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  • Journal article
    Ait Bihi Ouali L, Graham D, 2021,

    The impact of the MeToo scandal on women’s perceptions of security

    , Transportation Research Part A: Policy and Practice
  • Journal article
    Zhang N, Graham DJ, Hörcher D, Bansal Pet al., 2021,

    A causal inference approach to measure the vulnerability of urban metro systems

    , Transportation, ISSN: 0049-4488

    Transit operators need vulnerability measures to understand the level of service degradation under disruptions. This paper contributes to the literature with a novel causal inference approach for estimating station-level vulnerability in metro systems. The empirical analysis is based on large-scale data on historical incidents and population-level passenger demand. This analysis thus obviates the need for assumptions made by previous studies on human behaviour and disruption scenarios. We develop four empirical vulnerability metrics based on the causal impact of disruptions on travel demand, average travel speed and passenger flow distribution. Specifically, the proposed metrics based on the irregularity in passenger flow distribution extends the scope of vulnerability measurement to the entire trip distribution, instead of just analysing the disruption impact on the entry or exit demand (that is, moments of the trip distribution). The unbiased estimates of disruption impact are obtained by adopting a propensity score matching method, which adjusts for the confounding biases caused by non-random occurrence of disruptions. An application of the proposed framework to the London Underground indicates that the vulnerability of a metro station depends on the location, topology, and other characteristics. We find that, in 2013, central London stations are more vulnerable in terms of travel demand loss. However, the loss of average travel speed and irregularity in relative passenger flows reveal that passengers from outer London stations suffer from longer individual delays due to lack of alternative routes.

  • Journal article
    Singh R, Graham DJ, Anderson RJ,

    Quantifying the effects of passenger-level heterogeneity on transit journey times

    , Data-Centric Engineering, ISSN: 2632-6736

    In this paper we apply flexible data-driven analysis methods on large scale mass transit data to identify areas for improvement in the engineering and operation of urban rail systems. Specifically, we use data from automated fare collection (AFC) and automated vehicle location (AVL) systems to obtain a more precise characterisation of the drivers of journey time variance on the London Underground, and thus an improved understanding of delay. Total journey times are decomposed via a probabilistic assignment algorithm and semiparametric regression is undertaken to disentangle the effects of passenger-specific travel characteristics from network related factors. For total journey times, we find that network characteristics, primarily train speeds and headways, represent the majority of journey time variance. However, within the typically twice as onerous access and egress time components, passenger-level heterogeneity is more influential. On average, we find that intra-passenger heterogeneity represents 6% and 19% of variance in access and egress times, respectively, and that inter-passenger effects have a similar or greater degree of influence than static network characteristics. The analysis shows that while network-specific characteristics are the primary drivers journey time variance in absolute terms, a non-trivial proportion of passenger-perceived variance would be influenced by passenger-specific characteristics. The findings have potential applications related to improving the understanding of passenger movements within stations, for example, the analysis can be used to assess the relative way-finding complexity of stations, which can in turn guide transit operators in the targeting of potential interventions.

  • Journal article
    Ait Bihi Ouali L, Graham D, Trompet M, Barron Aet al., 2020,

    Gender differences in the perception of safety in public transport

    , Journal of the Royal Statistical Society Series A: Statistics in Society, Vol: 183, Pages: 737-769, ISSN: 0964-1998

    Concerns over women's safety on public transport systems are commonly reported in the media. In this paper we develop statistical models to test for gender differences in the perception of safety and satisfaction on urban metros and buses using large-scale unique customer satisfaction data for 28 world cities over the period 2009 to 2018. Results indicate a significant gender gap in the perception of safety, with women being 10\% more likely than men to feel unsafe in metros (6% for buses). This gender gap is larger for safety than for overall satisfaction (3% in metros and 2.5% in buses), which is consistent with safety being one dimension of overall satisfaction. Results are stable across specifications and robust to inclusion of city-level and time controls. We find heterogeneous responses by sociodemographic characteristics. Data indicates 45% of women feel secure in trains and metro stations (respectively 55% in buses). Thus the gender gap encompasses more differences in transport perception between men and women rather than an intrinsic network fear. Additional models test for the influence of metro characteristics on perceived safety levels and find that that more acts of violence, larger carriages, and emptier vehicles decrease women's feeling of safety.

