通流量优化调度和车载网络设计等问题解决的基础性问题展开研究。首先，从课题组已经具备的北京、上海及洛杉矶三个大规模城市范围内的车载移动数据入手，从宏观和微观两个不同维度建立移动模型，以刻画微观移动速率、移动方向、移动长度及宏观区域切换与滞留时间等移动参数；其次，基于移动模型，分析车载移动行为特征，揭示车载移动的可预测性及预测极限；再次，研究逼近理论预测极限的车载移动预测算法问题，提出包括节点区域滞留时间、区域切换及移动速度与方向在内的移动预测算法。最后，本项目将面向城市智能交通系统，运用所提出的相关预测算法，展开车辆行车路径优化与车载网络机会路由转发算法相关应用。

中文关键词： 自组织车载网络；网络建模；移动管理；移动预测；

英文摘要： With the dramatic increase of vehicles in the large cities, traffic congestion and accidents have become a global range of social issues. Urban intelligent transportation system is one of the important solutions to solve the traffic problems. The project will investigate for vehicular mobility prediction problems, which is related to the transport network optimization and vehicular network design in the intelligent transportation systems. First, based on three large scale city vehicular mobility trace, Beijing, Shanghai and Los Angeles, we investigate two different dimensions of the macro-and micro to establish the mobile model, which aims to characterize the microscopic level mobility rate, direction, moving length and macro level regions switching and residence time. Secondly, based on the mobile model, we will analyze the behavioral characteristics of the vehicular mobility and reveals their predictability limits. Third, we will propose mobility prediction algorithm to approximation the theory prediction limits, include the prediction of staying time, regional switching and movement speed and direction. Finally, we will use the proposed prediction algorithms to study the vehicle driving path optimization and the opportunities routing forwarding algorithms for vehicle networks in the urban intelligent transp

英文关键词： Ad hoc vehicular networks；network modeling；mobility management；mobility prediction；