基于SD-GM理论的城市交通拥堵收费模型研究

随着中国城市化建设步伐的不断加快,交通拥堵在不断地加剧。同时,因机动车污染物的排放,每年将产生大量的NO_x,从而又会引起严重的大气污染(如“雾霾”污染)。针对这些问题,本文从环境和社会的角度出发,采用系统动力学与灰色系统相结合的方法(SD-GM),构建了城市交通拥堵收费模型,并对模型中主要变量进行动态仿真和决策分析,以此来寻找缓解交通拥堵和减少机动车尾气排放的可行策略。通过现实性测试和敏感性测试,得到拥堵收费的范围不超过100元/天*辆。通过进一步的仿真和结果分析可得到以下结论:(1)在区间[25,40] 内,随着拥堵收费的提高,NO_x存量,机动车出行吸引度和交通拥堵程度都呈下降趋势,而车均道路面积呈上升趋势。(2)但并非拥堵收费越高越好, 超过40 元/天*辆,会产生相反的效果。最后,通过比较分析,得到NO_x存量,机动车出行量,机动车出行吸引度和交通拥堵程度分别下降了约33.76%,39.64%,43.26%,82.25%,而车均道路面积提高了大约65.68%,进而验证了模型的有效性和实用性。     

平均上班花费时间计算及其成因探究

上班花费时间是反应交通拥堵问题的一个重要因素.指标的长短可以衡量一个城市产业结构规划的合理性、交通网络构建的合理性、功能分区建设的合理性以及城市人力资源分布的利用程度、居住的适宜程度、人们生活的幸福程度等.因此,计算了2008-2013年中国其中31个省市自治区的平均上班花费时间.选取造成交通拥堵的4个主要因素:私家车保有量,城市交通承载力,公共交通系统,科技创新发展中的17个指标对拥堵时间进行时间与空间分析.根据分析结果给出不同时间,不同地域中国各省市自治区解决交通拥堵问题的合理性建议,以期为我国十三五规划的城市交通管理提供实践参考,推动我国交通出行更安全、更便捷、更经济、更环保、更舒适的运行和发展.     

A-P-S组合策略的多重绩效及其“褪色”效应分析

为了降低城市交通拥堵及空气污染程度,本文在现有研究的基础上引入罚款政策,利用系统动力学方法原理构建了机动车污染物减排管控模型。通过仿真和比较分析来探索空气污染收费(Air pollution charging fee,简称APCF)、罚款(penalty)和补贴(subsidy)政策(简称A-P-S策略)的作用效果。研究结果表明:一方面,组合策略具有多重绩效,不但能够降低污染损失(经济-环境效益)、死亡人口的生命价值(社会-经济效益)、交通拥堵程度(社会效益)和机动车污染物总量(环境效益),而且能大大改善环境生态承载力(环境效益)和机动车非法出行增长量(社会安全绩效);另一方面,政策在实施过程中也会遇到一定的局限性,如初期的滞后性,后期的“褪色”效应和“反弹”效应,因此,从长期来看,需要及时调整组合方案。最后,根据仿真结果提出了相应的政策建议,进而为城市交通和环保等相关部门提供决策参考。     

多层次模糊综合评价在城市交通承载力评价中的应用

城市交通承载力评价是一项复杂的系统二程.根据交通承载力的特点、评价过程及评价结果的模糊性,将城市交通承载力分为交通设施承载力和交通环境承载力,结合城市交通现状构建了交通承载力的评价指标体系.借助熵权法确定各评价指标的客观权重,并将其与模糊一致矩阵的主观赋权法相结合,提出基于组合权的多层次模糊综合评价法.评价结果表明,组合评价方法比单一评价方法更符合城市交通承载力的实际状况,从而为交通管理决策提供科学依据.     

基于系统动力学的城市道路交通污染控制问题研究

城市交通污染是我国城市化发展进程中亟待解决的问题,问题涉及变量多且结构复杂,很难用数学模型进行全面描述.为了综合考虑城市交通污染气体排放的影响因素及其相关关系,从系统的角度出发应用系统动力学原理在充分考虑交通拥堵对污染气体排放影响的基础上建立了城市交通污染气体排放模型.并以上海市为例运用Vensim PLE软件对模型进行仿真,发现交通拥堵对城市交通污染的影响非常显著,当交通负荷大于1.62时,污染物的排放量呈指数增长.最后针对上海市的交通政策对污染气体排放的影响进行仿真分析,提出控制交通污染的合理化建议.     