  • Journal article
    Singh R, Graham DJ, Horcher D, Anderson RJet al., 2020,

    Decomposing journey time variance on urban metro systems via semiparametric mixed methods

    , Transportation Research Part C: Emerging Technologies, Vol: 114, Pages: 140-163, ISSN: 0968-090X

    The availability of automated data for urban metro systems allows operators to accurately measure journey time reliability. However, there remains limited understanding of the causes of journey time variance and how journey time performance can be improved. In this paper, we present a semiparametric regression modelling framework to determine the underlying drivers of journey time variance in urban metro systems, using the London Underground as a case study. We merge train location and passenger trip data to decompose total journey times into three constituent parts: access times as passengers enter the system, on-train times, and egress times as passengers exit at their destinations. For each journey time component, we estimate non-linear functional relationships which we then use to derive elasticity estimates of journey times with respect to service supply and demand factors, including operational and physical characteristics of metros as well as passenger demand and passenger-specific travel characteristics. We find that the static fixed physical characteristics of stations and routes have the greatest influence on journey time, followed by train speeds, and headways, for which the average elasticities of total journey time are −0.54 and 0.05, respectively. The results of our analysis could inform operators about where potential interventions should be targeted in order to improve journey time performance.

  • Journal article
    Morse L, Trompet M, Barron A, Anderson R, Graham Det al., 2020,

    A benchmarking framework for understanding bus performance in the U.S.

    , Benchmarking: an international journal, Vol: 27, Pages: 1533-1550, ISSN: 1463-5771

    Purpose This paper describes a benchmarking framework applied to medium-sized urban public bus agencies in the United States which has overcome the challenges of data quality, comparability and understanding.Design/methodology/approach The benchmarking methodology described in this paper is based on lessons learned through seven years of development of a fixed route key performance indicator (KPI) system for the American Bus Benchmarking Group (ABBG). Founded in 2011, the ABBG is a group of public medium-sized urban bus agencies that compare performance and share best practices with peers throughout the United States. The methodology is adapted from the process used within international benchmarking groups facilitated by Imperial College and consists of four main elements: peer selection, KPI system development, processes to achieve high-quality data, and processes to understand relative performance and change.Findings The four main elements of the ABBG benchmarking methodology consist of eighteen sub-elements, which when applied overcome three main benchmarking challenges; comparability, data quality, and understanding. While serving as examples for the methodology elements, the paper provides specific insights into service characteristics and performance among ABBG agencies.Research limitations/implications The benchmarking approach described in this paper requires time and commitment and thus is most suitably applied to a concise group of agencies. Practical implications This methodology provides transit agencies, authorities and benchmarking practitioners a framework for effective benchmarking. It will lead to high-quality comparable data and a strong understanding of the performance context to serve as a basis for organizational changes, whether for policy, planning, operations, stakeholder communication, or program development. Originality/value The methodology, while consistent with recommendations from literature, is unique in its scale, in-depth validation

  • Journal article
    Graham D, Niak C, McCoy EJ, Li Het al., 2019,

    Do speed cameras reduce road traffic collisions?

    , PLoS One, Vol: 14, ISSN: 1932-6203

    This paper quantifies the effect of speed cameras on road trafficcollisions using anapproximate Bayesian doubly-robust (DR) causal inference estimation method.Previous empirical work on this topic, which shows a diverse range ofestimatedeffects, is based largely on outcome regression (OR) models using the Empirical Bayesapproach or on simple before and after comparisons. Issues of causality andconfounding have received little formal attention. A causal DR approach combinespropensity score (PS) and OR models to give an average treatmenteffect (ATE)estimator that is consistent and asymptotically normal under correct specification ofeither of the two component models. We develop this approach withina novelapproximate Bayesian framework to derive posterior predictive distributions for theATE of speed cameras on road traffic collisions. Our results for England indicatesignificant reductions in the number of collisions at speed cameras sites (mean ATE =-15%). Our proposed method offers a promising approach for evaluation of transportsafety interventions.

