Browse Publications Technical Papers 2018-01-1586

Study on Important Indices Related to Driver Feelings for LKA Intervention Process 2018-01-1586

Lane Keeping Assistance (LKA) system is a very important part in Advanced Driver Assistance Systems (ADAS). It prevents a vehicle from departing out of the lane by exerting intervention. But an inappropriate performance during LKA intervention makes driver feel uncomfortable. The intervention of LKA can be divided into 3 parts: intervention timing, intervention process and intervention ending. Many researches have studied about the intervention timing and ending, but factors during intervention process also affect driver feelings a lot, such as yaw rate and steering wheel velocity. To increase driver’s acceptance of LKA, objective and subjective tests were designed and conducted to explore important indices which are highly correlated with the driver feelings.
Different kinds of LKA controller control intervention process in different ways. Therefore, it’s very important to describe the intervention process uniformly and objectively. This paper proposes 16 Characteristic Indices (CI), such as ‘maximum yaw rate’, to describe steering wheel motion, vehicle motion and other aspects during variable LKA intervention processes. Then, to acquire drivers’ subjective evaluation about LKA, a questionnaire including 3 questions from different aspects was designed for drivers to give Subjective Ratings (SR).
Lastly, to describe the nonlinear correlation between CI and SR, Random Forests (RF) algorithm was used to establish the correlation model. Different from other modeling methods, RF can not only build the model by data training, but also give out the importance of each CI in the model.
Through this method, important indices really affecting the driver feelings during the LKA intervention process were explored. What’s more, by the use of CI, the correlation model can predict the driver feelings regardless of specific LKA controller type, thus important indices can be optimized, which means the prediction about SR can be used to offer necessary guidance to the development and calibration of LKA system.


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