Simon Blainey

Barriers to passenger rail use: a review of the evidence

Research has shown that even when rail travel is the most cost-effective mode of transport for a particular journey, many travellers will still choose other modes. This indicates the existence of non-financial barriers to rail use, and this paper reviews the evidence on the importance of such barriers, focusing particularly on the UK but also considering research from other countries. A total of 37 distinct barriers were identified, and these can be divided into “hard”, “soft” and “complementary” factors. Travellers are unlikely to consider these barriers individually, viewing them instead as a package, which can make it difficult to identify which barriers are most significant. In many cases, all barriers which exist for a particular traveller will need to be addressed before mode shift occurs. After considering the relative importance of the different barriers, the paper concludes by making some suggestions as to the most effective ways in which these barriers can be overcome and mode shift to rail achieved. This has key implications for transport policy, as it can inform the targeting of the limited funds available to influence travel behaviour and increase the sustainability of travel patterns.

Following the cognitive work analysis train of thought: exploring the constraints of modal shift to rail transport

Environmental concerns show that transport is responsible for almost a quarter of all greenhouse gas emissions, and it is also the fastest growing sector. Modal shift towards public transport could help slow down, or even reverse, this trend. There appear to be a number of constraints that are preventing this from happening. This paper explores the constraints to modal shift to rail transport from the perspective of cognitive work analysis, specifically the abstraction hierarchy, the contextual activity template and social organisational and cooperation analyses. Whilst these analyses may not present any new barriers, they do show how the constraints are interlinked in an explicit manner. These interrelations are important for two reasons. First, in consideration of constraint removal, one must anticipate the likely effects on the remainder of the system. Second, by linking functions and situations, new concepts of travel may be identified and explored. Practitioner Summary: The purpose of this study was to use a semi-structured approach to identifying constraints to modal shift from a variety of perspectives. It is argued that cognitive work analysis offers a new way of thinking about the modal shift problem and helps to generate new insights into potential solutions.

Modelling local rail demand in South Wales

Abstract Direct demand models have been developed based on ticket sales data for 85 local rail stations in South Wales. Initially log-linear regression models were calibrated, incorporating a variety of independent variables. Geographical Information Systems were used to implement flexible station catchment definition methods, notably flow-specific catchments where population units were allocated to stations by minimising the total travel time to individual destinations. To validate these methods a survey of ultimate trip end locations was carried out on the Rhymney line in South Wales. To give consistency with predictions from trip end models, methods were developed to constrain predicted trip numbers for each flow based on the total trips observed or predicted from origin stations. Simple scaling had only limited success, so probabilistic trip distribution models were calibrated by using both the linear and non-linear regression. These gave superior results and explicitly incorporated the effects of intervening opportunities in the model form.

Railway station choice modelling: a review of methods and evidence

ABSTRACT Since the first railway station choice studies of the 1970s, a substantial body of research on the topic has been completed, primarily in North America, the U.K. and the Netherlands. With many countries seeing sustained growth in rail passenger numbers, which is forecast to continue, station choice models have an important role to play in assessing proposals for new stations or service changes. This paper reviews the modelling approaches adopted, the factors found to influence station choice and the application of models to real-world demand forecasting scenarios. A consensus has formed around using the closed-form multinomial logit and nested logit models, with limited use of more advanced simulation-based models, and the direction effects of a range of factors have been consistently reported. However, there are questions over the validity of applying non-spatial discrete choice models to a context where spatial correlation will be present, in particular with regard to the models’ ability to adequately represent the abstraction behaviours resulting from competition between stations. Furthermore, there has been limited progress towards developing a methodology to integrate a station choice element into the aggregate models typically used to forecast passenger demand for new stations.

Resilience engineering: theory and practice in interdependent infrastructure systems

The economy and well-being of modern societies relies on complex and interdependent infrastructure systems to enable delivery of utilities and movement of goods, people and services. This complexity has resulted in an increased potential for cascading failures, whereby small scale initial failures in one system can result in events of catastrophic proportions across the wider network. Resilience and the emerging concept of resilience engineering within infrastructure are among the main concerns of those managing such complex systems. However, the disparate nature of resilience engineering development in various academic and industrial regimes has resulted in a diversity of definitions and characterisations. These are discussed in this paper, as are the commonalities between sectors and between different engineering disciplines. The paper also highlights the various methodologies used as part of resilience engineering implementation and monitoring, current practices including existing approaches and metrics, and an insight into the opportunities and potential barriers associated with these methodologies and practices. This research was undertaken for the Resilience Shift initiative to shift the approach to resilience in practice for critical infrastructure sectors. The programme aims to help practitioners involved in critical infrastructure to make decisions differently, contributing to a safer and better world.

