Popular route planning with travel cost estimation from trajectories

With the increasing number of GPS-equipped vehicles, more and more trajectories are generated continuously, based on which some urban applications become feasible, such as route planning. In general, popular route that has been travelled frequently is a good choice, especially for people who are not familiar with the road networks. Moreover, accurate estimation of the travel cost (such as travel time, travel fee and fuel consumption) will benefit a well scheduled trip plan. In this paper, we address this issue by finding the popular route with travel cost estimation. To this end, we design a system consists of three main components. First, we propose a novel structure, called popular traverse graph where each node is a popular location and each edge is a popular route between locations, to summarize historical trajectories without road network information. Second, we propose a self-adaptive method to model the travel cost on each popular route at different time interval, so that each time interval has a stable travel cost. Finally, based on the graph, given a query consists of source, destination and leaving time, we devise an efficient route planning algorithm which considers optimal route concatenation to search the popular route from source to destination at the leaving time with accurate travel cost estimation. Moreover, we conduct comprehensive experiments and implement our system by a mobile App, the results show that our method is both effective and efficient.