  • Conference paper
    Ait Bihi Ouali L, Graham DJ, 2019,

    Gender Differences in the Perception of Safety in Transport: The case of subways

    , 8th hEART Conference
  • Journal article
    Graham D, Gibbons S, 2019,

    Quantifying wider economic impacts of agglomeration for transport appraisal: existing evidence and future directions

    , Economics of Transportation, Vol: 19, ISSN: 2212-0122

    This paper is concerned with the Wider Economic Impacts (WEIs) of transport improvements that arise via scale economies of agglomeration. It reviews the background theory and empirical evidence on agglomeration, explains the link between transport and agglomeration, and describes a three step procedure to appraise agglomeration impacts in a number of different settings. It includes new analytical work on measures of agglomeration and reports agglomeration-productivity elasticity estimates for the UK not previously published in the academic literature. The paper concludes with a set of recommendations for future empirical work on agglomeration and transport appraisal.

  • Journal article
    Li H, Graham DJ, Ding H, Ren Get al., 2019,

    Comparison of empirical Bayes and propensity score methods for road safety evaluation: a simulation study

    , Accident Analysis and Prevention, Vol: 129, Pages: 148-155, ISSN: 0001-4575

    Statistical evaluation of road safety interventions can be undertaken using a variety of different approaches, typically requiring different assumptions to obtain causal identification. In this paper, we conduct a simulation study to compare the performance of empirical Bayes (EB) and propensity score (PS) based methods, which have featured prominently in the recent literature, in settings with and without violation of key assumptions. The estimators considered include EB, inverse probability weighting (IPW), and Doubly Robust (DR) estimation. We find that while the EB approach has good finite sample properties when model assumptions are met, the consistency of this estimator is substantially diminished when the reference and treated sites follow different functions. The IPW estimator performs well in large samples, but requires a correctly specified PS model with sufficient overlap in covariate distributions between treated and control units. The DR estimator allows for violation of assumptions in either the regression or PS model, but not both. We find that this added level of robustness affords overall better performance than attained via EB or IPW estimation.

  • Journal article
    Singh R, Graham DJ, Anderson RJ, 2019,

    Characterizing journey time performance on urban metro systems under varying operating conditions

    , Transportation Research Record, Vol: 2673, Pages: 516-528, ISSN: 0361-1981

    Automated fare collection (AFC) data provide opportunities for improved measurement of public transport service quality from the passenger perspective. In this paper, AFC data from the London Underground are used to measure service quality through an analysis of journey time performance under regular and incident-affected operating conditions. The analysis involves two parts: (i) parametrically defining the shape of journey time distributions, and (ii) defining three performance metrics based on the moments of the distributions to measure the mean and variance of journey times. The metrics show that mean journey times are longest during the afternoon peak across all lines analyzed, and are more variable during the afternoon and off-peak periods depending on the line. Under incident conditions, mean journey times range from 8% to 39% longer compared with regular conditions, depending on the line. Overall, the main application of this work is that the metrics presented here can be directly applied by operators to quantify customer journey time performance, and can be further extended for industry-wide application to compare performance across metro networks.There has been increasing recognition in the transport industry of the need for performance metrics that capture journey time reliability from a passenger perspective as opposed to the traditional operator-oriented indicators. In a report for the Organisation for Economic Co-operation and Development (OECD) on service quality metrics used by metro operators, it is noted that the three most commonly reported metrics relating to journey time are train delay, wait times, and passenger journeys on-time (1). The first two metrics capture train performance from a schedule and headway adherence point of view. The third attempts to capture the experience of the user; however, it is recognized that operator-oriented indicators are rarely able to measure the true impact of passenger delay (2).The journey time distribution on

  • Journal article
    Achurra-Gonzalez PE, Angeloudis P, Goldbeck N, Graham D, Zavitsas K, Stettler Met al., 2019,

    Evaluation of port disruption impacts in the global liner shipping network

    , Journal of Shipping and Trade, Vol: 4, Pages: 1-21, ISSN: 2364-4575

    The global container shipping network is vital to international trade. Current techniques for its vulnerability assessment are constrained due to the lack of historical disruption data and computational limitations due to typical network sizes. We address these modelling challenges by developing a new framework, composed by a game-theoretic attacker-defender model and a cost-based container assignment model that can identify systemic vulnerabilities in the network. Given its focus on logic and structure, the proposed framework has minimal input data requirements and does not rely on the presence of extensive historical disruption data. Numerical implementations are carried in a global-scale liner network where disruptions occur in Europe’s main container ports. Model outputs are used to establish performance baselines for the network and illus-trate the differences in regional vulnerability levels and port criticality rankings with different disruption magnitudes and flow diversion strategies. Sensitivity analysis of these outputs identifies network compo-nents that are more susceptible to lower levels of disruption which are more common in practice and to assess the effectiveness of component-level interventions seeking to increase the resilience of the system.

