Location–based vehicular moving predictions for wireless communication. (13th September 2012) - Wu, Hsin–Te
In cellular networks, an important practical issue is how to ensure high–quality service. We assume all Base Stations (BSs) have a Geographic Information System (GIS) that has a street map with all BSs and all vehicles have a Global Positioning System (GPS), which acquires data for vehicle speed, direction, and location and sends this information to the nearest BS periodically when communicating within the BS. Based on this vehicle information, a BS checks whether an intersection has a traffic light, determines the traffic light pattern, predicts where vehicles may move, determines whether vehicles may move into another region, and informs the BS to reserve resources for a hand–off. Based on GPS and GIS information, the proposed method, TSDMP, has a lower prediction error rate in predicting traffic light patterns and vehicle movements than other techniques.