User perspectives in public transport timetable optimisation

The present paper deals with timetable optimisation from the perspective of minimising the waiting time experienced by passengers when transferring either to or from a bus. Due to its inherent complexity, this bi-level minimisation problem is extremely difficult to solve mathematically, since timetable optimisation is a non-linear non-convex mixed integer problem, with passenger flows defined by the route choice model, whereas the route choice model is a non-linear non-continuous mapping of the timetable. Therefore, a heuristic solution approach is developed in this paper, based on the idea of varying and optimising the offset of the bus lines. Varying the offset for a bus line impacts the waiting time passengers experience at any transfer stop on the bus line.In the bi-level timetable optimisation problem, the lower level is a transit assignment calculation yielding passengers’ route choice. This is used as weight when minimising waiting time by applying a Tabu Search algorithm to adapt the offset values for bus lines. The updated timetable then serves as input in the following transit assignment calculation. The process continues until convergence.The heuristic solution approach was applied on the large-scale public transport network in Denmark. The timetable optimisation approach yielded a yearly reduction in weighted waiting time equivalent to approximately 45 million Danish kroner (9 million USD).     

Short-term forecasting of high-speed rail demand: A hybrid approach combining ensemble empirical mode decomposition and gray support vector machine with real-world applications in China

Short-term forecasting of high-speed rail (HSR) passenger flow provides daily ridership estimates that account for day-to-day demand variations in the near future (e.g., next week, next month). It is one of the most critical tasks in high-speed passenger rail planning, operational decision-making and dynamic operation adjustment. An accurate short-term HSR demand prediction provides a basis for effective rail revenue management. In this paper, a hybrid short-term demand forecasting approach is developed by combining the ensemble empirical mode decomposition (EEMD) and grey support vector machine (GSVM) models. There are three steps in this hybrid forecasting approach: (i) decompose short-term passenger flow data with noises into a number of intrinsic mode functions (IMFs) and a trend term; (ii) predict each IMF using GSVM calibrated by the particle swarm optimization (PSO); (iii) reconstruct the refined IMF components to produce the final predicted daily HSR passenger flow, where the PSO is also applied to achieve the optimal refactoring combination. This innovative hybrid approach is demonstrated with three typical origin–destination pairs along the Wuhan-Guangzhou HSR in China. Mean absolute percentage errors of the EEMD-GSVM predictions using testing sets are 6.7%, 5.1% and 6.5%, respectively, which are much lower than those of two existing forecasting approaches (support vector machine and autoregressive integrated moving average). Application results indicate that the proposed hybrid forecasting approach performs well in terms of prediction accuracy and is especially suitable for short-term HSR passenger flow forecasting.     

The management of the rural transportation problem in Nigeria

In spite of the fact that about 70% of Nigeria's population live in rural areas, these areas have remained largely inaccessible. Not only do they lack motorable roads and organized public transport but also field surveys indicate that nearly all rural inhabitants do not have a private car. A Directorate of Food, Roads and Rural Infrastructure has been set up to manage the inaccessibility problem, among others. Whereas there are several conventional approaches to the management of the rural transportation problem, the Nigerian approach relies on the provision of roads. This restrictive approach with an emphasis on locational to the neglect of personal accessibility has various limitations which are analysed.     

大坡度引水隧道无轨运输出渣方式的应用

辽西北供水工程11#支洞，断面小、坡度大，出渣运输方式是决定工期的关键控制因素。采用无轨运输出渣方式，存在以下问题：隧道纵坡坡度较大，运输渣车爬坡困难、存在严重的安全隐患；断面小，自卸车在陡坡上运行和洞内调头困难等。对此采取扩大隧道开挖断面、设置避车洞，改装车辆、确保车辆制动的可靠性；加强安全管理措施等。实践证明，采用无轨运输方式出渣具有节约工期、经济效益显著等特点，可根据实际工况加以选用。     

大型机场地面集疏运需求预测方法研究

机场地面集疏运系统是机场发展的重要支撑，交通需求预测是进行机场集疏运交通规划的前提。笔者以四阶段预测的基本原理为基础，结合机场集疏运需求特点，对预测的整体思路、方法、步骤和内容等进行详细分析，优化调整出行分布、方式划分预测模型，并以南京禄口国际机场为实例进行了预测。研究成果对国内同类大型机场的集疏运需求预测具有借鉴和参考价值。     

Innovative systems for the transportation disadvantaged: Toward more efficient and operationally usable planning tools

When considering innovative forms of public transport for specific groups, such as demand responsive services, the challenge is to find a good balance between operational efficiency and 'user friendliness' of the scheduling algorithm even when specialized skills are not available. Regret insertion-based processes have shown their effectiveness in addressing this specific concern. We introduce a new class of hybrid regret measures to understand better why the behaviour of this kind of heuristic is superior to that of other insertion rules. Our analyses show the importance of keeping a good balance between short- and long-term strategies during the solution process. We also use this methodology to investigate the relationship between the number of vehicles needed and total distance covered - the key point of any cost analysis striving for greater efficiency. Against expectations, in most cases decreasing fleet size leads to savings in vehicle mileage, since the heuristic solution is still far from optimality.     

基于城市轨道交通线网级的乘客信息系统建设研究

针对城市轨道交通乘客信息系统线网化后仍按传统方式构建存在资源浪费、管理困难、接口复杂繁多等诸多问题,提出建设线网级的乘客信息发布中心,实现对线网内PIS系统播出信息控制的思路,对线网级乘客信息系统系统架构、乘客信息发布中心构成进行重点研究。     

轨道交通车载智能应急电源系统

作为在紧急情况下为轨道交通列车辅助系统供电的应急电源,铅酸或镍铬电池被普遍使用;随着技术的不断发展,锂离子电池的应用也越来越广泛.介绍了GJCL-A型锂离子轨道交通车载智能应急电源系统的组成、工作原理、设计方案及试点应用情况.GJCL-A型锂离子轨道交通车载智能应急电源系统的试验应用结果表明,用于车厢的110V应急供电4 300 s后,其剩余电量仍有40％以上.     

强关联性地铁车站的界定及设计要点分析

强关联性车站作为一种新出现的车站形式其被界定的时机对车站方案设计影响重大,在设计阶段需要特别注意,及早甄别。通过定义强关联性车站,从其界定的最佳时机、基本分类以及隐蔽性强关联性车站设计实例,介绍强关联性车站界定要点说明,指出强关联性车站内在关联性以及判别的外在切入点。     

既有线钢轨焊接接头焊后综合处理系统的研制

介绍了既有线钢轨焊接接头焊后热处理、矫直及外形精整综合处理系统的总体结构、主要技术参数和性能特点。现场使用表明,样机采用感应加热、液压四向矫直和固定支点仿形打磨技术,自动化、专业化程度高,满足铁路标准规定的质量要求,提升了既有线维护质量和效率。