  • Conference paper
    Anupriya A, Graham D, Horcher D, 2019,

    Existence of Hypercongestion in Highways: A truth or a fallacy?

    , ITEA Annual Conference on Transportation Economics
  • Journal article
    Canavan S, Barron A, Cohen J, Graham DJ, Anderson RJet al., 2019,

    Best Practices in Operating High Frequency Metro Services

    , Transportation Research Record, ISSN: 0361-1981

    © National Academy of Sciences: Transportation Research Board 2019. Most metro rail systems worldwide are facing increasing demand and the need to deliver additional capacity in key corridors. Although total capacity reflects the combination of train capacity and frequency, increasing frequency is the primary strategy to increase capacity on existing lines where infrastructure is fixed. Higher frequencies also increase efficiency, by attracting more passengers and making existing journeys faster, thereby making better use of expensive rail infrastructure and increasing both metro revenues and wider economics benefits to the cities they serve. This paper is based on a study conducted for the Community of Metros, a worldwide group of metro systems, which surveyed 17 high frequency lines. The paper first documents the characteristics of high frequency lines [with 25 trains per hour (tph) or more defined as “high frequency” and 30 tph or more as “very high frequency”] and presents the various constraints to higher frequency operations, including how they interact and the various possible solutions. Five main categories of constraints were identified, relating to signaling and train control, station and train crowding, fleet, terminal turnarounds, and service complexity. To achieve the highest frequencies, it is essential for metro systems to take a holistic approach and identify not only the immediate constraints but also secondary and tertiary constraints that may prevent the full benefits of improvements from being realized. This paper provides guidance to those operating, funding, planning, and designing metro systems in how to maximize frequency and thereby deliver greater benefits to riders, transit agencies, and stakeholders.

  • Journal article
    Collins DJ, Graham DJ, 2019,

    Use of open data to assess cyclist safety in London

    , Transportation Research Record, Vol: 267, Pages: 27-35, ISSN: 0361-1981

    This study develops a predictive model for cycling collisions in London. Specifically, the effects of bus lanes, parking or loading facilities, and multilane roads on the risk of cycling collisions are considered. To the best of the authors’ knowledge, this is the first such predictive collision model that develops covariates to measure the characteristics of different types of road infrastructure within zones. A kernel density estimator is used to identify 90 collision hotspots. Each hotspot is populated with information regarding the highway infrastructure within it. A multiple linear regression model tests for the statistical significance of the infrastructure variables. Bus lanes, multilane roads, and 30-mph speed limits are found to affect cycle collision counts, whereas junction density has the largest impact on collision density. Speed limits of 20 mph affect collision counts to a lesser degree than 30 mph, indicating potential safety improvement from reducing speed limits. One-way roads are found to reduce the risk of collisions, along with the provision of priority junctions. This infers that other junction types, such as roundabouts and signalized junctions, present a higher collision risk. The models produce conflicting results on parking or loading provision. The models are expanded to include sociodemographic variables, such as population and employment. The combined model offers no performance improvement over the infrastructure-only model, although a potential link between public transport provision and reducing cycle collisions warrants further investigation.

  • Journal article
    Achurra-Gonzalez PE, Novati M, Foulser-Piggott R, Graham DJ, Bowman G, Bell MGH, Angeloudis Pet al., 2019,

    Modelling the impact of liner shipping network perturbations on container cargo routing: Southeast Asia to Europe application

    , Accident Analysis & Prevention, Vol: 123, Pages: 399-410

    Understanding how container routing stands to be impacted by different scenarios of liner shipping network perturbations such as natural disasters or new major infrastructure developments is of key importance for decision-making in the liner shipping industry. The variety of actors and processes within modern supply chains and the complexity of their relationships have previously led to the development of simulation-based models, whose application has been largely compromised by their dependency on extensive and often confidential sets of data. This study proposes the application of optimisation techniques less dependent on complex data sets in order to develop a quantitative framework to assess the impacts of disruptive events on liner shipping networks. We provide a categorization of liner network perturbations, differentiating between systemic and external and formulate a container assignment model that minimises routing costs extending previous implementations to allow feasible solutions when routing capacity is reduced below transport demand. We develop a base case network for the Southeast Asia to Europe liner shipping trade and review of accidents related to port disruptions for two scenarios of seismic and political conflict hazards. Numerical results identify alternative routing paths and costs in the aftermath of port disruptions scenarios and suggest higher vulnerability of intra-regional connectivity.

