Rail transit agencies have greatly advanced the ability to measure delays to rail system customers and have developed key performance indicators for rail systems based on customer travel time. The ability for operators to link these customer delay metrics to root causes would provide great benefit to agencies, from incident response improvement to capital program prioritization. This paper describes a method for linking late train arrivals to both late customers and incident tickets. Inspired by traffic flow theory, the method identifies impact zones in time and space that can then be linked to a potential root cause by way of incident tickets. This algorithm is currently under development by the Washington Metropolitan Area Transit Authority’s Office of Planning, and its outputs are being integrated into a variety of operations- and capital-related business processes.
HendrenP.AntosJ.CarneyY.HarcumR.Transit Travel Time Reliability: Shifting the Focus from Vehicles to Customers. Transportation Research Record: Journal of the Transportation Research Board, 2015. 2535: 35–44.
HalvorsenA.WoodD.StaskoT.JeffersonD.ReddyA.Passenger-Centric Performance Metrics for the New York City Subway. Transportation Research Record: Journal of the Transportation Research Board, 2019. 2673: 417–426.
AntosJ. D.EichlerM. D.Drinking from the Fire Hose: Visualizing Metrorail’s Fare System Data. Presented at 94th Annual Meeting of the Transportation Research Board, Washington, D.C., 2015.
9.
AntosJ. D.EichlerM. D.Tapping into Delay: Assessing Rail Transit Passenger Delay with Data from a Tap-In, Tap-Out Fare System. Transportation Research Record: Journal of the Transportation Research Board, 2016. 2540: 76–83.
10.
AntosJ. D.EichlerM. D.Planning a Successful Monthly Pass for Metrorail. Presented at 96th Annual Meeting of the Transportation Research Board, Washington, D.C., 2017.
11.
ChigusaK.A Framework for Identification of Systematic Service Deterioration in Urban Rail Systems. Doctoral dissertation. Massachusetts Institute of Technology, 2018.
12.
NelsonD.O’NeilK.Commuter Rail Service Reliability: On-Time Performance and Causes for Delays. Transportation Research Record: Journal of the Transportation Research Board, 2000. 1704: 42–50.
13.
HalvorsenA.JeffersonD.StaskoT.ReddyA.Algorithm for Tracing Train Delays to Incident Causes. Transportation Research Record: Journal of the Transportation Research Board, 2020. 2674: 264–273.
14.
LighthillM. J.WhithamG. B.On Kinematic Waves. II. A Theory of Traffic Flow on Long Crowded Roads. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, Vol. 229, No. 1178, 1955, pp. 317–345.
15.
DaganzoC. F.Fundamentals of Transportation and Traffic Operations. Pergamon, Oxford, 1997.
GordonJ. B.Intermodal Passenger Flows on London’s Public Transport Network: Automated Inference of Full Passenger Journeys Using Fare-Transaction and Vehicle-Location Data. Doctoral dissertation, Massachusetts Institute of Technology, 2012.
18.
GordonJ. B.KoutsopoulosH. N.WilsonN. H.AttanucciJ. P.Automated Inference of Linked Transit Journeys in London Using Fare-Transaction and Vehicle Location Data. Transportation Research Record: Journal of the Transportation Research Board, 2013. 2343: 17–24.
19.
GordonJ. B.KoutsopoulosH. N.WilsonN. H.Estimation of Population Origin–Interchange–Destination Flows on Multimodal Transit Networks. Transportation Research Part C: Emerging Technologies, Vol. 90, 2018, pp. 350–365.
