This session presents research advances in light rail performance, management and design including papers on international comparisons of light rail, research on real time understanding of tram bunching, optimising track design for delay minimisation and mode choice during tram service disruptions.
An International Comparative Study of the Transit Performance of Small Light-Rail Systems in Spain and the United States
Luis Ramos-Santiago, Clemson UniversityShow Abstract
Margarita Novales Ordax, Universidade da Coruña
Francisco-Alberto Varela-García, Universidade da Coruña
This paper aims to register and understand differences in transportation performance of five most similar modern light-rail systems; two operate in Spain (Granada and Tenerife) and three in the United States (Norfolk, Charlotte, and Cleveland). All cases are relatively small in scale and scope, featuring 1 or 2 lines and a maximum of 34 stations. Data related to monthly and annual ridership, service supply, and service consumption was collected and harmonized for base year 2018. A set of key service quality, land-use, and socio-economic factors was identified in precedent transit ridership and LRT performance literature and used in the ranking of systems. Each factor was ranked according to expected positive or negative effects on ridership and performance. In addition, socio-economic and land-use contextual attributes within stations’ network-based service areas were collected and aggregated in GIS for system-wide comparisons. Results indicate that the two systems from Spain register the best ranking scores and the highest performance indicators, with the system from Tenerife (which opened to service 10 years before Granada) reporting the highest levels for ridership, service productivity, and cost effectiveness. Charlotte’s light-rail registers the best ranking and performance indicators for the sub-set of U.S. systems, and third overall. The authors conclude that contextual attributes related to land-use characteristics, automobile availability, and service levels are key in explaining the differences in performance, albeit other variables related to local culture, planning, service delivery, and performance management need to be explored and documented in the future for a more comprehensive evaluation.
When Will They Bunch Next? Predictive Analytics of Streetcar Bunching Occurrence Time for Real-Time Applications
Aya Aboudina, Cairo UniversityShow Abstract
Ehab Diab, University of Saskatchewan
Amer Shalaby, University of Toronto
Bunching occurs when transit vehicles are unable to maintain their scheduled headways, resulting in two or more vehicles arriving at a stop in close succession and following each other too closely thereafter. Very few studies explored the prediction of bunching in real-time, particularly for streetcar service. Predicting the time to bunching in real-time allows transit agencies to take more preventive actions to avoid the occurrence of bunching or to minify its effects. In this study, we present a comprehensive literature review of the recent research conducted in bunching and real-time prediction models. Based on the findings from the literature review, we propose a model for real-time prediction of streetcar bunching. The Kalman Filtering (KF) model predicts the travel time to bunching incidents, and is tested and analysed using automatic vehicle location (AVL) data feed from Toronto Transit Commission (TTC)’s next bus system, for one streetcar route (Route 506 Carlton). The results show that: 1) the model provides good predication quality given that it relies only on the real-time GPS feed of streetcars, which makes it practical for use in real-time prediction applications, 2) the model prediction accuracy improves as the transit vehicle travels away from the terminal, and 3) increasing the number of past days involved in the calculations beyond 6 days and/or increasing the number of leading trips considered in the same day beyond 7 or 10 trips might increase the prediction error.
An optimization model for rail line crossover design considering the cost of delay
Willem Trommelen, Universiteit TwenteShow Abstract
Konstantinos Gkiotsalitis, University of Twente
Eric C. van Berkum, Universiteit Twente
In this study, we introduce a method to optimize the crossover locations of an independent rail line by minimizing the cost of passenger delay. Past works showed that including passenger delay in the decision of rail design choices could be beneficial from an economical and societal perspective. However, those works were only able to evaluate a few alternatives, because the degraded schedules had to be determined manually. In this work, we introduce an integer non-linear model to find the best crossover design. We further develop an algorithm to evaluate a set of crossovers and determine the cost of delays for all segments on a rail line given a set of potential disruptions. The monetized cost of passenger delays is used to analyze the trade-off between the additional flexibility of an extra crossover and the purchase and scheduled maintenance cost of this crossover. Our model is applied in a light rail line in Bergen (Norway) resulting in 10% reduction in terms of passenger delays.
Transit Users’ Mode Choice Behavior During Short-Term LRT Planned Service Disruption (PSD)
Asim Muhammad, University of Calgary, SchulichShow Abstract
Adam Weiss, Carleton University
Lina Kattan, University of Calgary, Schulich
S.C. Wirasinghe, University of Calgary
Light Rail Transit (LRT) Planned Service Disruptions (PSDs) improve service reliability, extend infrastructure’s life and reduce the frequency and impact of unplanned service disruption caused by system failure. However, the literature on the impact of LRT PSDs on transit customers’ travel mode choice behavior is scarce relative to that on unplanned service disruptions. This study aimed to investigate transit customers’ mode choice behavior in response to short-term LRT PSD in the City of Calgary, AB, Canada. A stated preference survey was designed to gather respondents’ mode choices under a set of hypothetical PSD scenarios. A mixed multinomial logit model was estimated using stated preference data. Findings of this study include: 1) Stated LRT ridership dropped by about 35% during the examined LRT short-term service disruption. 2) The customers that use an LRT payment pass (monthly, seniors, students, etc.) and are frequent weekend LRT users are more likely to stay with the LRT mode in case of short-term PSD 3) The value of time for transit users’ during short-term LRT PSD was be 11.76 $/hr. and 13.0$/hr. for travel time (excluding wait time) and wait time during travel, respectively. A sensitivity analysis was conducted on key variables to predict choice probabilities of transit alternatives and recommendations were made to improve Calgary Transit customers’ experience during short-term LRT PSDs.
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