A cloud-based driving directions service in time-dependent landmark graph

A daily activity and been implemented as a key feature in many map services like Google and Bing Maps. A fast driving route saves not only the time of a driver but also energy consumption. This service is important for both end users and governments aiming to ease traffic problems and protect environment. The time that a driver traverses a route depends on the following three aspects: 1) The physical feature of a route, such as distance, capacity (lanes), and the number of traffic lights as well as direction turns; 2) The time-dependent traffic flow on the route; 3) A user’s driving behavior. A good routing service should consider these three aspects (routes, traffic and drivers), the scope of the shortest/fastest path computing. Efficient taxi dispatching and monitoring, taxis are usually equipped with a GPS sensor, enables them to report their locations to a server at regular intervals, minutes. That is, a lot of GPS-equipped taxis already exist in major cities, generating a huge number of GPS trajectories every day. The distance of a route, they also consider other factors, such as the time-variant traffic flows on road surfaces, traffic signals and direction changes contained in a route. These factors can be learned by experienced drivers but are too subtle and difficult to incorporate into existing routing engines. a cloud-based cyberphysical system for computing practically fast routes for a particular user, using a large number of GPSequipped taxis and the user’s GPS-enabled phone. GPS-equipped taxis are used as mobile sensors probing the traffic rhythm of a city in the physical world. A Cloud in the cyber world is built to aggregate and mine the information from these taxis as well as other sources from Internet, like Web maps and weather forecast. The mined knowledge includes the intelligence of taxi drivers in choosing driving directions and traffic patterns on road surfaces. The knowledge in the Cloud is used in turn to serve Internet users and ordinary drivers in the physical world. A mobile client, typically running in a user’s GPSphone, accepts a user’s query, communicates with the Cloud, and presents the result to the user. The mobile client gradually learns a user’s driving behavior from the user’s driving routes (recorded in GPS logs), and supports the Cloud to customize a practically fastest route for the user