合作博弈视角下城市道路交通拥堵收费研究

城市道路交通设施作为准公用物品,其外部效应必然导致交通拥堵的发生,实施拥堵收费的目的则是使交通拥堵产生的外部成本内部化,确保城市道路资源得到高效配置,应用经济杠杆来调节交通需求,以缓解交通拥堵.本文应用合作博弈相关理论对城市道路拥堵网络问题进行了分析,从同一时刻各个路段的通勤者数目这一角度定义拥堵成本,重点证明了拥堵成本为凸函数的城市道路拥堵网络博弈存在非空的核,拥堵成本为凹函数的城市道路交通网络博弈虽不存在非空的核,但总是存在最优的树网络,最后,结合上述结论对城市道路拥堵收费进行讨论,从理论上对拥堵收费的合理性进行了说明,并提出了进一步研究的方向.     

城市交通投资结构调整与交通需求互动优化模型研究

城市交通投资结构研究有助于了解交通供给能力特征,缓解城市交通拥堵状况.北京市在过去的十几年来大量的交通资金投入到道路建设中,但并没有从根本上扭转日益突出的交通供需矛盾状况.从交通投资与交通需求的关系出发,探讨投资方向和投资力度对交通供需结构的影响.给出交通投资结构阶段统计特征、分析了北京市"七五"至"十五"时期交通投资系统与交通需求、交通供给和社会经济系统关系.应用多目标优化方法,并运用M atlab软件计算不同交通结构情境下的交通投资取向、结构、管理上提出建议.     

低碳政策下考虑道路拥堵的多式联运路径选择问题

为明确低碳政策及道路拥堵对多式联运路径选择的影响,构建了不同碳排放政策下考虑道路拥堵的多式联运路径选择模型。模型在考虑拥堵对运输时间影响的基础上进一步量化其对系统碳排放的作用效果。针对此类整数规划模型,设计了基于保优策略和移民策略的遗传算法进行求解。最后,通过算例探讨强制排放、碳税、碳交易及碳补偿四种碳排放政策对多式联运减排、缓解拥堵及成本的影响。结果表明考虑道路拥堵对运输碳排放的影响可得到更加合理的路径决策,且以强制碳排放政策为主的多种政策组合能更好的降低碳排放、缓解道路拥堵并促进多式联运推广。本模型可为政府制定合理的多式联运低碳政策以及企业制定合理的路径决策提供理论依据。     

城市非高峰期动态出行交通网络均衡

我国在城市化进程中,许多城市交通部门为了缓解城市交通拥堵问题,制订了大力发展公共交通的政策,而城市公共交通非高峰期的出行人群交通方式选择是一个值得讨论的问题.在此基础上通过分析几种不同的交通出行方式的分路段成本,建立了具有非高峰期特点的多方式出行路网模型,并对模型进行了计算求解,依据结果对非高峰期公共交通出行的特点进行了讨论.     

交通拥堵与空气质量——来自汽车尾号限行的证据

由于空气的污染来源众多,交通拥堵是否加剧了空气质量的恶化,一般情况下很难界定和区分。本文利用一个特殊的工具变量——北京市工作日高峰时段汽车根据尾号限行,来分析和回答上述问题。由于受文化习惯影响,居民在挑选车牌号码时一般都不选4,因此包含数字4的车牌号很少。每当限行尾号为4和9的工作日,北京市的道路交通相比其他工作日会更拥堵,这为我们提供了一个识别交通拥堵的独特指标。通过使用双重差分模型排除了大量干扰因素后,我们对北京市35个空气质量监测站点PM2.5浓度逐时数据的分析发现,在限行尾号为4和9的工作日,高峰时段与非高峰时段的PM2.5浓度差异,比其他工作日的差异高出9.46%。交通拥堵显著降低了空气质量。     

大数据背景下基于5S的城市交通拥堵评价模型研究

近几年来,城市交通拥堵问题日益突出,极大制约了城市发展。在大数据背景下,为了准确掌握交通实时拥堵状况,改善城市交通,便利市民出行,本文深入挖掘城市交通拥堵的影响因素,构建了基于交通5S要素的城市拥堵理论模型,运用径向基函数神经网络方法工具,以上海静安寺、上海站、陆家嘴周围三大拥堵路段的交通数据集为例,验证了该模型的有效性。实验结果表明,由该模型获得的城市交通拥堵预测值与上海实际交通路况具有较好的拟合效果,表明交通5S模型与方法能够准确有效地评价城市交通拥堵。     

A dynamic route guidance system based on real traffic data

Mobility is one of the vital goods of modern societies. One way to alleviate congestion and to utilise the existing infrastructure more efficiently are Advanced Traveller Information Systems (ATIS). To provide the road user with optimal travel routes, we propose a procedure in two steps. First on-line simulations supplemented by real traffic data are performed to calculate actual travel times and traffic loads. Afterwards these data are processed in a route guidance system which allows the road user an optimisation with regard to individual preferences. To solve this multiple criteria optimisation problem fuzzy set theory is applied to the dynamic routing problem.     

