Passenger Flows in Underground Railway Stations and Platforms, MTI Report 12-43

Urban rail systems are designed to carry large volumes of people into and out of major activity centers. As a result, the stations at these major activity centers are often crowded with boarding and alighting passengers, resulting in passenger inconvenience, delays, and at times danger. This study examines the planning and analysis of station passenger queuing and flows to offer rail transit station designers and transit system operators guidance on how to best accommodate and manage their rail passengers. The objectives of the study are to: 1) Understand the particular infrastructural, operational, behavioral, and spatial factors that affect and may constrain passenger queuing and flows in different types of rail transit stations; 2) Identify, compare, and evaluate practices for efficient, expedient, and safe passenger flows in different types of station environments and during typical (rush hour) and atypical (evacuations, station maintenance/ refurbishment) situations; and 3) Compile short-, medium-, and long-term recommendations for optimizing passenger flows in different station environments

Exploring rail futures using scenarios: experience and potential

In 1995 the author of this paper undertook a scenario exercise for British Rail to identify priorities for rail science and technology developments under the new privatised regime. Four marketbased 2010 scenarios were developed for UK rail transport: 1) cost driven; 2) quality driven, 3)technology driven and 4) environmentally driven. These helped to identify areas of strategic R&D that were needed to improve rail’s competitiveness. It is now over a decade since this scenario exercise took place. This paper, updating an earlier review (Potter and Roy, 2000), revisits the 1995 scenarios and compares them to what actual market strategies emerged within the privatised railway industry. It explores whether the four scenarios did succeed in capturing the range of market responses that emerged from rail privatisation and what lessons this contains for the use of scenarios transport research

The philosophy and practice of Taktfahrplan: a case-study of the East Coast Main Line.

Executive Summary This Working Paper has three purposes, represented by three Parts: - to explain the principles of the Taktfahrplan approach to railway timetabling; - to summarise the implications of the background research on the structure of the network; and - to describe the exercise of constructing a Taktfahrplan for the East Coast Main Line that formed the case-study of the potential benefits of such a scheme compared with the existing timetable. In Part I the broad principles and objectives are first outlined, and the advantages and disadvantages discussed [§ 1.1,1.2]. A Taktfahrplan is based on standard hours and the careful, network-wide coordination of sewices. It is recognised that ultimately the choice between this and conventional timetabling methods must depend on an evaluation of the loss of present flexibility to adjust to time-specific market demands against the gains from enhanced connectivity and from the fact of regularity. Issues concerning resources and the management of peak periods are also explained. Terminology is then dealt with because words and phrases are being used with imprecise and various meanings [§1.3]. There follows a detailed account of the arithmetic rules through which the ideal relationships between train (and bus) sewices can be attained, together with an explanation of the measures that can be taken to make the best compromises in the face of the characteristics of the real network - or to adjust it over time [§ 1.4]. In Part 2 the research to highlight features of the underlying demand for travel is described. This is not a necessary component of strategic timetable planning, but it is argued that it is desirable in order both to break free from the historical baggage and to seize the business, environmental and social-policy opportunities that a 'clean- sheet' timetable would present [§2.1]. The provisional findings from this work (it was left incomplete for reasons that are explained) are then deployed to form the skeleton of a national network connecting 100 important centres with 158 links. This is followed by an analysis of the very variable standards of the rail timetable on those links and of the road competition and by an account of some first thoughts as to how a full-scale Taktfahrplan might start to be developed on this network [§2.2]. This emphasises the inter-relationships between sewices and the inescapable consequences for pathing trains, once it is accepted that sensible spacing of services and striving for good connectivity are more important than optimising routes on a self-contained basis. It was thought appropriate to include a summary of the findings regarding the low-density end of the current rail system in order to indicate the issues that Taktfahrplan might raise in this respect [§2.3]. The East Coast case-study is presented in Part 3. Some technical matters are explained first, including the key point that the exercise used the Viriato timetabling software employed by the Swiss Federal Railways (and many other systems) to construct Taktfahrpliine [§3.1]. Successive sub-parts then describe groups of services: long-distance [§3.2], services within Scotland [§3.3], services in North East England [§3.4], the trans-Pennine network [§3.5] and some of the Yorkshire services [§3.6]

OPTIMIZATION OF STATION LOCATIONS AND TRACK ALIGNMENTS FOR RAIL TRANSIT LINES

Designing urban rail transit systems is a complex problem, which involves the determination of station locations, track geometry, right-of-way type, and various other system characteristics. The existing studies overlook the complex interactions between railway alignments and station locations in a practical design process. This study proposes a comprehensive methodology that helps transit planners to concurrently optimize station locations and track alignments for an urban rail transit line. The modeling framework resolves the essential trade-off between an economically efficient system with low initial and operation cost and an effective system that provides convenient service for the public. The proposed method accounts for various geometric requirements and real-world design constraints for track alignment and stations plans. This method integrates a genetic algorithm (GA) for optimization with comprehensive evaluation of various important measures of effectiveness based on processing Geographical Information System (GIS) data. The base model designs the track alignment through a sequence of preset stations. Detailed assumptions and formulations are presented for geometric requirements, design constraints, and evaluation criteria. Three extensions of the base model are proposed. The first extension explicitly incorporates vehicle dynamics in the design of track alignments, with the objective of better balancing the initial construction cost with the operation and user costs recurring throughout the system's life cycle. In the second extension, an integrated optimization model of rail transit station locations and track alignment is formulated for situations in which the locations of major stations are not preset. The concurrent optimization model searches through additional decision variables for station locations and station types, estimate rail transit demand, and incorporates demand and station cost in the evaluation framework. The third extension considers the existing road network when selecting sections of the alignment. Special algorithms are developed to allow the optimized alignment to take advantage of links in an existing network for construction cost reduction, and to account for disturbances of roadway traffic at highway/rail crossings. Numerical results show that these extensions have significantly enhanced the applicability of the proposed optimization methodology in concurrently selecting rail transit station locations and generating track alignment

