| Summary: | Reliable assessment methods of driver acceptance are needed due to increased interest in high levels of autonomous driving systems. Subjective evaluation methods have mostly been utilized to assess the acceptance of newly developed advanced driver assistance systems because acceptance varies depending on the individual. In this paper, an objective evaluation methodology of driver acceptance for an autonomous driving system was proposed based on objective measurable parameters in the case of automatic lane change situations. To this end, a massive driver–vehicle interaction database was utilized, constructed by a specially designed experimental program. The experiment was carried out with 19 selected drivers (9 experts and 10 novices), supposed as an autonomous driving system. The database consisted of not only various measurable parameters on control commands, vehicle behaviors, and relations with other vehicles but also subjective acceptances. To interpret the driver acceptance, objective parameter sets were derived by two different methods: a statistical significance test and an acceptance sensitivity analysis. Then, a modeling method based on stochastic estimation to evaluate driver acceptance was suggested as an objective evaluation method for the driver acceptance of an automatic lane change system. The data set of the expert drivers was only used for the acceptance evaluation modeling; the other data sets of the novice drivers were used for verifications for the suggested model. The estimation accuracies of the two different models using a significance test and sensitivity analysis were 90.2% and 99.5%, respectively. This objective method for acceptance evaluation can not only be expanded to other functions of an autonomous driving system but also to an entirely autonomous driving vehicle.
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