Analysing mobility and environmental impacts of automated ride-sharing services under mixed traffic

Shared Automated Vehicles (SAVs) hold great promise for the future of urban mobility. Automated ride-sharing services are expected to alleviate traffic congestion, reduce traffic emissions, and significantly improve road safety by combining advanced connected and autonomous vehicle (CAV) technology with the ride and/or car-sharing concept. These benefits, however, are highly dependent on the deployment concept of the service and environment including network characteristics, CAV technology, traffic compositions, population acceptance, etc. This study aims to assess the mobility and environmental impacts of introducing a door-to-door automated ride-sharing (ARS) service under different deployment scenarios. Two calibrated and validated city-scale networks with different characteristics were used: a suburban area in the Greater Manchester (UK) and a city-centre area in Leicester (UK). An optimisation technique for the vehicle routing problem was developed to efficiently operate ARS at a network-level. The customers' preference for individual and shared rides with Willingness to Share (WTS) was investigated to gain a better understanding of the performance indicators (i.e., delay, travel time, speed, kilometres-driven and emissions) The introduction of ARS was investigated under two deployment scenarios: 1) mixed with conventional human-driven vehicles (HDVs) and 2) mixed with HDVs with varying CAV market penetration rates. Findings suggest that introducing ARS can adversely impact mobility and the environment under mixed traffic, especially in suburban areas, and the benefits of an automated ride-sharing system are highly dependent on WTS. The findings will assist local authorities in formulating automated ride-sharing policies to manage the traffic on roads. • Explores how introducing a door-to-door automated ride-sharing service can impact mobility & environment across various deployment scenarios. • Investigates the potential of automated ride-sharing to enhance urban mobility during the initial phases of autonomous vehicle deployment. • Utilized calibrated and validated city-scale networks, each with unique characteristics, to ensure a comprehensive analysis. • Explores ride-sharing integration with human driven vehicles, automated vehicles and public willingness to share rides.