Effect of Environmental Factors and Individual Differences on Subjective Evaluation of Human-Like and Conventional Automated Vehicle Controllers

Abstract

Achieving optimal performance in human-machine systems, such as highly automated vehicles, relies, in part, on individuals’ acceptance and use of the system, which is in turn affected by their enjoyment of engaging with, or experiencing, the system. This driving simulator study investigated individuals’ real-time subjective evaluation of four different Automated Vehicle (AV) driving styles, in different environmental contexts. Twenty-four participants were recruited to manually drive a contextually rich simulator environment, and to experience human-like and non-human-like AV driving styles, as well as the automated replay of their own manual drive. Their subjective real-time feedback towards these driving styles was analyzed. Our results showed that participants gave higher positive feedback towards the replay of their own drive, compared to the other three controllers. This difference was statistically significant, when compared to the high-speed controller (named as Fast), particularly for sharp curves. With respect to the replay of their own drive, participants gave higher negative feedback when navigating an Urban environment, compared to Rural settings. Moreover, changes in roadside furniture affected individuals’ feedback, and this effect was more prominent when the vehicle was driving closer to the edge of the road. Based on our results, we conclude that individuals’ perception of different AV driving styles changes based on different environmental conditions, including, but not limited to, road geometry and roadside furniture. These findings suggest that humans prefer a slower human-like driving style for AV controllers that adapts its speed and lateral offset to roadside objects and furniture. Investigating individual differences in AV driving style preference showed that low Sensation Seeking individuals preferred the slower human-like controller more than the faster human-like controller. Consideration of this human-centered feedback is important for the design of future AV controllers, to enhance individuals’ ride experience, and potentially improve acceptance and use of these vehicles.

Keywords: Driver behaviourReal-time feedbackAutomated Vehicle Driving styleHighly automated driving (HAD)