Development of railway station choice models to improve the representation of station catchments in rail demand models

ABSTRACT This paper describes the development of railway station choice models suitable for defining probabilistic station catchments. These catchments can then be incorporated into the aggregate demand models typically used to forecast demand for new rail stations. Revealed preference passenger survey data obtained from the Welsh and Scottish Governments was used for model calibration. Techniques were developed to identify trip origins and destinations from incomplete address information and to automatically validate reported trips. A bespoke trip planner was used to derive mode-specific station access variables and train leg measures. The results from a number of multinomial logit and random parameter (mixed) logit models are presented and their predictive performance assessed. The models were found to have substantially superior predictive accuracy compared to the base model (which assumes the nearest station has a probability of one), indicating that their incorporation into passenger demand forecasting methods has the potential to significantly improve model predictive performance.

Installation of under sleeper pads on ballasted railway tracks: An economic analysis of their potential implementation:

This study examines the economic impact of installing under sleeper pads in two different routes in the UK: the London-Portsmouth line and a section of the East Coast Main Line. The Portsmouth line is a typical suburban route with a high proportion of commuters whereas the East Coast Main Line is a higher speed line with less users and more distance between stations. The cost implications of this intervention are assessed through a stochastic application of cost benefit analysis underpinned with a sensitivity analysis. Using an industry-specific model, vehicle track interaction strategic model, as well as the results of laboratory experiments conducted at the University of Southampton, we are able to offer a set of conclusions. Increased reliability, improved ride quality and reduced vibration are important benefits for the users, higher in total terms on the Portsmouth line than on the East Coast Main Line, but smaller when the comparison is made on a per capita basis. In other words, the investment brings a higher absolute efficiency gain for the Portsmouth line but a higher relative efficiency gain for the East Coast Main Line. It is found that under sleeper pads can lead to substantial financial savings; these are higher for the East Coast Main Line than the Portsmouth line. Finally, depending on assumptions concerning noise impacts, under sleeper pads are likely to have substantial wider social benefits; these are much higher for the Portsmouth line than the East Coast Main Line. Although these conclusions are based on a UK case study, they could be applicable to any railway operation in a developed region facing high maintenance costs and growing demand.

Using GIS to assess the potential for centralised planning of bus networks

ABSTRACT The current regulatory and planning environment means that road-based public transport in UK urban areas (with the exception of London) tends to be planned on a piecemeal basis, and there are often conflicts between the needs and priorities of operators, passengers and planners. In consequence, several local authorities are considering adopting an alternative regulatory environment using quality contracts, with a consequent shift towards centralised service planning. There are though no tools readily available to ensure this centralised service planning will lead to a situation, which provides a better balance between the interests of the different stakeholders. This paper describes the development of a methodology to fill this gap, using Southampton as a case study to explore the corresponding improvement methods, which could be applied based on the alternative regulatory environment. The improvement methods, including both bus route design and frequency setting, are considered in this paper, which demonstrates how this service improvement problem can be solved by making use of an optimisation technique, the tabu search algorithm, developed under the environment of ArcObjects for Java. While the methodology is developed in the UK context, the general principles used could be applied more widely to improve transit network planning.

REDUCING MAINTENANCE COSTS FOR BALLASTED TRACK: EVIDENCE FROM BRITAIN

Over the last twenty years, the railways in Britain have seen rapid growth, with patronage doubling and the level of train service increasing by 50%. However, these successes have also led to challenges. In particular real unit costs are estimated to have increased by 50%, with particularly marked increases in infrastructure renewal and enhancement costs. Against this background, the University of Southampton have been leading the Track 21 and Track to the Future projects, funded by the Engineering and Physical Sciences Research Council. These projects are assessing how to make ballasted track systems more durable given higher traffic levels, and how to reduce the costs of maintenance and renewal. Track 21 considered a number of engineering interventions of which this paper focusses on one, Under Sleeper Pads (USPs). The cost implications of this intervention are assessed for the South West Main Line using an industry-specific model, VTISM (Vehicle Track Interaction Strategic Model), adapted in two ways. First, the results of laboratory experiments from specialist test rigs are incorporated into the model. Secondly, the wider effects of increased reliability, improved ride quality and reduced vibration are also considered within a costbenefit analysis framework. It is found that USPs can lead to substantial financial savings and, depending on assumptions concerning noise impacts, are likely to have substantial wider social benefits.

Defining probability-based rail station catchments for demand modelling

The aggregate models commonly used in the UK to estimate demand for new local rail stations require the station catchment to be defined first, so that inputs into the model, such as the population from which demand will be generated, can be specified. The methods typically used to define the catchment implicitly assume that station choice is a deterministic process, and that stations exist in isolation from each other. However, studies show that pre-defined catchments account for only 50-60 percent of observed trips, choice of station is not homogeneous within zones, catchments overlap, and catchments vary by access mode and station type. This paper describes early work to implement an alternative probability-based approach, through the development of a station choice prediction model. To derive realistic station access journey explanatory variables, a routable multi-modal network, incorporating data from OpenStreetMap, the Traveline National Data Set and National Rail timetable, was built using OpenTripPlanner and queried using an API wrapper developed in R. Results from a series of multinomial logit models are presented and a method for generating probabilistic catchments using estimated parameter values is described. An example probabilistic catchment is found to provide a realistic representation of the observed catchment, and to perform better than deterministic catchments.