Latest revision as of 10:47, 15 February 2021

Abstract

In order to improve the adaptation of driver to the advanced driver assistance system (ADAS) and optimize the active safety control technology of vehicle under man-computer cooperative driving, this paper investigated the correlation between driver’s improper driving behaviors and abnormal vehicle states under the ADAS. Based on the warning data collected from the driver’s assistance warning system equipped on buses, the interaction between improper behaviors, between abnormal vehicle states, and between improper behaviors and abnormal vehicle states were quantitatively analyzed through the hierarchical clustering method and improved Apriori algorithm. The results showed that eye closure and yawn were high in concurrency (probability: 0.888) and interaction (average probability: 0.946); the interaction among lane departure, rapid acceleration, and rapid deceleration are frequent (average probability: 0.7224); eye closure (average probability: 0.452) and yawn (average probability: 0.444) are likely to induce abnormal vehicle states such as rapid acceleration and rapid deceleration. Some suggestions proposed based on the results are as follows. First, it is suggested that the ADAS should combine the warning modes of eye closure and yawn; second, when the driver closes eyes or yawns, the control of the ADAS over the lateral and longitudinal performance of vehicle should be enhanced; third, the extent of control by the ADAS should be determined according to the relationship probability; finally, the lateral control over the vehicle by the ADAS should be strengthened when there is a forward collision warning.

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The different versions of the original document can be found in:

• http://dx.doi.org/10.1155/2020/9743504 under the license http://creativecommons.org/licenses/by/4.0/

• https://doi.org/10.1155/2020/9743504

• http://downloads.hindawi.com/journals/mpe/2020/9743504.pdf,

http://downloads.hindawi.com/journals/mpe/2020/9743504.xml,

http://dx.doi.org/10.1155/2020/9743504 under the license cc-by

• https://www.hindawi.com/journals/mpe/2020/9743504,

http://downloads.hindawi.com/journals/mpe/2020/9743504.pdf,

https://academic.microsoft.com/#/detail/3080761611 under the license http://creativecommons.org/licenses/by/4.0/