Setting expediting repair policy in a multi-echelon repairable-item inventory system with limited repair capacity

Inventory systems with limited repair capacity are affected by congestion externalities, caused by use of a shared service. There is incompatibility between individual and system optimisation in considering congestion externalities. Three models are described that investigate the congestion effect in a multi-echelon inventory system which has two modes of repair, each with a limited repair capacity. An expanding repair policy employed by the bases in order to choose which repair mode to use is described and compared with different expediting policies related to congestion externalities. The expanding repair policy that considers congestion externalities was found to lead to better system performance measurement than an expanding policy with no congestion. The results of the numerical experiment indicate that the model that ignores congestion externalities—that is, the model that measures each base as an individual—leads to poorer performance measurement for every expediting repair policy, and particularly for the optimal expediting repair policy.     

基于畅通可靠性的开放小区交通流分配及优化决策

开放小区内部道路可增加城市道路网的密度和可达性,从而达到缓解城市道路拥堵的目的。通过对出行者进行问卷调查,得知其路径选择行为主要考虑出行时间及时间波动性两方面因素,基于此对CONTRAM费用函数进行改进,得到适用于小区开放后的广义出行费用,该费用考虑了畅通可靠性对路径选择的影响;结合小区开放后出行者选择准则,建立考虑广义出行费用的随机用户最优模型(SUO),并采用逐次平均算法(MSA)进行求解,从而得到更为精确的路段交通流量;基于小区道路开放后需承担的交通量,结合城市道路规划相关规范,对横断面、出入口等方面提出开放小区内部道路规划的建议。     

Simultaneously optimizing link tolls and signal settings in a road network

The problem of determining link tolls to reduce traffic congestion is often referred as a toll design problem. In this paper, optimal tolls are determined for signal-controlled junctions in urban traffic road networks where the rerouting traffic is properly taken into account. This problem can be formulated as a mathematical program with equilibrium constraints (MPEC) where the user equilibrium is expressed as a variational inequality problem. Due to the non-differentiability of the equilibrium problem, an efficient convergent solution scheme is established. Numerical calculations are conducted on a variety of example road networks and comparisons are made with earlier methods.     

A GIS-based decision support system for planning urban transportation policies

A decision support system (DSS) integrated in a geographical information system (GIS) for the analysis and evaluation of different transport policies is presented. The objective of the tool is to assist transport administrators enhance the efficiency of the transportation supply while improving environmental and energy indicators. The DDS works on three levels. The first performs the transport network analysis, the second assesses the energy consumption and pollutant emissions and the third evaluates the several policies selected. Road traffic is simulated using a deterministic, multi-modal traffic assignment model with capacity constraints. The model allows the estimation of traffic flow patterns within each link of the road network starting from the knowledge of the network characteristics and traffic demand. Energy consumption and pollutant emission calculations are based on the methodology developed by the CORINAIR working group. The evaluation of each policy scenario is based on a number of traffic, environmental and energy indicators. A multi-criteria analysis, where decision is based upon judging over appropriate weighted criteria, is adopted. Models are integrated in a GIS environment, which serves as the repository of the data as well as the user interface of the tool. The use of the tool is demonstrated through characteristic case studies on the Greater Athens Area in Greece. Two policy measures, one concerning the extension of the region where half of the private cars are prohibited from entering to the Municipality of Athens and the other the reduction of parking places in the same region by 50% are evaluated.     

Spatial distribution complexities of traffic congestion and bottlenecks in different network topologies

Recently, urban traffic congestion has become a popular social problem. The generation and the propagation of congestion has close relation with the network topology, the traffic flow, etc. In this study, based on the traffic flow propagation method, we investigate the time and space distribution characteristics of the traffic congestion and bottlenecks in different network topologies (e.g., small world, random and regular network). The simulation results show that the random network is an optimal traffic structure, in which the traffic congestion is smaller than others. Moreover, the regular network is the worst topology which is prone to be congested. Additionally, we also prove the effects of network with community structure on the traffic system and congestion bottlenecks including its generation, propagation and time–space complexities. Results indicate that the strong community structure can improve the network performance and is effective to resist the propagation of the traffic congestion.