Predicting driving direction with weighted markov model


Autoria(s): Mao, Bo; Cao, Jie; Wu, Zhiang; Huang, Guangyan; Li, Jingjun
Contribuinte(s)

Zhou, Shuigeng

Zhang, Songmao

Karypis, George

Data(s)

01/01/2012

Resumo

Driving direction prediction can be useful in different applications such as driver warning and route recommendation. In this paper, a framework is proposed to predict the driving direction based on weighted Markov model. First the city POI (Point of Interesting) map is generated from trajectory data using weighted PageRank algorithm. Then, a weighted Markov model is trained for the near term driving direction prediction based on the POI map and historical trajectories. The experimental results on real-world data set indicate that the proposed method can improve the original Markov prediction model by 10% at some circumstances and 5% overall.<br />

Identificador

http://hdl.handle.net/10536/DRO/DU:30083690

Idioma(s)

eng

Publicador

Springer

Relação

http://dro.deakin.edu.au/eserv/DU:30083690/huang-predictingdriving-2013.pdf

http://dro.deakin.edu.au/eserv/DU:30083690/huang-predictingdriving-evid-2013.pdf

http://www.dx.doi.org/10.1007/978-3-642-35527-1_34

Direitos

2013, Springer

Palavras-Chave #driving direction prediction #trajectory mining #weighted PageRank
Tipo

Conference Paper