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Dive into the research topics where Stephen D. Clark is active.

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Featured researches published by Stephen D. Clark.


Transportation Research Part B-methodological | 2002

Sensitivity analysis of the probit-based stochastic user equilibrium assignment model

Stephen D. Clark; David Watling

Abstract The probit-based stochastic user equilibrium (SUE) model has the advantage of being able to represent perceptual differences in utility across the driver population, while taking proper account of the natural correlations in these utilities between overlapping routes within the network (which the simpler logit SUE is unable to do). Its main drawback is the potentially heavy computational demands, and this has previously been thought to preclude a consideration of the sensitivity analysis of probit-based SUE, whereby an approximation to changes in the equilibrium solution is deduced as its input parameters (specifically origin/destination (O–D) flows and link cost-flow function parameters) are perturbed. In the present paper, an efficient computational method for performing such an analysis for general networks is described. This approach uses information on SUE path flows, but is not specific to any particular equilibrium solution algorithm. Problems inherent in the consideration of general network topologies are identified, and methods proposed for overcoming them. The paper concludes with an application of the method to a realistic network, and compares the approximate solutions with those obtained by direct estimation methods.


Transportation Research Record | 2000

PROBIT-BASED SENSITIVITY ANALYSIS FOR GENERAL TRAFFIC NETWORKS

Stephen D. Clark; David Watling

The probit-based stochastic user-equilibrium (SUE) model is widely recognized as one of the most intuitively robust traffic network assignment techniques. Its advantages include explicit consideration of random perceptual differences in utility across the driver population and the ability to take proper account of the correlations in these utilities between overlapping routes, which the simpler logit SUE is unable to do. Its main drawback is the potentially heavy computational demands of the method, but various efficient approximation methods have been observed to provide reasonable solutions. This computational complexity was previously, however, thought to preclude a consideration of the sensitivity analysis of probit-based SUE, whereby an approximation to changes in the equilibrium solution is deduced as its input parameters are perturbed. An efficient computational method for performing such an analysis in general networks is described. A simple network example is described in detail to illustrate the method, and it is followed by a larger network example that further demonstrates the practical nature of the method.


Transportation Research Record | 2002

Cleaning of Matched License Plate Data

Stephen D. Clark; Susan Grant-Muller; Haibo Chen

Three methods for identifying outlying journey time observations collected as part of a motorway license plate matching exercise are presented. Each method is examined to ensure that it is comprehensible to transport practitioners, is able to correctly classify outliers, and is efficient in its application. The first method is a crude method based on percentiles. The second uses a mean absolute deviation test. The third method is a modification of a traditional z- or t-statistical test. Results from each method and combinations of methods are compared. The preferred method is judged to be the third method alone, which uses the median rather than the mean as its measure of location and the inter-quartile range rather than the standard deviation as its measure of variability. This method is seen to be robust to both the outliers themselves and the presence of incident conditions. The effectiveness of the method is demonstrated under a number of typical and atypical road traffic conditions. In particular, the method is applied to a different section of motorway and is shown to still produce useful results.


Health & Place | 2014

Sub regional estimates of morbidities in the English elderly population.

Stephen D. Clark; Mark Birkin; Alison J. Heppenstall

This study focuses on identifying the future trends and spatial concentrations of morbidities in the English elderly population. The morbidities to be estimated are: coronary heart disease; strokes; diabetes; cancer; respiratory illnesses and arthritis in the 60 year and older household residential population. The technique used is a spatial microsimulation of the elderly population of local authorities in England using data from the 2001 Census and the English Longitudinal Study of Ageing. The longitudinal nature of the microsimulated population is then used to estimate the morbidity prevalences for local authorities in 2010/2011. With this knowledge, planners will be able to focus the available health and care resources in those areas with greatest need. For most of these morbidities, there is evidence of a strong correlation between the type of authority and the estimated prevalence rates.


Transportation Research Record | 2000

Cycling and Urban Traffic Management and Control Systems

Stephen D. Clark; Matthew W. Page

Since the 1950s, cycling has been a declining mode of travel in the United Kingdom. During this same period, sophisticated techniques for managing traffic in the urban environment have been developed. Given these circumstances, the presence of cyclists is often ignored by urban traffic control (UTC) systems, which are dominated by consideration of the flows and journey times of private motorized vehicles. Authorities are enthusiastic about the promotion of cycling as a mode of travel and are looking to see if this can be assisted by use of traffic management systems. The fact that cyclists and potential cyclists vary considerably in their abilities and performance, as well as in their attitudes to timesaving and safety, is highlighted. The context of the problem is set, the specific issue of detection of cycles is examined, the potential for implementation of priority measures in different types of UTC systems is discussed, and the issue is illustrated with some actual installations. Limited European evidence would suggest that only minimum effort is needed to take explicit account of cycling when a UTC system is being implemented. This supports the idea that cyclists can be given a higher degree of consideration within a UTC system without incurring significant additional costs. Only when cycling achieves a near-dominant proportion of the trips within a city and is growing in volume, as is the case in China, is explicit consideration to cyclists given.