  • Journal article
    Carbo Martinez J, Graham D, Anupriya A, Casas D, Melo Pet al., 2018,

    Evaluating the causal economic impacts of transport investments: evidence from the Madrid-Barcelona high speed rail corridor

    , Journal of Applied Statistics, Vol: 46, Pages: 1714-1723, ISSN: 0266-4763

    This paper evaluates economic impacts arising from the introduction of high-speed rail (HSR) between Madrid and Barcelona. Using difference-in-differences estimation we estimate an average treatment effect for provinces with stops on the HSR line of 2.4% for economic output, 3.3% for numbers of firms, and 1.1% for labour productivity. We complement our DID results with a synthetic control analysis for Lleida and Tarragona, two provinces that we argue were assigned HSR stations largely due to their incidental location. We find that both the number of firms and labour productivity are substantially higher in these provinces than in their synthetic counterparts.

  • Conference paper
    Anupriya A, Graham D, Anderson R, Carbo JMet al., 2018,

    Cost Function for Urban Rail Transport Systems

    , Transportation Research Board 98th Annual Meeting
  • Conference paper
    Zhang N, Graham DJ, Carbo Martinez JM, 2018,

    Using smart card data to analyse the disruption impact on urban metro systems

    , Transportation Research Board 98th Annual Meeting
  • Journal article
    Zhang F, Graham DJ, Wong M, 2018,

    Quantifying the substitutability and complementarity between high-speed rail and air transport

    , Transportation Research Part A: Policy and Practice, Vol: 118, Pages: 191-215, ISSN: 0965-8564

    This paper quantifies the substitution and complementary effects of high-speed rail (HSR) on air travel demand in terms of both route traffic and airport enplanement. Employing the difference-in-differences (DID) method, the first part of the analysis measures the effect of new HSR routes on parallel air route traffic with a focus on East Asian regions (Mainland China, Japan, South Korea, and Taiwan). The second part examines the effect of air-HSR integration on passenger enplanement at East Asian airports and compares with that in the Central European market. We find that in general the airport’s access cost (reflected by the distance from central city) has a negative impact on the air traffic. The substitution effects of HSR are the most significant on short- and medium-haul (below 1000 km) air routes while introducing HSR services has encouraged long distance (over 1000 km) air travels in Mainland China. The complementary effect is investigated in the context of air-HSR integration, which has significantly positive impacts on airport enplanement at primary hub airports when fitted with on-site HSR links. The benefit is limited at secondary hubs and regional airports possibly by locations and HSR service frequencies.

  • Journal article
    Han K, Graham D, Ochleng W, 2018,

    Border delays could cause congestion

    , Food Science and Technology (London), Vol: 32, Pages: 14-15, ISSN: 1475-3324
  • Journal article
    Barron A, Canavan S, Cohen J, Anderson Ret al., 2018,

    Operational impacts of platform doors in metros

    , Transportation Research Record, Vol: 2672, Pages: 266-274, ISSN: 0361-1981

    Platform doors are increasingly installed by metros, primarily to improve safety. However, they have the potential for both positive and negative operational impacts, mostly by affecting dwell times at stations. Using data from the CoMET and Nova international metro benchmarking consortia of 33 metro systems, this paper seeks to understand and quantify these operational impacts. Overall, platform doors have a net negative impact on dwell times, leading to between 4 and 15 seconds of extra time per station stop. This is due to additional time for the larger doors to open and close slower passenger movements due to the additional distance between platforms and trains and, most importantly, extended departure delays after both sets of doors are closed caused by the need to ensure safety (that no one is trapped in the gap between the two sets of doors). This is a particular problem in mainland China, where metros conduct manual safety checks that require drivers to step out of trains onto platforms. However, despite longer dwell times, platform doors have a net positive impact on metro operations, largely due to the many safety benefits that also reduce delays and thereby improve service performance. There are also potential benefits regarding energy and ventilation. To mitigate the negative impacts, metros should seek to refine procedures and improve technology to reduce dwell time delays caused by platform doors. Reducing or eliminating these extra delays are essential to delivering efficient service and maximum capacity, provided that safety can be assured.

