Data Services for Carpooling Based on Large-Scale Traffic Data Analysis

With the social development and vehicle increasing, traffic congestion becomes a pressing problem. Carpooling is one solution for traffic congestion. This paper begins with a motivation case and proposes a service-based method to automatically identify vehicles which travel together (i.e., Traveling companion) and provide carpooling candidates for users in heavy urban traffic. This paper focuses on services design and implementation of the carpooling functions in a distributed parallel computing environment. Through a comprehensive evaluation by experiments, our proposal is shown to deliver good efficiency and effectiveness.