Prediction-Based Optimization For Online People And Parcels Share A Ride Taxis

One of the major problems faced in the urban environment is the efficient public transportation of people and goods. Clients make a call to the company to request a transportation service for people or parcels. A good transport scheduling will bring better profits to companies while satisfying people demands and reducing negative social impact such as traffic jam and pollution. We extend the work in [10] on a people and parcel share-a-ride taxis transportation model and propose algorithms to schedule taxis that exploit prediction on requests in an online scenario.