A Method for Driving Route Predictions Based on Hidden Markov Model

Abstract EN

We present a driving route prediction method that is based on Hidden Markov Model (HMM).

This method can accurately predict a vehicle’s entire route as early in a trip’s lifetime as possible without inputting origins and destinations beforehand.

Firstly, we propose the route recommendation system architecture, where route predictions play important role in the system.

Secondly, we define a road network model, normalize each of driving routes in the rectangular coordinate system, and build the HMM to make preparation for route predictions using a method of training set extension based on K-means++ and the add-one (Laplace) smoothing technique.

Thirdly, we present the route prediction algorithm.

Finally, the experimental results of the effectiveness of the route predictions that is based on HMM are shown.