Optimizing Performance of Ride-Sourcing Transportation Networks

In this project we are developing ways of improving the performance of self-interested drivers in ride-sourcing applications. Each driver has the objective of maximizing its profit, while the ride-sourcing company focuses on customer experience by seeking to minimizing the expected wait time for pick-up. These objectives are not usually aligned, and the company has no direct control on the waiting locations of the drivers.

We have developed two indirect control methods to optimize the set of waiting locations of the drivers, thereby minimizing the expected wait time of the customers: 1) sharing the location of all drivers with a subset of drivers, and 2) paying the drivers to relocate. We have shown that finding the optimal control for each method is NP-hard.  Despite this, we have developed algorithms that can find near-optimal controls in each case. We have evaluated the performance of the proposed control methods on real-world data showing significant improvements in customer wait-time.