  • Journal article
    Canavan S, Graham D, Anderson R, Barron Aet al., 2018,

    Urban metro rail demand: evidence from dynamic generalised method of moments (GMM) estimates using panel data

    , Transportation Research Record, Vol: 2672, Pages: 288-296, ISSN: 0361-1981

    This paper estimates elasticities of demand for metro service with respect to fares, income, quality of service, population and network length. Data for 32 world metro systems covering the period from 1996 to 2015 are analysed within a dynamic panel data specification. Three key contributions are made. First, we collate a database for estimation that is more extensive than that used in previous studies. Second, the quality of the data we have available allows us to more accurately represent quality of service than has been possible previously. And lastly, we estimate and compare two different measures of demand. Our analysis finds a statistically significant negative fare elasticity of -0.25 in the long run for a passenger km specified model and -0.4 in the long run for a passenger journeys specified model, and a positive long run income elasticity of 0.17 and 0.18 for the passenger km and passenger journey models respectively. Regarding quality of service we find positive long run elasticities of 0.56 and 0.47 for the passenger km and passenger journey models respectively. Income levels, population and the size of the network are also found to be statistically significant and positive in nature. The results suggest passenger km and passenger journeys will increase more in response to changes in service (here represented by increased capacity) than to changes in fares, with the difference in elasticities of service and fares being more pronounced for passenger km.

  • Journal article
    Trompet M, Anderson RJ, Graham DJ, 2018,

    Improved understanding of the relative quality of bus public transit using a balanced approach to performance data normalization

    , Transportation Research Part A: Policy and Practice, Vol: 114, Pages: 13-23, ISSN: 0965-8564

    In order for bus operators and/or their respective authorities to understand where service quality can improve, it is useful to systematically compare performance with organizations displaying similarities in types of services offered, operational characteristics and density of the service area. These similar characteristics enable peer organizations to benchmark performance once their operational data are normalized for differences in scale of operations. The most commonly used normalization factors for the demand side output are passenger boardings and passenger kilometres. For the supply side output these are vehicle kilometres and vehicle hours. Through twelve years of experience in the International Bus Benchmarking Group (IBBG) a better understanding of differences in service characteristics between ‘similar’ peers has been achieved, which highlight a challenge for the interpretation of normalized performance. It became clear that relative performance should often not be concluded from performance indicators normalized in a single dimension. Variety between peers in commercial speed, trip length, vehicle planning capacity, vehicle weight and network efficiency result in the need for a bi-dimensional or balanced approach to data normalization. This paper quantifies the variety within these operational characteristics and provides examples of the interpretation bias this may lead to. A framework is provided for use by bus organization management, policymakers and benchmarking practitioners that suggests applicable combinations of denominators for a balanced normalization process, leading to improved understanding of relative performance.

  • Journal article
    Barzin S, D'Costa S, Graham DJ, 2018,

    A pseudo - panel approach to estimating dynamic effects of road infrastructure on firm performance in a developing country context

    , Regional Science and Urban Economics, Vol: 70, Pages: 20-34, ISSN: 0166-0462

    To overcome the absence of true firm-level data, we provide evidence that the use of pseudo-panels based on aggregated data can correctly identify production function parameters. We construct a pseudo-panel of Colombian manufacturing firms for the years of 2000–2009 to study the effects of transportation infrastructure on firm performance in a developing country and find elasticities of output with respect to road infrastructure ranging from 0.13 to 0.15 per cent. This confirms that roads are important for private output growth and, as our results are larger than those reported in the literature for developed countries, that transportation infrastructure is relatively more important for the economy of developing countries. We also identify a one-year time lag with which firms' outputs react to road stock changes. This could be indicative of firms requiring time to adjust their production to road changes. We furthermore identify that the effect of road infrastructure is particularly large for heavy manufacturing industries. Moreover, we investigate the regional heterogeneity of the role of transportation infrastructure for firms' output growth. Our results are robust to different econometric concerns. We additionally provide Monte Carlo simulations to support the validity of pseudo-panels in the context of firm-level data.

