Urban observatory science: Leveraging geospatial data and real-world experimentation for sustainability

I recently delivered a virtual keynote address to the Chinese Professionals in Geographic Information Sciences (CPGIS) annual meeting – the main GIS conference in China. Originally scheduled to take place in Nanchang, Jiangxi Province, China, it was switched to an online only conference due to the COVID pandemic; the keynote was pre-recorded.

 

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

Measuring the structural similarity of network time prisms using temporal signatures with graph indices

New publication: Jaegal Y, Miller HJ. (2019) Measuring the structural similarity of network time prisms using temporal signatures with graph indices. Transactions in GIS. 00:1–24. https ://doi.org/10.1111/tgis.12582

Abstract.  The network‐time prism (NTP) is an extension of the space‐time prism that provides a realistic model of the potential pattern of moving objects in transportation networks. Measuring the similarity among NTPs can be useful for clustering, aggregating, and querying potential mobility patterns. Despite its practical importance, however, there has been little attention given to similarity measures for NTPs. In this research, we develop and evaluate a methodology for measuring the structural similarity between NTPs using the temporal signature approach. The approach extracts the one‐dimensional temporal signature of a selected property of NTPs and applies existing path similarity measures to the signatures. Graph‐theoretic indices play an essential role in summarizing the structural properties of NTPs at each moment. Two extensive simulation experiments demonstrate the feasibility of the approach and compare the performance of graph indices for measuring NTP similarity. An empirical application using bike‐share system data shows that the method is useful for detecting different usage patterns of two heterogenous user groups.