城市公交动态网络的CPSS模型及其时空域协同优化方法研究

In the project, urban public traffic includes all kinds of public transportation tools with the fixed lines and stops, like bus with or without own lanes, and BRT etc. Until now, the basic research of urban public traffic focuses on the bus priority control of the intersection, bus line and network’s scheduling, buses’ real-time monitoring and scheduling, but there is few research on passengers’ travel behavior based on real-time data acquisition of buses’ and passenger’s status, and their collaboration with buses. With the increasing popularity of urban bus cards and smart phones, it becomes necessary and possible for the real-time collection of public traffic passengers’ OD data and travel status, bus passengers’ travel dynamics, bus network’s status and dynamics. To solve two key scientific problems, i.e. CPSS modelling and verification, passengers and buses’ adaptive and collaborative optimization and its realization, our project’s main research topics include: public traffic’s network and environment model; buses’ dynamic network model; bus passengers’ social network model; Cyber-Physical-Social-System (CPSS) models of Urban Public Traffic Dynamic Network (UPTDN) including its main factors like passengers, buses, road network and environment; construction and verification of CPSS platform for UPTDN; passengers and buses’ matching degree definition and its dynamic analysis in different spatio-temporal domains of UPTDN; passengers and buses’ collaborative optimization method and the typical applications, such as: the information acquisition, collaborative and personalized service for every passenger and bus. In the end, by using the online computing experiments, available application data or pilot, the achieved CPSS models and CPSS platform of UPTDN are verified, and the passenger service and buses scheduling’s quality can be improved continuously by pursing their adaptive and collaborative optimization.

城市公交包括普通公交、专用道公交、BRT等，是具有固定线路和站点的公交工具。目前，国内外研究集中在路口公交优先控制、公交线路优化和公交车辆调度，较少通过采集乘客数据来研究出行规律，来实现不同时空域中人车协同优化。随着公交卡和智能手机普及，可全面获取乘客OD和出行方式等数据，从而分析掌握公交路网实时状态、公交乘客出行规律等。本项目为解决CPSS模型构建和验证、不同时空域中公交乘客自适应协同优化和有效调控2个关键科学问题，拟主要研究：公交路网环境模型；公交车联网模型；公交乘客社会网络模型；城市公交动态网络(UPTDN)要素的社会物理信息系统(CPSS，人、车、路和环境)模型及数据验证；UPTDN的CPSS平台构建与验证；UPTDN的时空域人车匹配度定义与分析；UPTDN的时空域人车协同优化典型应用。最后，通过计算实验、可用数据或应用示范，来验证CPSS模型和平台、公交和乘客自适应协同优化方法。

城市公交包括普通公交、专用道公交、BRT等，是具有固定线路和站点的公交工具。目前，国内外研究集中在路口公交优先控制、公交线路优化和公交车辆调度，较少通过采集乘客数据来研究出行规律，来实现不同时空域中人车协同优化。为实现城市公交动态网络（Urban Public Traffic Dynamic Network, UPTDN）全要素的服务和管控水平，在不同时空域的协同持续优化，本项目解决了社会物理信息系统（Cyber-Physical-Social-System, CPSS）模型构建和验证、不同时空域中公交乘客自适应协同优化和有效调控2个关键科学问题，主要研究内容包括：首先，引入了移动社交网络，利用手机信令数据、微博、新闻、GPS轨迹等相关社交媒体数据获取了城市公交动态网络所需的基础数据并建模UPTDN-CPSS的各个组件模块，全面准确地描述城市公交动态网络全要素；其次，以此为基础，根据现有人工交通系统Transworld和计算实验，解决UPTDN的CPSS平台构建难题；然后，借助该CPSS平台，分析了人车行为的动态演化规律，找到UPTDN中的人、车、路协同优化方法；最后，对CPSS平台的计算实验以及在城市公交系统领域开展了示范应用，验证项目整体方案的可行性。执行期内，本项目建立了城市公交道路、车辆、乘客和环境等要素的CPSS模型及其时空域人车协同优化方法，掌握道路和车辆状况、市民公交出行规律，研究了公交乘客的个性化服务算法，实现了不同乘客和相应车辆在时间和空间域的自适应协同优化算法和功能，以不断地提高“人找车、车找人”的匹配准确率和服务效率，构建政府用户的城市公交监管功能和优化算法，公交乘客和公交工具在不同时间和空间域的协同优化算法。项目成果可实现城市公交的智能化、个性化信息服务，吸引更多市民出行选择公交，提高城市公交分担率，促进城市交通向高效和绿色方向发展。项目组共发表专著章节3章，论文45篇，其中SCI收录16篇，EI收录27篇，其他期刊论文2篇；授权专利8项，取得科研奖励8项。