Title:Universal laws of matching probability, routing distance and detour distance in on-demand ride-sourcing markets
Presenter:Yang Hai
Time:2019.12.27 10:00-12:00am
Location:A716
Invited by:Prof.Liu Tianliang
Abstract:By serving two or more passenger requests in each ride in ride-sourcing markets, ride-splitting (or ride-sharing) services are now becoming an important
component of shared smart mobility for improving vehicle utilization and alleviate traffic congestion. Three key measures in ride-splitting services are of great interest. The first one is the proportion of passengers who are pool-matched (referred to as pool-matching probability), the second is passengers’ average detour distance, and the third is drivers’ routing distance to pick-up and drop-off all passengers with different origins and destinations in one ride-splitting service. The values of these measures are critically dependent on the passenger demand for ride-splitting and matching strategies. Due to complexity of the ride-sourcing market, it is difficult to analytically establish the relationships between these measures and passenger demand. This study empirically ascertains these relationships of interest through extensive experiments based on the actual on-demand mobility data obtained from Chengdu, Haikou, and Manhattan. It is surprising that the relationships between the three aforementioned measures and the number of passengers in the matching pool can be well fitted by some simple curves (with fairly high goodness-of-fit), or elegant empirical laws exist to speak about the relationships. Our findings are insightful and useful for our understanding of right-sourcing markets.
