【作者】 孙晓梅；

【导师】 杨兆升；

【作者基本信息】 吉林大学 ， 交通信息工程及控制， 2011， 博士

【摘要】 伴随着经济的快速发展与城市化进程的不断加快,城市交通拥挤与拥堵、交通安全等道路交通问题不断蔓延丌来,不仅造成了巨额的经济损失,同时加剧环境污染和能源消耗,对生活、工作、出行等居民日常活动造成了严重的影响。同时,我国由于道路面积率普遍偏低、混合交通流严重等因素,导致城市交通问题更加难以解决。据统计,我国有15座城市每天因交通拥堵造成的经济损失近10亿元；每年全国由于交通拥堵造成的损失则达到全国GDP的5%-8%。如何解决城市交通拥挤与拥堵这一民生问题,已经成为举国上下关注的热点。目前,解决道路交通问题的途径主要分为2类：加强道路建设一增加道路容量；发展智能交通系统(Intelligent Transportation Systems,ITS)—提高道路运行效率。然而在城市土地资源有限的条件下,通过智能交通系统优化道路交通组织与管理无疑成为一条最有效的途径。作为ITS的核心组成部分,动态交通诱导系统在城市道路交通管理中的作用日益凸显。它采用检测技术、计算机技术、网络技术等高新手段,基于实时交通信息采集、处理与传输,通过中心式、分布式等多种诱导方式,为驾驶员提供交通事件、行程时间和优化路径等动态信息,可引导驾驶员避开拥挤走最佳行驶路线,从而实现了路网交通流的均衡动态分配,有效缓解了交通拥挤。作为交通诱导系统的关键和核心技术之一,动态路径选择是每个出行者都要面临的问题。就其本质而言,路径选择就是在综合多源信息的前提下,选择合适的路阻函数,将路网合理动态优化,再选择合适的算法计算出满足一定条件的最佳路径。路径选择模型及其算法,通过快速求解从出发地到目的地的最优路径,从微观上优化出行者的合理出行,从宏观上促进了路网交通流量的均衡分配,起到缓解交通拥挤的重大意义。依托国家高技术研究发展计划(863计划)课题以及昆明公安局交通警察支队项目,本文主要针对多源交通信息下的动态路径选择模型与算法展开研究,重点研究多源交通信息下的出行者路径选择行为、出行前动态路径选择模型与算法、换乘行为影响下的公交路径选择模型与算法以及出行中的动态自适应路径选择模型与算法等。全文共分六章,第二章至第五章是论文研究的核心内容,针对多源交通信息作用的出行者行为以及出行前、出行过程中以及公交换乘等不同出行者需求,研究合理的动态路径选择模型与算法。第一章主要介绍论文的研究背景、国内外研究现状、研究目的及研究思路,第六章为论文的总结与展望,对论文的主要研究内容、关键创新点以及下一步的研究重点做总结性概括与前瞻性展望。论文的具体研究成果如下：1)在对国内外交通诱导系统、动态交通分配理论及动态路径选择模型的研究现状与发展趋势做总结性分析的基础上,提出了现有动态路径选择模型研究中存在的不足,明确了动态路径选择技术的研究目的与研究意义,并提出了多源交通信息下的动态路径选择技术的研究方法和研究思路；2)从多源交通信息的内涵与外延入手,对多源交通信息的概念、组成、特征以及系统构成进行了具体分析,并针对多源交通信息的服务领域与主要用户,对出行者对目的地、出行方式、路径选择、出发时刻等多源交通信息的需求特征展开具体研究,提出了多源交通信息条件下出行者路径选择行为研究的理论基础、影响因素与假设条件,分析了不同信息强度下出行者的路径选择行为,为出行者路径选择模型的建立提供了理论依据；3)分析了先验信息、不确定信息以及多源动态信息3种不同信息模式下的路径选择关键点,在对先验信息条件下基于前景理论的出行前路径选择模型,以及不确定信息条件下基于累积前景理论的静态路径选择模型研究的基础上,提出了以多源交通信息下的以预测行程时间最短为第一优化目标、以行程时间可靠性为约束条件的出行前多目标规划模型与算法。考虑到非常态事件对出行路径选择的影响因素,在分析了基于行程时间与路线复杂度及基于行程时间与安全性的应急疏散救援路径选择模型研究的基础上,提出了基于事件影响扩散实时估计的应急路径选择模型。4)针对不同网络换乘条件下的公交网络路径选择问题,分析了公交换乘行为影响下的公交网络变换方法,对基于公交票价与线路运行时间转化及基于最优路线分析的公交换乘网络变换方法进行了具体研究。针对传统最短路算法无法有效解决公交网络路径优化的不足,基于准用户最优动态交通分配准则,提出了常态换乘条件下求解K条公交路径选择模型与算法。分别对基于随机网络技术的、考虑换乘等待时间的公交路径选择模型,以及非常态下基于时间扩展网络的应急疏散公交路径选择模型进行了扩展性研究。5)针对出行中路径选择的时变性与时效性特点,结合蚁群算法求解离散系统下优化问题的优越性,提出了基于改进蚁群算法的路径自适应选择模型。在对城市道路交通流呈现出的间断性特性分析的基础上,提出了适用于间断流的行程时间自适应指数平滑预测方法,并以短时预测路段行程时间作为路径选择信息素、建立了求解K条最优路径的自适应路径选择模型与方法,克服了传统基于蚁群算法的路径选择自适应模型在复杂路网结构与交通流动态变化情况下,动态路段行程时间函数标定困难、求解复杂以及误差较大等问题。更多还原

