Public transit agencies publish real time information for use in mobile apps
We benchmark several strategies using empirical transit system performance data.
Overall, real time information does not outperform simply following schedule.
Real time information can reduce waiting time for some users based on location.
Including a time buffer improves the greedy approach used by popular apps.
A claimed benefit of real-time information (RTI) apps in public transit systems is the reduction of waiting time by allowing passengers to appropriately time their arrivals at transit stops. Although previous research investigated the overall impact of RTI on waiting time, few studies examine the mechanisms underlying these claims, and variations in its effectiveness over time and space. In this paper, we theorize and validate the sources of RTI-based users’ waiting time penalties: reclaimed delay (bus drivers compensating for being behind schedule) and discontinuity delay (an artifact of the update frequency of RTI). We compare two RTI-based strategies – the greedy strategy used by popular trip planning apps and a prudent strategy with an insurance buffer – with non-RTI benchmarks of arbitrary arrival and following the schedule. Using real-time bus location data from a medium-sized US city, we calculate the empirical waiting times and risk of missing a bus for each trip planning strategy. We find that the best RTI strategy, a prudent tactic with an optimized insurance time buffer, performs roughly the same as the simple, follow-the-schedule tactic that does not use RTI. However, relative performance varies over time and space. Moreover, the greedy tactic in common transit apps is the worst strategy, even worse than showing up at a bus stop arbitrarily. These results suggest limitations on claims that RTI reduces public transit waiting times.
On July 29th, I participated in a webinar on the Impacts of COVID-19 on Mobility, organized by The Ohio State University College of Arts and Sciences, the College of Engineering and the OSU Alumni Association. The recording is posted below. Very interesting discussion; worth watching!
Faculty and industry experts have a conversation about the potential implications of COVID-19 on the design of our communities and various modes of transportation including air travel, personal vehicles, public transit, micro-mobility and ride-hailing services.
Chris Atkinson, Director, The Ohio State University Smart Mobility Program
Jennifer Clark, Professor and Section Head, City and Regional Planning
Harvey Miller, Reusche Chair in Geographic Information Science; Director, Center for Urban and Regional Analysis
Sophia Mohr, Chief Innovation Officer, Central Ohio Transit Authority
Stephanie Morgan, Executive Director, Air Transportation and Aerospace Campus
Giorgio Rizzoni, Center for Automative Research, Ford Motor Company Chair, Mechanical & Aerospace Engineering
We develop an analytical framework for measuring accessibility considering travelers’ heterogeneous safety margin plans and routing strategies under travel time uncertainty.
We explore how accessibility changes under various safety margin plans and routing strategies.
We define and measure robust accessibility: geographic areas that are accessible regardless of the safety margin planning and routing strategy.
Robust accessibility provides a conservative and reasonable view of accessibility under travel time uncertainty.
We apply our framework to measure the accessibility impacts of new public transit service under travel time uncertainty.
Uncertainties in travel times due to traffic congestion and delay are risks for drivers and public transit users. To avoid undesired consequences such as losing jobs or missing medical appointments, people can manage the risks of missing on-time arrivals to destinations using different strategies, including leaving earlier to create a safety margin and choosing routes that have more reliable rather than fastest travel times. This research develops a general analytical framework for measuring accessibility considering automobile or public transit travelers’ heterogeneous strategies for dealing with travel time uncertainty. To represent different safety margin plans, we use effective travel time (expected time + safety margin), given specified on-time arrival probabilities. Heterogeneity in routing strategy is addressed using different Pareto-optimal routes with two main criteria: faster travel time vs. higher reliability. Based on various safety margin and routing strategy combinations, we examine how accessibility changes under varying safety margin plans and routing strategies. Also, we define and measure robust accessibility: geographic regions that are accessible regardless of the safety margin planning and routing strategy. Robust accessibility can provide a conservative and reasonable view of accessibility under travel time uncertainty. To demonstrate the applicability of the methods, we carry out an empirical study on measuring the impacts of new transit service on healthcare accessibility in a deprived neighborhood in Columbus, Ohio, USA.