Archive | 2017

Using the 2001 and 2011 Censuses to reconcile ethnic group estimates and components for the intervening decade for English local authority districts

Philip Rees; Stephen D. Clark; Pia Wohland; Nik Lomax; Paul Norman

This chapter describes the creation of new estimates of ethnic populations and components of change in local authority districts (LADs) in England for years between the 2001 and 2011 Censuses. Information on ethnic populations by age and gender is provided in censuses. In between censuses, information on ethnic population change is scarce. To fill the gap we used data from the two censuses with reconciled total population and component estimates published by the Office of National Statistics. This chapter outlines the sequence of steps used to produce a ten-year time series. These reconciled population and component estimates provide a firmer foundation for ethnic-specific projections than hitherto available. The role of the census in this work is vital.


Archive | 2017

Population Projections by Ethnicity: Challenges and a Solution for the United Kingdom

Philip Rees; Pia Wohland; Paul Norman; Nikolas Lomax; Stephen D. Clark

This chapter describes the context, model, estimates and assumptions for projections of ethnic group populations in England at local authority scale, and in Wales, Scotland and Northern Ireland. A bi-regional cohort-component model is used; estimates of the component rates for ethnic groups are developed; assumptions are aligned to recent official projections with one exception. For international migration we assume higher immigration, emigration and net balances of 254 thousand in the long term compared with the most recent official assumption of 185 thousand. The projections show that the UK population grows significantly, from a population of 59.1 million in 2001 to 84.5 million in 2061. Black, Asian and other Minority ethnic groups expand their share of the UK population from 8 to 30 % in that period. This increasing diversity is greatest in the UK’s largest cities but ethnic minority groups grow fastest outside those cities. We show through a comparison of 2001 based and 2011 based projections that there is considerable uncertainty both nationally and locally in future diversity although the direction of travel to a more diverse future is certain.


EPJ Data Science | 2017

Classification of Westminster Parliamentary constituencies using e-petition data

Stephen D. Clark; Nik Lomax; Michelle A. Morris

In a representative democracy it is important that politicians have knowledge of the desires, aspirations and concerns of their constituents. Opportunities to gauge these opinions are however limited and, in the era of novel data, thoughts turn to what alternative, secondary, data sources may be available to keep politicians informed about local concerns. One such source of data are signatories to electronic petitions (e-petitions). Such e-petitions have risen greatly in popularity over the past decade and allow members of the public to initiate and sign an e-petition online, with popular e-petitions resulting in media attention, a response from the government or ultimately a debate in parliament. These data are thus novel in their availability and have not yet been widely used for research purposes. In this article we will use the e-petition data to show how semantic classes of Westminster Parliamentary constituencies, fitted as Gaussian finite mixture models via EM algorithm, can be used to typify constituencies. We identify four classes: Domestic Liberals; International Liberals; Nostalgic Brits and Rural Concerns, and illustrate how they map onto electoral results. The findings and the utility of this approach to incorporate new e-petitions and adapt to changes in electoral geography are discussed.


Journal of Maps | 2015

Mapping car ownership in Great Britain over four decades

Stephen D. Clark

This article describes a methodology for mapping the level of household car ownership for the island of Great Britain, using data from five population Censuses. The basic units of display are ‘Tracts’, which are aggregations of local municipality electoral wards that were in place for each of the three Censuses conducted in 1981, 1991 and 2001. In addition, this article documents the utility of these Tracts to represent a consistent geography across two additional Censuses, those of 1971 and 2011. This analysis enables a consistent and complete picture of changes in car ownership over a 40-year period to be visualised as both geographical maps and cartograms of Great Britain. The advantages and disadvantages of each type of representation are discussed. The paper finishes by providing evidence of a downward trend in car ownership in central London and increasing spatial homogeneity in car ownership through time.


Journal of Information Technology & Politics | 2018

Estimating the outcome of UKs referendum on EU membership using e-petition data and machine learning algorithms

Stephen D. Clark; Michelle A. Morris; Nik Lomax

ABSTRACT The United Kingdom’s 2016 referendum on membership of the European Union is perhaps one of the most important recent electoral events in the UK. This political sentiment has confounded pollsters, media commentators and academics alike, and has challenged elected Members of the Westminster Parliament. Unfortunately, for many areas of the UK this referendum outcome is not known for Westminster Parliamentary Constituencies, rather it is known for the coarser geography of counting areas. This study uses novel data and machine learning algorithms to estimate the Leave vote percentage for these constituencies. The results are seen to correlate well with other estimates.

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