Door-to-door travel times in RP departure time choice models: An approximation method using GPS data

A common way to determine values of travel time and schedule delay is to estimate departure time choice models, using stated preference (SP) or revealed preference (RP) data. The latter are used less frequently, mainly because of the difficulties to collect the data required for the model estimation. One main requirement is knowledge of the (expected) travel times for both chosen and unchosen departure time alternatives. As the availability of such data is limited, most RP-based scheduling models only take into account travel times on trip segments rather than door-to-door travel times, or use very rough measures of door-to-door travel times. We show that ignoring the temporal and spatial variation of travel times, and, in particular, the correlation of travel times across links may lead to biased estimates of the value of time (VOT). To approximate door-to-door travel times for which no complete measurement is possible, we develop a method that relates travel times on links with continuous speed measurements to travel times on links where relatively infrequent GPS-based speed measurements are available. We use geographically weighted regression to estimate the location-specific relation between the speeds on these two types of links, which is then used for travel time prediction at different locations, days, and times of the day. This method is not only useful for the approximation of door-to-door travel times in departure time choice models, but is generally relevant for predicting travel times in situations where continuous speed measurements can be enriched with GPS data.     

Future electricity demand from battery‐powered vehicles

An important decision faced by airline schedulers is how to adapt the flight schedule and aircraft assignment to unforeseen perturbations in an established schedule. In the face of unforeseen aircraft delays, schedulers have to decide which flights to delay, and when delays become excessive, which to cancel. Current scheduling models deal with simple decision problems of delay or cancellation, but not with both simultaneously. But in practice the optimal decision may involve results from the integration of both flight cancellations and delays. In Part I of this paper, a quadratic programming model for the integration decision problem is given. The model can formulate the integration of flight cancellations and delays as well as some special cases, such as the ferrying of surplus aircraft and the possibility of swapping different types of aircraft. In this paper, based on the special structure of the model, an effective algorithm is presented, sufficient computational experiments are conducted and some results are reported. These show that we can expect to obtain a sufficiently good solution in terms of reasonable CPU time.     

Bus running time prediction using a statistical pattern recognition technique

Abstract

Given that real-time bus arrival information is viewed positively by passengers of public transit, it is useful to enhance the methodological basis for improving predictions. Specifically, data captured and communicated by intelligent systems are to be supplemented by reliable predictive travel time. This paper reports a model for real-time prediction of urban bus running time that is based on statistical pattern recognition technique, namely locally weighted scatter smoothing. Given a pattern that characterizes the conditions for which bus running time is being predicted, the trained model automatically searches through the historical patterns which are the most similar to the current pattern and on that basis, the prediction is made. For training and testing of the methodology, data retrieved from the automatic vehicle location and automatic passenger counter systems of OC Transpo (Ottawa, Canada) were used. A comparison with other methodologies shows enhanced predictive capability.     

基于广西旅游业的道路客运发展探析

文章针对广西道路旅客运输的现状及广西道路客运企业发展旅游业的优越条件,以＂运游结合＂为切入点,介绍以快捷优质的客运服务带动＂慢旅游＂道路客运企业发展旅游业的新模式,对采取＂运游结合＂经营模式,提高服务质量,发展＂慢旅游＂提出了相关的建议。     

TD-LTE技术承载地铁集群通信业务问题研究

3GPP LTE协议的设计初衷是为普通商业和消费型通信服务提供高移动性及高带宽的数据业务,当前并未提供完备的集群解决方案。TD-LTE(时分-长期演进)技术用于承载地铁多媒体集群业务的应用前景,已得到了轨道交通建设各方的高度关注。通过结合成熟集群通信的业务特征,分析TD-LTE技术自身的技术特点,归纳出TD-LTE承载地铁集群通信业务所存在的主要问题,并提出相应的解决思路,为其承载关键型集群通信业务的应用提供一些参考。     

定时、定线路上下班拼车方案实现与评价——以淮安为试点

因信息不畅、费用不统一、违法犯罪时有发生和法律界定不明确等问题,导致私家车拼车市场发展缓慢.设计了以淮安为试点的定时、定线路上下班拼车方案,搭建了拼车信息平台,实现了拼车的信息检索、信息配对、双方互选、双方互评等功能,并利用时间费用阻抗评价模型和Vissim仿真对该实施后的方案进行评价,结果表明该方案可使时间费用阻抗减少65%~86%,拼车路网中平均车速提高17.83%、总停车延误时间减少34.84%、总行驶时间减少28.29%、总延误时间减少40.89%、平均延误时间减少29.23%.方案在淮安试点表明,该方案能较大地减少拼车过程中的出行时间和出行费用,改善拼车区域路网交通拥堵状况,提高拼车过程的安全性和经济性.      

基于RFID和视频监测的城市交通运行状态模糊判别

为了确定城市道路网路的交通状态,为主动的交通管理、交通诱导及控制提供支持,提出了一种基于无线射频识别(RFID)交通检测系统和视频监控系统的交通运行状态模糊判别方法.在该方法中,交通运行状态由从RFID系统获得的车辆行驶时间和从视频监控系统中获得的车辆速度决定.由于实际的交通状态可以从视频中直接观测,因此实际交通运行状态的阈值可以根据视频来校准,用以评估本文所提出方法的性能.基于安装于南京的RFID和视频交通检测系统进行实证分析,结果表明本文所提出的方法是可行的.下一步工作可推进交通数据,特别是 RFID数据在交通管理中的应用.     

基于城市交通容量分析的公交优先研究 ——以广州为例

基础设施扩容为主的道路交通和轨道交通建设,成为目前各大城市普遍采取的治理城市交通拥堵的主要手段,由于轨道交通建设存在资金和建设时间持续问题,如何对有限的道路交通资源重新划分成为治堵工作的关键.本文以综合交通模型为基础,形成以地面公交路权优先为突破口的交通系统容量优化方法,提出交通系统人次容量定义,构建度量舒适性和可控性的评判标准,建立层次化的公交专用道布设方法,动态调整地面公交和小汽车的路网资源比,保障地面公交路权,达到小汽车和公交出行时耗的相对均衡,实现交通的个体最优向系统最优的转化,形成一条落实公交优先的新路径.最后以广州市为例,将容量分析技术应用到实际路网,提出以公交专用道方案为主的道路资源定量分配方案,落实公交优先,指导广州市交通发展.     

高速铁路路基结构空间时变系统耦合动力分析

考虑高速线路的实际工况,建立了包括轨道结构和车辆的路基结构空间时变动力系统分析模型.将线路结构及车辆离散为不同的单元,采用能量原理导出了系统动力方程,进一步建立了系统动力矩阵.作为模型的验证,对连续谐波不平顺条件下系统动力响应进行了分析,得出了车辆走行过程中的车体加速度、动轮载以及基床动应力、基床动变形等动态响应结果.计算结果表明,本文中的计算模型是合理的.     

弹性需求下多类型用户拥挤收费模型

基于时间价值不同的多类型用户特性,提出了弹性需求下多类型用户的拥挤收费模型,并以一个简化的路网实例比较了多类型用户收费模型与单一类型用户收费模型的区别。简化实例分析结果表明:当费率水平较低时,单一类型用户收费模型高估了路网的流量、社会效益,当费率水平较高时,则低估了路网的流量和社会效益;同时单一类型用户收费模型的路网社会效益和利润区域对应的道路通行能力区间较宽,费率水平区间窄,而多类型用户收费模型的路网社会效益和利润区域对应的道路通行能力区间相对较窄,费率水平区间较宽。