What is it about?
In this paper I explored how to improve predictive models of transit ridership by incorporating measures of accessibility (ease or convenience in reaching spatially distributed opportunities) at two distinct scales: metropolitan and local. Both phenomena were operationalized on an origin-based cumulative opportunities model with distance-decay functions. I also explored if a combination of high levels of both metropolitan and local accessibility yields higher ridership. That is, if a synergistic effect occurs with number of boardings at station-level increasing beyond the individual effect of each measure. Model results indicate such is the case, and register high explanatory (predictive) power.
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Why is it important?
Developing a relatively easy to implement and more economical transit ridership model with high explanatory power can help key stakeholders in benefit/cost evaluation of route and mode alternatives; transit service planning and scheduling studies; and Transit Oriented Development [TOD] scenario planning given accessibility measures' ability to capture land-use/travel interactions. My investigation also contributes to transportation and land-use science by demonstrating how urban geography concepts can be integrated in econometric models of ridership (service consumption) for both predictive and theoretical insights on aggregate travel behavior. Advancing more sustainable transportation modes (walking, bicycling, transit) in combination with supporting design and land-use policies (TOD), is critical to addressing an increasing urbanized humanity and a more sustainable relationship with its supporting natural ecosystems. Sustainable urban transportation systems play a key role in this transformation.
Perspectives
I believe that land-use planners, transportation planners (engineers), urban designers, real-estate developers, policy-makers, among other key stakeholders would benefit from incorporating an accessibility lense in their theory and practice. And that having a common theoretical and practical background on this central topic would facilitate interdisciplinary understanding and collaboration in crafting policies and guiding design in the public interest.
Dr. Luis Enrique Ramos-Santiago
University of Massachusetts Boston
Read the Original
This page is a summary of: Enhancing station level Direct-Demand models with Multi-Scalar accessibility indicators, Transportation Research Interdisciplinary Perspectives, May 2023, Elsevier,
DOI: 10.1016/j.trip.2023.100834.
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