【Abstract】 Nowadays,with fast economy development and urbanization speed,traffic congestion and safety problems have spread worldwide cities.They lead to huge economic losses as well as environmental degradation and energy consumption,and affected people’s daily travel activities seriously.According to statistics,there are 15 cities with one billion losses every day caused by traffic congestion,and this may lead to 5 percent to 8 percent of national GDP one year. So how to solve this difficult livelihood issue is excepted in the whole country.However, there are two roads before us,building roads and employ Intelligent Transportation Systems(ITS).No doubt improve existing roads’ efficiency is the most perfect way,when urban land resources are limited.As the core of ITS,traffic flow guidance system(TFGS) has become more significant in urban traffic managements.Based on high-tech means,TFGS picks up real-time traffic data to guidance information that include traffic incidents,travel time and optimal path.So drivers can avoid crowded sections through central or distributed guidance type,then relieve traffic congestion by made traffic flow balanced distribution in the network.As a key technology of TFGS, dynamic route choice is a general matter to every traveller. And route choice is essentially a task that choose a suitable impedance function under complex and multi-sources information,then realize the flow optimization dynamically on the road network,and calculate an optimal path depend on several conditions through right algorithm.The process optimize travellers reasonable travel at the micro and balance traffic flow’s distribution at the macro.Supported by National High-Tech Research and Development Program(863 Program)and Kunming Public Security Bureau traffic police detachment program,this thesis is aimed mainly at key technologies of dynamic route choice models and algorithms under multi-sources. Specifically, it lays emphasis on the research of travellers’ travel behaviour under multi-sources traffic information, dynamic route choice models and algorithms before travelling, public transportation route choice models and algorithms affected by transfer activities and adaptive route choice models and algorithm on travel. And this thesis consists of six chapters.The first chapter introduced the research background of the thesis,the research status at home and abroad,research targets and ideas. Chapter two to Chapter five are the core content of this thesis,they have studied on dynamic route choice models and algorithm against travellers’ travel behaviours under multi-sources traffic information and different requirements during different travel periods and travel styles.And Chapter six has generalized summaries,key innovations of the whole thesis and made a forward-looking for further work.The main achievements of the thesis are as follows:1) Based on status and trends analysis of TFGS, dynamic Traffic Assignment (DTA) and dynamic route choice models, it put forward the shortages of common dynamic route choice models, and defined the targets and worth of dynamic route choice technology study, then made out study method and ideas of this study under multi-sources traffic information.2) Starting from the contents and extensions of multi-sources,a specific analysis was made on its concept,compositions and features,then the thesis studied on the travellers’ information demand characteristics,including destinations,travel styles,route choices and starting time demands etc..And the theory, factors and assumptions for travellers’ dynamic route choice behaviours under multi-sources were also proposed.Based on this study basis,this thesis analyzed travellers’ route choice behaviours under different information strengths,which supported theories for route choice models.3) The key issues about route choice were analyzed that under prior information,uncertain information and multi-sources information modes.Firstly,this thesis studied on route choice models based on prospect theory when only prior information were provided,and route choice models based on cumulative prospect theory under uncertain information as well.Secondly,it put forward a multi-objectives route choice model with minimum predicting travel time as the first optimization goal and travel time reliability as constraints.Taking the abnormal accidents’ influence about route choice into account,this thesis proposed a route choice model based on a real-time estimation of accidents’ influence,after the analysis of the emergency route choice models based on travel time and routes complexity as well as travel time and safety.4) Firstly,it studied on the transform method of public transportation network under the influence of transfer behaviours,consisting of the method based on bus fares covertion to bus route travel time and the method based on optimal route analysis.Secondly,following the quasi-DTA principles,a bus route choice model with K optimal paths was put forward based on improved method.After that,this thesis made an extended study on bus route choice model based on Graphical Evaluation and Review Technique considering transfer time,as well as emergency bus route choice model based on time-expanded network under abnormal accidents.5) Against time-varying and timeliness characteristic of route choice on-travel,this thesis put forward a adaptive route choice model based on improved ant-method with the superiority shows in solve the optimal problems of discrete system.Firstly,it analyzed features of intermittent urban traffic flow,and then proposed a adaptive exponential smoothing method for travel time prediction under intermittent traffic flow. Secondly,with prediction travel time as route choice pheromone,this thesis established an adaptive route choice model,so it overcome the problems common route choice model has made by ant-method更多还原