Interaction strategies with advanced driver assistance systems. (July 2022)

• Record Type: Journal Article
• Authors: Neuhuber, N.; Pretto, P.; Kubicek, B.
• Is Part Of: Transportation research. Volume 88(2022)
• Page Start: 223
• Page End: 235
• Publication Date: 2022-07
• Subjects: Trust in automation -- Trust calibration -- Reliance behavior -- Human-automation interaction -- Safe usage; Automobile drivers -- Psychology -- Periodicals; Automobile driving -- Psychological aspects -- Periodicals; Transportation -- Psychological aspects -- Periodicals; 629.283019
• DOI: 10.1016/j.trf.2022.05.013
• Languages: English
• ISSNs: 1369-8478

Abstract

Highlights: The presented studies provide insights into categories of drivers choosing different interaction strategies when using advanced driver assistance systems. Extreme driver categories with interaction strategies indicative for both misuse and disuse were observable. Results indicate that some drivers had difficulties to adapt their level of trust and reliance strategy to changing driving environments. Results underline the need of tutoring systems that are tailored for different driver categories. Abstract: When using advanced driver assistance systems (ADAS) drivers need to calibrate their level of trust and interaction strategy to changes in the driving context and possible consequent reduction of system reliability (e.g. in harsh weather conditions). By investigating and identifying categories of drivers who choose inadequate interaction strategies, it is possible to address unsafe usage with e.g. tutoring lessons tailored to the respective driver category. This paper presents two studies investigating categories of drivers who apply different interaction strategies when using ADAS. Study I was designed as an exploratory field study with 37 participants interacting with a SAE level 2 system. For the exploratory study, it was important to observe and understand the interaction strategies in a driving context which entails the real complexity of the driving task. The experimental set-up of study II (simulator study), however, allowed to clearly interpret the interaction strategies as either calibrated or un-calibrated by varying the situational risk. Participants (N = 33) were driving in a situation where the system was either working reliably ( low-risk condition ) or in a situation where the system displayed repeatedly errors under harsh weather conditions ( high-risk condition ). Cluster analyses with the variables trust, monitoring behavior towards the system and usage behavior were performed to analyze potential categories of drivers. Extreme driver categories with interaction strategies indicative for both misuse and disuse were observed in both studies. In study I, drivers were categorized as either highly trusting attentive, moderately trusting attentive, moderately inattentive, inattentive or skeptical . In study II, drivers were categorized as either un-calibrated, calibrated, inconsistent or skeptical . Taken together, results underline the need of tutoring systems that are tailored for different driver categories.