Comfort and Safety in Conditional Automated Driving in Dependence on Personal Driving Behavior

Abstract

When changing from active driving to conditional automated driving (CAD), the question arises whether users still prefer their own driving behavior while being a passenger. The aim of this paper is to analyze driving behavior preferences in CAD based on the perception of comfort and safety, taking the personal driving behavior into account. Furthermore, it is investigated if users are able to manually demonstrate their desired driving behavior for CAD. Data on the personal, desired and experienced automated driving behavior of 42 participants from a real-world study was used to investigate both research questions for car-following (CF) and decelerating to a lead vehicle (DL) situations. In a first step, the personal and desired driving behavior is compared with the automated driving behavior based on selected parameters. Subsequently, the relationship between behavior differences and the assessed situation comfort and safety is analyzed. The results show a dependency between differences of personal and automated driving behavior and subjective ratings for comfort and safety. Furthermore, results suggest that participants prefer a driving behavior similar to or more defensive than their own for CAD. Our findings also show that participants were able to demonstrate their desired comfort driving behavior in CF and DL situations.

Dilemma of Responsibility-Sensitive Safety in Longitudinal Mixed Autonomous Vehicles Flow: A Human-Driver-Error-Tolerant Driving Strategy

“…Given that HDVs are not controllable directly, it is feasible to achieve specific objectives through AVs' controllers. Utilizing controlled vehicles to influence the movement dynamics is not a novel concept [53]. For example, AVs have been employed to mitigate jerks or oscillation waves [28], [54].…”

Control Transitions in Level 3 Automation: Safety Implications in Mixed-Autonomy Traffic

“…Another motivational factor behind those research studies was to derive indicators of how to conceive takeover strategies in simulation models and automated driving systems with respect to lead times and post-ToC behavior. Recently, studies have focused on human responses to prototypical Level 3 automated driving systems in terms of physiological effects, risk acceptance, comfort level, trust, and various other aspects from the perspective of being in a passenger role during Level 3 operation [12][13][14][15][16][17][18]. An extensive literature review examining various influential factors on takeover performance is given by [19].…”