Computer Science ›› 2018, Vol. 45 ›› Issue (3): 235-240.doi: 10.11896/j.issn.1002-137X.2018.03.037

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Uncertain Vehicle Intersection Trajectory Prediction

MAO Ying-chi and CHEN Yang   

  • Online:2018-03-15 Published:2018-11-13

Abstract: In the city road,real-time,accurate and reliable trajectory prediction of mobile vehicles can bring very high application value,which can not only provide accurate location-based services,but also can help the vehicle to predict the traffic situation.At present,the trajectory prediction method of moving vehicles is mainly based on the precise historical trajectory in Euclidean space,and does not consider the vehicle trajectory prediction with uncertain historical data in restricted road network.A trajectory prediction method based on Markov chain was proposed to solve this problem.Its advantages include redefining the path algorithm of completion,making up for the incompleteness of uncertain historical data,and achieving prediction by using the characteristics of low time complexity and high prediction accuracy with Markov chain.This method avoids the problem of low prediction accuracy caused by too much query time due to the frequent pattern mining and the excess noise.The results show that under the same parameter setting,the prediction accuracy of the method is 18.8% higher than that of the mining frequent trajectory model,and the prediction time is reduced by 80.4% on average.Therefore,the method has high prediction accuracy for the trajectory prediction of the vehicle intersection,and achieves the prediction of a series of vehicle future trajectories.

Key words: Restricted road network,Vehicle trajectory prediction,Uncertainty historical data,Completion path,Markov chain

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