The Framework of Increasing Drivers’ Income on the Online Taxi Platforms

Abstract

Traffic congestion reduces the working efficiency of taxis, thus lowering the income of taxi drivers. In most cases, taxi drivers will choose the least time-consuming route, which is usually the shortest in distance to the destination. However, during rush hours when traffic flow is heavy, the shortest route may not be the most time-efficient. A detour sometimes can save time for drivers but that may highly increase the fare for passengers. In order to optimize the balance between fare and profit, this paper proposes a framework, called ProfitMax, which will recommend a fixed price and a more profitable route by assigning the most suitable taxi for online taxi-hailing. The taxi's profit of completing an order is calculated by the income per minute. We use drivers’ personal driving habit to estimate the basic cost of an order and then recommend the most profitable route. ProfitMax trains the personal fuel-consumption model and estimates the fuel consumption on drivers’ smart devices. We use a real taxiing data set, including one-month taxis’ GPS trajectories and car-OBD (on-board-diagnose) readings, for the performance evaluation. Experimental results show that ProfitMax estimated the fuel consumption more accurate than baselines and can also save more than 10% fuel for the whole driver community. It also shows that ProfitMax can improve the total income by recommending more profitable routes to drivers.