The Two-Step Model of Operating Speed on Horizontal Curves Based on Driver's Information Collection and Processing

Zhong, Xiaoming; Fu-tian, Ren; Rong, Jian; Chen, Yongsheng; Xue, Jingang

doi:10.1061/40730(144)58

Cited by 1 publication

(1 citation statement)

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“…Mistakes during steering is one of the main factors, which fundamentally results from the driver's incorrect recognition or misjudgment of road condition, vehicle performance or surrounding environment, that normally let the driver enter a corner at a high speed [2]. In order to solve the aforementioned problems, many studies have been conducted to calculate the safe speed for cornering and several models have been developed during the last few decades [3][4][5][6][7][8]. According to [3], a predicting model of the 85th percentile speed was developed by Krammers in 1993, and Polus built four speed models based on numbers of speed data to estimate the operating speed for the twolane rural roads.…”

Section: Introductionmentioning

confidence: 99%

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

Chen

Chi

Wang

et al. 2012

Computer and Computing Technologies in Agriculture V

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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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