Applications of Genetic Algorithm and Its Variants in Rail Vehicle Systems: A Bibliometric Analysis and Comprehensive Review

Railway systems are time-varying and complex systems with nonlinear behaviors that require effective optimization techniques to achieve optimal performance. Evolutionary algorithms methods have emerged as a popular optimization technique in recent years due to their ability to handle complex, multi-objective issues of such systems. In this context, genetic algorithm (GA) as one of the powerful optimization techniques has been extensively used in the railway sector, and applied to various problems such as scheduling, routing, forecasting, design, maintenance, and allocation. This paper presents a review of the applications of GAs and their variants in the railway domain together with bibliometric analysis. The paper covers highly cited and recent studies that have employed GAs in the railway sector and discuss the challenges and opportunities of using GAs in railway optimization problems. Meanwhile, the most popular hybrid GAs as the combination of GA and other evolutionary algorithms methods such as particle swarm optimization (PSO), ant colony optimization (ACO), neural network (NN), fuzzy-logic control, etc with their dedicated application in the railway domain are discussed too. More than 250 publications are listed and classified to provide a comprehensive analysis and road map for experts and researchers in the field helping them to identify research gaps and opportunities

High-Speed Projects in the United States: Identifying the Elements for Success-Part 1, MTI Report 05-01

For almost half a century, high-speed ground transportation (HSGT) has held the promise of fast, convenient, and environmentally sound travel for distances between 40 and 600 miles. While a number of HSGT systems have been developed and deployed in Asia and Europe, none has come close to being implemented in the United States. Yet this is not for lack of trying. There have been several efforts around the country, most of which have failed, some of which are still in the early stages, and a few of which might come to pass. The goal of this study was to identify lessons learned for successfully developing and implementing high-speed rail (HSR) in the United States. Through a broad literature review, interviews, and three specific case studies—Florida, California, and the Pacific Northwest—this study articulates those lessons and presents themes for future consideration

National Multi-Modal Travel Forecasts. Literature Review: Aggregate Models

This paper reviews the current state-of-the-art in the production of National Multi-Modal Travel Forecasts. The review concentrates on the UK travel market and the various attempts to produce a set of accurate, coherent and credible forecasts. The paper starts by a brief introduction to the topic area. The second section gives a description of the background to the process and the problems involved in producing forecasts. Much of the material and terminology in the section, which covers modelling methodologies, is from Ortúzar and Willumsen (1994). The paper then goes on to review the forecasting methodology used by the Department of Transport (DoT) to produce the periodic National Road Traffic Forecasts (NRTF), which are the most significant set of travel forecasts in the UK. A brief explanation of the methodology will be given. The next section contains details of how other individuals and organisations have used, commented on or attempted to enhance the DoT methodology and forecasts. It will be noted that the DoT forecasts are only concerned with road traffic forecasts, with other modes (rail, air and sea) only impacting on these forecasts when there is a transfer to or from the road transport sector. So the following sections explore the attempts to produce explicit travel and transportation forecasts for these other modes. The final section gathers together a set of issues which are raised by this review and might be considered by the project

National Multi-Modal Travel Forecasts. Literature Review: Aggregate Models

This paper reviews the current state-of-the-art in the production of National Multi-Modal Travel Forecasts. The review concentrates on the UK travel market and the various attempts to produce a set of accurate, coherent and credible forecasts. The paper starts by a brief introduction to the topic area. The second section gives a description of the background to the process and the problems involved in producing forecasts. Much of the material and terminology in the section, which covers modelling methodologies, is from Ortúzar and Willumsen (1994). The paper then goes on to review the forecasting methodology used by the Department of Transport (DoT) to produce the periodic National Road Traffic Forecasts (NRTF), which are the most significant set of travel forecasts in the UK. A brief explanation of the methodology will be given. The next section contains details of how other individuals and organisations have used, commented on or attempted to enhance the DoT methodology and forecasts. It will be noted that the DoT forecasts are only concerned with road traffic forecasts, with other modes (rail, air and sea) only impacting on these forecasts when there is a transfer to or from the road transport sector. So the following sections explore the attempts to produce explicit travel and transportation forecasts for these other modes. The final section gathers together a set of issues which are raised by this review and might be considered by the project

An elastic demand schedule-based multimodal assignment model for the simulation of high speed rail (HSR) systems

HSR represents the future of medium-haul intercity transport. In fact, a number of HSR projects are being developed all over the world despite the financial and economic crisis. Such large investments require reliable demand forecasting models to develop solid business plans aiming at optimizing the fares structure and the timetables (operational level) and, on the other hand, at exploring opportunities for new businesses in the long period (strategic level). In this paper we present a model system developed to forecast the national passenger demand for different macroeconomic, transport supply, and HSR market scenarios. The core of the model is based on the simulation of the competition between transportation modes (i.e. air, auto, rail), railways services (intercity vs. High Speed Rail) and HSR operators using an explicit representation of the timetables of all competing modes\services (schedule-based assignment). This requires, in turn, a diachronic network representation of the transport supply for scheduled services and a nested logit model of mode, service, operator, and run choice. To authors’ knowledge this represents the first case of elastic demand, schedule-based assignment model at national scale to forecast HSR demand. The overall modeling framework has been calibrated based on extensive traffic counts and mixed RP-SP interviews gathered between 2009 and 2011, on the Italian multimodal transportation system. The results of the models estimation are presented, and, some applications to test HSR service options (i.e. fares and timetable) of a new operator entering the HSR market and competing with the national incumbent are discussed