Agent-Based Modelling of Older Adult Needs for Autonomous Mobility-on-Demand: A Case Study in Winnipeg, Canada

TL;DR

This paper presents an agent-based model for estimating older adults' mobility needs in Winnipeg, aiding the planning of autonomous mobility-on-demand services through detailed simulation and calibration.

Contribution

It introduces a novel agent-based modeling approach using open data and MATSim to accurately simulate older adults' travel behaviors for AMoD system planning.

Findings

Model accurately reproduces observed travel behaviors.

Simulation tests show potential adoption of AMoD among older adults.

Provides policy guidance for elderly transportation needs.

Abstract

As the populations continue to age across many nations, ensuring accessible and efficient transportation options for older adults has become an increasingly important concern. Autonomous Mobility-on-Demand (AMoD) systems have emerged as a potential solution to address the needs faced by older adults in their daily mobility. However, estimation of older adult mobility needs, and how they vary over space and time, is crucial for effective planning and implementation of such service, and conventional four-step approaches lack the granularity to fully account for these needs. To address this challenge, we propose an agent-based model of older adults mobility demand in Winnipeg, Canada. The model is built for 2022 using primarily open data, and is implemented in the Multi-Agent Transport Simulation (MATSim) toolkit. After calibration to accurately reproduce observed travel behaviors, a new AMoD service is tested in simulation and its potential adoption among Winnipeg older adults is explored. The model can help policy makers to estimate the needs of the elderly populations for door-to-door transportation and can guide the design of AMoD transport systems.