Journal of Geographical Systems 2023 Best Paper Award

Totally chuffed that our paper on “realizable accessibility” has been selected by the Journal of Geographical Systems for the 2023 JGS Best Paper Award:

Inclusive accessibility: Integrating heterogeneous user mobility perceptions into space-time prisms,

New paper: Kar, A., Le, H.T.K. and Miller, H.J. (2023) “Inclusive accessibility: Integrating heterogeneous user mobility perceptions into space-time prismsAnnals of the American Association of Geographers, online first.

Abstract. Travelers’ day-to-day mobility depends on their perceptions, experiences, and personal characteristics. Many accessibility measures overlook perceptual factors and mainly consider space–time limitations of mobility, overestimating travelers’ potential mobility. We introduce a novel inclusive accessibility concept that advances time-geographic accessibility measures in light of travel behavior theories. We conceptualize inclusive accessibility as a subset of the classic space–time prism (STP) that incorporates hard constraints (e.g., limited infrastructure and services and time) and soft constraints (e.g., perceptions of safety and comfort toward the built environment and infrastructure and travel time preferences). We collected survey data on individual-level mobility perceptions and applied machine learning algorithms to predict personalized soft constraints for walking. Considering public transit and walking, we model and compare three network-based STPs: classic STP with hard constraints, inclusive STP with soft spatial constraints, and inclusive STP with soft spatial and temporal constraints. Our method demonstrates heterogeneities in individuals’ mobility perceptions. We illustrate that the individual’s level of accessibility shrinks substantially as we approach more conservative measures that include travel perceptions. Our method highlights the differences between travelers’ physically and psychologically accessible space depending on their travel choices and exposure.

Realizable accessibility: Evaluating the reliability of public transit accessibility using high-resolution real-time data

New paper: Liu, L., Porr, A. and Miller, H.J. (2023) “Realizable accessibility: Evaluating the reliability of public transit accessibility using high-resolution real-time data,” Journal of Geographical Systems, 25, 429-451.

Abstract. 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 schedule-based 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.