A Network Selection Algorithm Based on Vehicle Trajectory Prediction and AHP

Abstract

Abstract This paper proposes a network selection algorithm based on Vehicle Trajectory Prediction and AHP (VMAP). The Markov chain is used to predict the running trajectory of the vehicle. The predicted trajectory is used to calculate the dwell time of the vehicle in the network. A network in which the dwell time is greater than a preset threshold is selected as a candidate network. Then, using the Analytic Hierarchy Process (AHP) to determine the weights of each attribute of the candidate network and obtain the comprehensive evaluation quality index of each candidate network to select the optimal network. This algorithm can not only minimize the ping-pong effect generated, but also enable the vehicle to access the optimal network stably.