  Recent advances in communication technologies and automated vehicles have
opened doors for alternative mobility systems (taxis, carpool,
demand-responsive services, peer-to-peer ridesharing, and car sharing, shared
autonomous vehicles/shuttles). These new mobility services have gathered
interest from researchers, public and private sectors as potential solutions to
address last-mile problem--especially in low density areas where implementation
of high frequency buses is not feasible. In this study we investigate the
effects of ride-sharing service on travel demand and welfare, as it complements
public transportation under different scenarios. Two types of management and
vehicle types are considered: crowdsourced human driven vehicles (HDV) (e.g.
Uber, Lyft) and centrally operated shared autonomous vehicles (SAV). The
influence of fare discount on demand and mode shift is also investigated. A
case study of Oakville road network in Ontario, Canada is conducted using real
data. The results reveal that ride-sharing having the potential of increasing
ridership by 76 per cent and decreasing wait time by 47 per cent under
centrally operated shared autonomous vehicles with 50 per cent fare discount
for sharing.