  • Report
    Han K, Graham D, Ochieng W, 2018,

    M20/A20 Congestion Prediction with Post-Brexit Border Delays

    , M20/A20 Congestion Prediction with Post-Brexit Border Delays

    This research was commissioned by the BBC Inside Out South East program. It aims to quantify the congestion impact on M20/A20 of potential check time increase at Port of Dover and Eurotunnel (in Folkestone) in a post-Brexit scenario. We focus on a 40-mile segment of the M20/A20 motorway between Maidstone and Dover, with local access to Ashford and Folkestone. We consider outbound lorries and passenger vehicles that use the ferry and tunnel to cross the Straight of Dover, as well as traffic with local origins and destinations. Traffic simulations were conducted with assumptions regarding the check times at Dover and Eurotunnel for both current and post-Brexit scenarios. The impact of vehicle queuing at these locations was assessed in terms of queue length, travel time, and disruption to local traffic. The findings show that even one or two minutes of extra check times at the borders are accompanied by a dramatic increase of congestion on the motorways as well as local streets, with queues extending up to 30 miles from Dover/Eurotunnel towards Maidstone and travel time approaching 5 hours in peak times.

  • Journal article
    Melo PC, Graham DJ, 2018,

    Transport-induced agglomeration effects: Evidence for US metropolitan areas

    , Regional Science Policy and Practice, Vol: 10, Pages: 37-47

    While the interaction between transport and agglomeration economies is widely accepted, there is insufficient research attempting at a direct empirical quantification. Using a balanced panel dataset for US metropolitan areas, we estimate a system of simultaneous equations to measure the indirect effect of urban agglomeration economies which arises through transport provision. Our findings suggest that public transit reinforces the effect of urban agglomeration, whereas road lane miles appear to weaken it. The results highlight the importance of public transit in supporting positive urban agglomeration externalities.

  • Journal article
    Horcher D, Graham DJ, 2018,

    Demand imbalances and multi-period public transport supply

    , Transportation Research Part B: Methodological: an international journal, Vol: 108, Pages: 106-126, ISSN: 0191-2615

    This paper investigates multi-period public transport supply, i.e. networks in which capacity cannot be differentiated between links and time periods facing independent but nonidentical demand conditions. This setting is particularly relevant in public transport, as earlier findings on multi-period road supply cannot be applied when the user cost function, defined as the sum of waiting time and crowding costs, is nonhomogeneous. The presence of temporal, spatial and directional demand imbalances is unavoidable in a public transport network. It is not obvious, however, how the magnitude of demand imbalances may affect its economic and financial performance. We show in a simple back-haul setting with elastic demand, controlling for total willingness to pay in the network, that asymmetries in market size reduce the attainable social surplus of a service, while variety in maximum willingness to pay leads to higher aggregate social surplus and lower subsidy under efficient pricing. The analysis of multi-period supply sheds light on the relationship between urban structure, daily activity patterns, and public transport performance.

  • Conference paper
    Anupriya A, Graham D, Horcher D, Anderson Ret al., 2018,

    The impact of early bird scheme on commuter trip scheduling in Hong Kong: a causal analysis using travel card data

    , Transportation Research Board 97th Annual MeetingTransportation Research Board
  • Journal article
    Horcher D, Graham DJ, Anderson RJ, 2017,

    The economics of seat provision in public transport

    , Transportation Research Part E: Logistics and Transportation Review, Vol: 109, Pages: 277-292, ISSN: 1366-5545

    Seated and standing travelling imply significantly different experience for public transport users. This paper investigates with analytical modelling and numerical simulations how the optimal seat supply depends on demand and supply characteristics. The paper explores the implications of seat provision on the marginal cost of travelling as well. In crowded conditions, we distinguish two types of external costs: crowding density and seat occupancy externalities. We derive, using a realistic smart card dataset, the externality pattern of a metro line, and identify the distorting role of the occupancy externality that makes the welfare maximising fare disproportionate to the density of crowding.

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