Adaptive Design of Driver Steering Override Characteristics for LKAS 2019-01-5030
Lane Keeping Assistance System (LKAS) is a typical lateral driver assistance system with low acceptance. One of the main reasons is that fixed parameters cannot satisfy individual differences. So LKAS adaptive to driver characteristics needs to be designed. Driver Steering Override (DSO) process is an important process of LKAS. It happens when contradiction between driver’s intention and system behavior occurs. As feeling of overriding will affect the overall experience of using LKAS, the design of DSO characteristics is worthy of attention. This research provided an adaptive design scheme aiming at DSO characteristics for LKAS by building Driver Preference Model (DPM) based on simulator test data from preliminary experiments. The DPM was to represent the relationship between driver characteristics indices and driver preferred system characteristics indices. So that new drivers’ preference can be predicted by DPM based on their own daily driving data with LKAS switched off. The inputs of DPMs are 27 lane changing driver characteristics indices which were extracted based on natural lane changing data. Principal Component Analysis (PCA) and correlation analysis were used during input-indices selection. The outputs of DPMs are 2 driver preferred system characteristics indices which can express driver’s preferred DSO characteristics. 6 participants took part in preliminary experiments for data collection and evaluation experiments. Their preferred system characteristic indices were calculated through the results of evaluation experiments. The building of DPMs was realized by Random Forest (RF) based on 6 participants’ lane changing driver characteristics indices and driver preferred system characteristics indices. The verification of DPMs’ effectiveness was realized by subjective evaluation. The result showed that DPMs can realize adaptive design of DSO characteristics for LKAS focusing on driver’s preference and improve driver’s acceptance.