On-Demand Transit User Preference Analysis using Hybrid Choice Models

TL;DR

This paper develops hybrid choice models to analyze user preferences for on-demand transit services, providing insights into factors influencing different user groups and guiding improvements for service design and operational efficiency.

Contribution

It introduces three hybrid choice models applied to real data, revealing distinct preferences among user segments and offering practical recommendations for ODT service enhancement.

Findings

Captive users prioritize trip count, in-vehicle time, and prior main mode.

Non-captive users are influenced by time sensitivity, satisfaction, and trip purpose.

Improving reliability and adjusting fleet size can enhance service performance.

Abstract

In light of the increasing interest to transform the fixed-route public transit (FRT) services into on-demand transit (ODT) services, there exists a strong need for a comprehensive evaluation of the effects of this shift on the users. Such an analysis can help the municipalities and service providers to design and operate more convenient, attractive, and sustainable transit solutions. To understand the user preferences, we developed three hybrid choice models: integrated choice and latent variable (ICLV), latent class (LC), and latent class integrated choice and latent variable (LC-ICLV) models. We used these models to analyze the public transit user's preferences in Belleville, Ontario, Canada. Hybrid choice models were estimated using a rich dataset that combined the actual level of service attributes obtained from Belleville's ODT service and self-reported usage behaviour obtained from a revealed preference survey of the ODT users. The latent class models divided the users into two groups with different travel behaviour and preferences. The results showed that the captive user's preference for ODT service was significantly affected by the number of unassigned trips, in-vehicle time, and main travel mode before the ODT service started. On the other hand, the non-captive user's service preference was significantly affected by the Time Sensitivity and the Online Service Satisfaction latent variables, as well as the performance of the ODT service and trip purpose. This study attaches importance to improving the reliability and performance of the ODT service and outlines directions for reducing operational costs by updating the required fleet size and assigning more vehicles for work-related trips.