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	Driver lane changing behavior analysis based on parallel Bayesian networks
	Li Liu; Guo-qing Xu; Zhangjun Song
	2010
会议名称	2010 6th International Conference on Natural Computation, ICNC'10
英文摘要	Driver behavior model is one of the key technologies for the driver assistance and safety system which can provide useful priori knowledge for detecting the abnormal behaviors effectively. The paper introduces the Driver behavior model which is established by the parallel Bayesian networkswith steering angles and their difference and the final status of driver behavior is decided by the largest probability of the each status during the time of lane changing. In addition, the transition time of the status is automatic tagged by the multi-variable Gaussian model of steering angles and their difference. Finally, the parallel Bayesian network model is compared with the Gaussian Bayesian Network of the steering angles. The state transition diagram of driver behavior and the analysis of experiment results are given.
收录类别	EI
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/2804]
专题	深圳先进技术研究院_集成所
作者单位	2010
推荐引用方式 GB/T 7714	Li Liu,Guo-qing Xu,Zhangjun Song. Driver lane changing behavior analysis based on parallel Bayesian networks[C]. 见:2010 6th International Conference on Natural Computation, ICNC'10.

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