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

TL;DR

This study develops an Agent-Based Modelling (ABM) framework to estimate older adults' mobility demand for Autonomous Mobility-on-Demand (AMoD) in Winnipeg for 2022, using open data and the MATSim platform. The ABM integrates an environment model derived from OpenStreetMap, a synthetic population (n=768,845; older adults n=127,314) generated via Quasirandom Integer Sampling of Iterative Proportional Fitting, and an activity-based demand model aligned to the Time Use Survey, with calibration against Winnipeg travel patterns. AMoD scenarios are tested with fleet sizes of 100, 250, and 500 vehicles, including induced demand, to observe adoption, rejections, and modal shifts, revealing a fleet-size threshold where additional vehicles yield diminishing returns and highlighting equity implications for older, non-licensed users. The results demonstrate that AMoD adoption among older adults increases with fleet size, induces changes in travel behaviour, and must be designed in concert with infrastructure planning to maximize accessibility while mitigating unintended urban-complexity effects.

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.

Figures (15)

• Figure 1: Diagram of the three main components of the proposed ABM: an environment model, a synthetic population, and an activity-based model.
• Figure 2: (a) Model of Winnipeg road network in grey and bus routes on a Tuesday service in orange. Road width is proportional to the road capacity. (b) Model of Winnipeg buildings and facilities. Residential buildings are in red, shops and sustenance in blue, education and civic amenities in yellow, sport and entertainment facilities in pink, healthcare buildings in light green, industrial and transport in orange, other land use in dark green and mixed land use in grey. Visualisation realised with Simunto.
• Figure 3: Synthetic population individual attributes.
• Figure 4: Example of activity schedule for one agent.
• Figure 5: Iterative calibration of the simulated modal split for 25% population sample (v1). The coloured ranges represent the modal share objective for each mode. The coloured lines represent the evolution of the modal share of each mode through the calibration steps. The dotted lines show the 2007 WATS modal share for each mode. After 27 steps, the modal share for each mode falls within the objective range.