Abstract: Nowadays, real-time, accurate and reliable track prediction of moving objects plays a very important role in traffic management system, military mechanized battlefield and safe driving system， which has been applied more and more widely in the market, namely intelligent prediction. Intelligent prediction can provide accurate location-based services, and it can also recommend optimal routes to car owners based on pre-judgment, which has become a hot spot of research on mobile object database. Aiming at the shortcomings of the existing methods, a Gaussian mixture-Bayesian trajectory prediction model is proposed. The experimental results show that the GM-BM model can predict the most likely trajectory by adjusting the weight of the neutron model of the mixed model under the normal traffic flow of road section. After calculation, the prediction accuracy is improved by at least 10.00% compared with the single model under the same parameter setting.

Key words: trajectory prediction, Gaussian mixture-Bayesian model, probability distribution, intelligent prediction