混合交通流时间序列的去趋势波动分析

应用去趋势波动分析法研究交通流时间序列的复杂性,探讨了混合交通流时间序列演变行为的标度指数.根据标度指数的变化特征,进而揭示交通流时间序列所具有的长程相关性和短程相关性.通过分析发现,存在一密度ρ,当ρ₁<ρ<ρ₂时,交通流时间序列具有长程相关性;而当ρ<ρ₁或ρ>ρ₂时,交通流时间序列具有短程相关性,即密度的变化影响着标度指数的变化.另外分析了在不同慢车比率条件下时间序列的标度指数,发现慢车比率的变化 关键词： 混合交通流 去趋势波动分析 时间序列 长程相关     

区域资源条件评价指标体系建立的研究

从探讨建立区域资源条件评价指标体系的原则入手，对区域内各类资源的概念、特性及其构成了系统分析，进而建立了较为完善的区域资源条件评价指标体系，为实施区域资源条件评价奠定了科学的基础。     

考虑最大风险约束的危险品运输网络优化研究

本文在定义危险品运输风险的基础上，建立了带有最大风险约束的危险品运输网络模型，模型考虑了网络中社会车辆对危险品车辆的出行时间及网络总风险的影响，并针对建立的模型采用了相应的粒子群算法进行求解。最后应用算例分析了模型和算法的有效性。计算结果表明，考虑网络最大风险约束能使危险品运输的网络总风险得到较大幅度的降低。     

基于均衡和接续的路网列车运行图调整研究

铁路中的换乘车站如果发生突发事件,会造成路网中部分列车到达换乘站晚点,晚点超出一定范围时与之接续的列车将不再保持接续关系,导致旅客无法完成换乘且接续列车晚点。本文建立了基于均衡和接续的路网列车运行调整模型,调整后使列车到达终点站的时刻与原计划时刻偏差最小并且总延误时间最小。使用Gurobi优化软件对模型进行了求解,结果表明,调整后的运行图能够有效缓解突发事件对列车运行造成的影响,且晚点在一定的范围内,通过列车接续能够保证旅客的顺利换乘。     

Complex Behaviour for the Origin and Destination Matrix Estimation Problem

The origin and destination （O-D） matrix estimation is an important problem in traffic networks. We apply the gravitation model to express the preference attachment and to analyse the statistical characteristics of the traffic flow in each O-D pair in theory. It is found that the distribution of the future O-D matrix decays as a power law. Additionally, different exponents are obtained for both the constant and variable link cost.     

The Stability of Multi-modal Traffic Network

There is an explicit and implicit assumption in multimodal traffic equilibrium models, that is, if the equilibrium exists, then it will also occur. The assumption is very idealized; in fact, it may be shown that the quite contrary could happen, because in multimodal traffic network, especially in mixed traffic conditions the interaction among traffic modes is asymmetric and the asymmetric interaction may result in the instability of traffic system. In this paper, to study the stability of multimodal traffic system, we respectively present the travel cost function in mixed traffic conditions and in traffic network with dedicated bus lanes. Based on a day-to-day dynamical model, we study the evolution of daily route choice of travelers in multimodal traffic network using 10000 random initial values for different cases. From the results of simulation, it can be concluded that the asymmetric interaction between the cars and buses in mixed traffic conditions can lead the traffic system to instability when traffic demand is larger. We also study the effect of travelers' perception error on the stability of multimodal traffic network. Although the larger perception error can alleviate the effect of interaction between cars and buses and improve the stability of traffic system in mixed traffic conditions, the traffic system also become instable when the traffic demand is larger than a number. For all cases simulated in this study, with the same parameters, traffic system with dedicated bus lane has better stability for traffic demand than that in mixed traffic conditions. We also find that the network with dedicated bus lane has higher portion of travelers by bus than it of mixed traffic network. So it can be concluded that building dedicated bus lane can improve the stability of traffic system and attract more travelers to choose bus reducing the traffic congestion.     

应用人工神经网络确定评价指标的权重

阐述了如何利用人工神经网络方法确定评价指标的权重,以消除以往权重确定过程中人为影响及缺乏动态性这一弊端,具有一定的实用意义。     

基于参考点的逐日交通流演化研究

本文建立了基于参考点的逐日交通流演化模型,模型通过将实际出行时间与参考点进行比较,描述了出行者的感受对估计时间以及路径选择的影响。估计时间模型中用参数取值大小反应出行者对损失的规避大于对等量获得的偏好。分别讨论了出行者乐观、悲观以及中立情况下对应的参考点取值,并研究了三种情况对演化过程及总出行时间的影响。演化结果表明,出行者悲观情况下对应的系统总时间最大,乐观情况下对应的系统总时间最小。该研究有助于理解城市交通流演化的本质规律。     

基于智能交通卡数据的城市轨道交通乘客个体路径选择模型

在分析城市轨道交通乘客旅行时间组成要素的基础上,提出了一种基于智能交通卡数据的乘客个体路径选择模型,克服了传统路径选择模型只考虑群体路径选择的弊端。通过分析轨道交通刷卡出行的特点,建立了乘客旅行时间模型,确立了各旅行时间要素并分析了其独立性。对出行要素进行了估计,计算出路径旅行时间,提出了乘客个体的出行路径选择模型。以北京地铁网络为案例,分析了乘客个体的路径选择,并用实际数据验证了模型的有效性。