Title

Characterizing co-modality in urban transit systems from a passengers’ perspective

Document Type

Journal Article

Publication Date

2020

Subject Area

place - urban, operations - performance, technology - intelligent transport systems, technology - passenger information, land use - urban density, ridership - behaviour

Keywords

Public transit, Co-modality, Performance, Travel time, GTFS, API

Abstract

Co-modality is a concept based on a unified network system which will ensure the effective and sustainable utilization of all transportation modes. However, the application of co-modality as a measure of evaluating public transit system performance is recent and has been predominantly used in freight transport systems. This study proposes a novel approach by using co-modality as a key performance indicator to characterize public transit systems for passengers. This paper examines a new data set to evaluate transit systems from a user perspective. The data is gathered from an Application Programming Interface (API) which pulls from the real-time General Transit Feed Specification (GTFS). Data was collected over 24 h to explore 4320 transit trips and 69,120 attributes for a single origin–destination pair. Co-modality is used to understand how dozens of transit routes and schedules will best serve transit users. A detailed analysis of trips involving multiple transit segments is conducted to understand how varying headways influence the overall trip travel time. The main conclusion for this paper is that a user perspective is necessary to understand co-modality across public transit systems. Some of the metrics identified in this paper, such as percent of trip spent walking, will be useful in assessing last-mile portions of travel across multiple trips. A better understanding of transit service to travelers by the transit system as a whole will help to improve transportation in dense urban areas.

Rights

Permission to publish the abstract has been given by SpringerLink, copyright remains with them.

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