Menu
This research aims to address a significant gap in understanding the diverse and complex mobility needs of ageing populations and explore applications of Artificial Intelligence in the design of future on-demand, autonomous transit services to meet these needs. The RAIM project will undertake qualitative and quantitative analysis of the diverse mobility needs of ageing populations in the UK and Canada, and apply a suite of computational methods to analyze, predict, and optimize an inclusive electric autonomous (EA) demand-responsive transit (DRT) system design. The project will break new ground on understanding and modelling the complex interactions of socio-economic status, gender, physical and health conditions, cognitive impairment, lifestyle, and attitudes on spatiotemporal demand for autonomous mobility in older populations. RAIM will furthermore make advances in optimizing supply to meet complex, heterogeneous demand, through novel application of Deep Reinforcement Learning and Graph Convolutional Networks. The project will engage closely with local transport providers and charitable organizations in the UK and Canada, and determine the economic and policy case for or against public intervention, building estimates of the costs and broader benefits of EA DRT schemes under current and future scenarios.
