基于和谐理念的出租车客运系统发展研究

从行业管理角度出发。采用和谐理念．分析当前出租车客运系统的“负效应”。探讨其表现形式和成因。通过对目前出租车客运系统和谐状态的判断。指出相关的和谐要点和简单措施。     

大型城市网络OD推算

提出了对已知流量的路段数少于OD对的对数的路网进行OD推算，利用Logit概率多路径选择模型，建立已知流量路段的分配模型，采用迭代算法对其进行求解，并对结果进行分析，提出了大型城市网路OD推算步骤。     

新线开通对线网客流特征的影响

随着北京市轨道交通的快速发展,每年的新线开通都将对线网各线的客流分布产生较大的影响,但新线可研多注重新线自身的预测,缺乏线网整体变化的预测分析.结合线网客流变化的关键因素,探索利用新线可研和现有OD数据预测新线开通后线网客流的方法,并以北京地铁4号线开通为例进行验证,从一定程度上证明该方法的可行性和适用性.     

动态OD反推理论中的关键问题研究

针对ITS研究中动态OD矩阵难以获得的问题,回顾动态OD反推理论的发展历程,在此基础上明确了该领域研究中的四个关键问题:状态变量的选择、系统方程的确定、OD量与路段流量的关系和OD矩阵动态特性的体现,在对其进行分析的基础上提出每个关键问题的解决方法,为动态OD反推理论的进一步研究垫定基础。     

车辆牌照信息调查法在公路OD调查中的应用

分析停车问询调查法和车辆牌照信息调查法在公路OD调查中的优缺点,结合浙江省两次全省公路OD调查的实际经验,指出公路OD调查自动化和常态化的发展方向.     

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通过常规阶段和奥运期间对出租车运行特征的监测与对比分析,研究奥运期间在交通限行背景下出租车出行规律和特征,评价出租车客运系统供给能力和运行效率,研究影响交通特征变化的有关因素,从而为今后大型活动的交通保障工作积累经验。研究结果表明,奥运期间出租车出车率达到92.26%,日均客运量较赛前增加19.2%,出租车空驶率由赛前的46.05%降低到37.06%;76.31%的受访者认为出租车运行速度较赛前有明显提高,而仅28.85%的受访者认为出租车候车时间明显变短,出租车服务水平还有待进一步提高。     

基于系统动力学的大连市出租车保有量预测

采用系统动力学模型,找出影响出租车规模内外因素间的因果关系,包括经济、人口、机动车保有量、出行需求、政策等.在系统结构分析和因果反馈分析的基础上建立了出租车系统,以大连市出租车相关统计数据进行仿真计算,分析了不同的发展政策对出租车系统的影响,提出相应的建议和对策.     

基于电动出租车数据的充电桩选址聚类方法比较

为有效降低出租车运营企业及经营者的经济成本,通过分析出租车的卫星轨迹数据,比较和选取用于电动出租车充电桩选址规划的聚类方法。以上海市电动出租车充电站的选址规划为研究对象,分别基于孤立森林和聚类算法设计异常值检测方法,对相关时段的出租车卫星数据进行清理以及数据可视化处理;比较层次聚类（Agglomerative Clustering）、高斯混合模型（Gaussian Mixture Model, GMM）、K-means聚类、Mean-Shift聚类以及谱聚类（Spectral Clustering） 5种算法的聚类效果,并选取K-means算法作为充电桩选址规划参考算法。从城市区域划分及企业运营角度确定充电桩选址方案,为未来上海市区电动出租车充电桩的数量和容量配置提供设计依据。     

Estimation of origin-destination matrices from link counts and sporadic routing data

Estimation of origin-destination (OD) matrices from link count data is a challenging problem because of the highly indeterminate relationship between the observations and the latent route flows. Conversely, estimation is straightforward if we observe the path taken by each vehicle. We consider an intermediate problem of increasing practical importance, in which link count data is supplemented by routing information for a fraction of vehicles on the network. We develop a statistical model for these combined data sources and derive some tractable normal approximations thereof. We examine likelihood-based inference for these normal models under the assumption that the probability of vehicle tracking is known. We show that the likelihood theory can be non-standard because of boundary effects, and provide conditions under which such irregular behaviour will be observed in practice. For regular cases we outline connections with existing generalised least squares methods. We then consider estimation of OD matrices under estimated and/or misspecified models for the probability of vehicle tracking. Theoretical developments are complemented by simulation experiments and an illustrative example using a section of road network from the English city of Leicester.     

The “Ubernomics” of ridesourcing: the myths and the reality

ABSTRACT

This paper looks at the economics of ridesourcing (or app-based ride-hailing) with a particular focus on the US. It brings together the rather dispersed literature on the subject focusing on the economic characteristics of the underlying industry and sets this within the broader context of transportation economics. In particular, it sorts out the realities of ridesourcing from some of myths that were perpetrated in its early days and, in many cases, still persist. It considers some of the empirical evidence that has emerged regarding the key parameters that determine the way Uber and the like operate, and the welfare implications of this, together with comments on some of the regulatory reactions to the new transportation platform. It concludes by suggesting some ways in which recent developments in economic could move forward our understanding of the industry as technologies and markets change.