Trends that will shape us: Transportation

On April 7, I participated in a panel discussion at the Columbus Metropolitan Club; topic: Trends that Will Shape Us: Transportation. Other guests include Jack Marchbanks (Director, Ohio Department of Transportation) and Kevin Chambers (Managing Director – Logistics, Distribution and Supply Chain, JobsOhio).

It was an interesting and lively conversation: spanning public transit, the impact of COVID on cities, social equity, infrastructure, freight and logistics.  Check it out!

Link to recording

 

 

Does real-time transit information reduce waiting time? An empirical analysis

New paper: Liu, L. and Miller, H.J. (2020) “Does real-time transit information reduce waiting time? An empirical analysis,” Transportation Research A, 141, 167-179.

Highlights

  • 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.

Abstract

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.

Media

Webinar: Impacts of COVID-19 on Mobility

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.

Panelists:

  • 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