Modelling the Intrusive feelings of advanced driver assistance systems based on vehicle activity log data: a case study for the lane keeping assistance system

TL;DR

This paper investigates drivers' emotional responses to advanced driver assistance systems, specifically lane keeping assistance, by analyzing vehicle activity logs to develop metrics for intrusive feelings and improve system design.

Contribution

It introduces a novel quantitative method to measure intrusive feelings caused by LKAS using vehicle log data, aiding affectively satisfactory system design.

Findings

Identified four types of intrusive feelings related to LKAS.

Developed a metric to quantify intrusive feelings from sensor data.

Provided a statistical analysis method for evaluating driver affective responses.

Abstract

Although the automotive industry has been among the sectors that best-understands the importance of drivers' affect, the focus of design and research in the automotive field has long emphasized the visceral aspects of exterior and interior design. With the adoption of Advanced Driver Assistance Systems (ADAS), endowing 'semi-autonomy' to the vehicles, however, the scope of affective design should be expanded to include the behavioural aspects of the vehicle. In such a 'shared-control' system wherein the vehicle can intervene in the human driver's operations, a certain degree of 'intrusive feelings' are unavoidable. For example, when the Lane Keeping Assistance System (LKAS), one of the most popular examples of ADAS, operates the steering wheel in a dangerous situation, the driver may feel interrupted or surprised because of the abrupt torque generated by LKAS. This kind of unpleasant experience can lead to prolonged negative feelings such as irritation, anxiety, and distrust of the system. Therefore, there are increasing needs of investigating the driver's affective responses towards the vehicle's dynamic behaviour. In this study, four types of intrusive feelings caused by LKAS were identified to be proposed as a quantitative performance indicator in designing the affectively satisfactory behaviour of LKAS. A metric as well as a statistical data analysis method to quantitatively measure the intrusive feelings through the vehicle sensor log data.