New paper: Liu, L. and Miller, H.J. (2022) “Measuring the impacts of dockless micro-mobility services on public transit accessibility,” Computers, Environment and Urban Systems, 98, 101885.
We develop new measures of the accessibility increments to public transit afforded by dockless micromobility. We apply this to public transit and Lime scooter data for Columbus. We find that dockless micro-mobility services such as scooters can improve public transit accessibility, but the benefits are very uneven and face substantial challenges including capacity and cost.
I was interviewed for an ABC 6 news investigative report on reckless driving in Columbus. It turned out to be more about ATVs, dirt bikes and wheelies than I expected, but I stand by my message. And wait to the end to see the virtual complete street!
Reckless on the road: What can be done to make Columbus streets safer? – ABC6 News Columbus, August 3 2022
New paper! Liu, L., Porr, A. and Miller, H.J. (2022) “Realizable accessibility: Evaluating the reliability of public transit accessibility using high-resolution real-time data,” Journal of Geographical Systems, online first.
Take home message:
We develop a refined time geographic measure of accessibility via public transit using real-time vehicle location data. We also show how to use this measure with schedule data to analyze the reliability of public transit accessibility at the urban scale. To be published in a special issue on “Time Geography in the Age of Mobility Analytics” in the Journal of Geographical Systems.
The widespread availability of high spatial and temporal resolution public transit data is improving the measurement and analysis of public transit-based accessibility to crucial community resources such as jobs and health care. A common approach is leveraging transit route and schedule data published by transit agencies. However, this often results in accessibility overestimations due to endemic delays due to traffic and incidents in bus systems. Retrospective real-time accessibility measures calculated using real-time bus location data attempt to reduce overestimation by capturing the actual performance of the transit system. These measures also overestimate accessibility since they assume that riders had perfect information on systems operations as they occurred. In this paper, we introduce realizable real-time accessibility based on space–time prisms as a more conservative and realistic measure. We, moreover, define accessibility unreliability to measure overestimation of schedulebased and retrospective accessibility measures. Using high-resolution General Transit Feed Specification real-time data, we conduct a case study in the Central Ohio Transit Authority bus system in Columbus, Ohio, USA. Our results prove that realizable accessibility is the most conservative of the three accessibility measures. We also explore the spatial and temporal patterns in the unreliability of both traditional measures. These patterns are consistent with prior findings of the spatial and temporal patterns of bus delays and risk of missing transfers. Realizable accessibility is a more practical, conservative, and robust measure to guide transit planning.