Research on Traffic Flow States Identification Method Based on Dynamic Bayesian Networks
Author(s): ZHANG Jing-lei, WANG Xiao-yuan, MA Li-yun, TAN De-rong, School of Transportation and Vehicle Engineering, Shangdong University of Technology
Pages: 45-49
Year: 2014 Issue: 1
Journal: Transactions of Beijing Institute of Technology
Keyword: traffic flow states; dynamic Bayesian networks; priori probability; transition probability;
Abstract: In order to accurately identify states of traffic flow,and support real-time traffic flow guidance system,the traffic flow states identification method is put forward based on dynamic Bayesian networks,combining three kinds of traffic flow parameters(speed,volume and occupancy).The method is validated through simulation experiments making use of the date of the city of Southampton,UK.The results show that the traffic flow identification method based on dynamic Bayesian networks can determine more accurately states of traffic flow.It provides a theoretical support for intelligent transportation systems,particularly real-time traffic flow guidance system.
Pages: 45-49
Year: 2014 Issue: 1
Journal: Transactions of Beijing Institute of Technology
Keyword: traffic flow states; dynamic Bayesian networks; priori probability; transition probability;
Abstract: In order to accurately identify states of traffic flow,and support real-time traffic flow guidance system,the traffic flow states identification method is put forward based on dynamic Bayesian networks,combining three kinds of traffic flow parameters(speed,volume and occupancy).The method is validated through simulation experiments making use of the date of the city of Southampton,UK.The results show that the traffic flow identification method based on dynamic Bayesian networks can determine more accurately states of traffic flow.It provides a theoretical support for intelligent transportation systems,particularly real-time traffic flow guidance system.
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