Driver Safe Speed Model Based on BP Neural Network for Rural Curved Roads

Abstract : In order to improve the safety and comfort of the vehicles on rural curved roads, the paper proposed a safe curve speed model based on the BP Neural Network. A series of drivers’ manual operation state data during cornering were gathered and observed according to the driver experiments under real traffic conditions. Three factors, referring to the speed calculated based on road trajectory parameters, the adhesion workload and the yaw rate computed from the processed data, were used as inputs of the model to obtain the target vehicle speed. Finally, tests verify the applicability of the modified model. It indicates that the developed speed model can adjust to the individual curve speed behavior of each driver.
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Daoliang Li; Yingyi Chen. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-370, pp.92-102, 2012, Computer and Computing Technologies in Agriculture V. 〈10.1007/978-3-642-27275-2_10〉
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Xiaolei Chen, Ruijuan Chi, Jianqiang Wang, Changle Pang, Qing Xiao. Driver Safe Speed Model Based on BP Neural Network for Rural Curved Roads. Daoliang Li; Yingyi Chen. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-370, pp.92-102, 2012, Computer and Computing Technologies in Agriculture V. 〈10.1007/978-3-642-27275-2_10〉. 〈hal-01361123〉

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