Takeover Requests in Highly Automated Truck Driving: How Do the Amount and Type of Additional Information Influence the Driver–Automation Interaction?

Abstract

Vehicle automation is linked to various benefits, such as increase in fuel and transport efficiency as well as increase in driving comfort. However, automation also comes with a variety of possible downsides, e.g., loss of situational awareness, loss of skills, and inappropriate trust levels regarding system functionality. Drawbacks differ at different automation levels. As highly automated driving (HAD, level 3) requires the driver to take over the driving task in critical situations within a limited period of time, the need for an appropriate human–machine interface (HMI) arises. To foster adequate and efficient human–machine interaction, this contribution presents a user-centered, iterative approach for HMI evaluation of highly automated truck driving. For HMI evaluation, a driving simulator study [n = 32] using a dynamic truck driving simulator was conducted to let users experience the HMI in a semi-real driving context. Participants rated three HMI concepts, differing in their informational content for HAD regarding acceptance, workload, user experience, and controllability. Results showed that all three HMI concepts achieved good to very good results in these measures. Overall, HMI concepts offering more information to the driver about the HAD system showed significantly higher ratings, depicting the positive effect of additional information on the driver–automation interaction.

Information Needs and Visual Attention during Urban, Highly Automated Driving—An Investigation of Potential Influencing Factors

“…References [4,11,13,16,18] report a degree of certainty (uncertainty information) with which the automation can cope with the current scenario as relevant. Additionally, it has been reported that the remaining automated travel distance/time is important [11,[19][20][21]. These information requirements have already been incorporated into the HMI design for partially and conditionally automated driving in numerous studies (e.g., [12,14,[22][23][24]).…”

“…Therefore, participants wanted to have an overview of this intersection. In the context of the navigation data, a display of the remaining automated travel time/distance was mentioned only three times, and, in contrast to the literature [11,[19][20][21], had only a subordinate role. On the one hand, this may be due to the fact that there were no interruptions due to requests to intervene, and, on the other hand, no free NDRAs were offered which might have required better planning via the remaining time.…”

The Effects of a Predictive HMI and Different Transition Frequencies on Acceptance, Workload, Usability, and Gaze Behavior during Urban Automated Driving

“…Studies actually investigating design and effects of predictive HMI elements were conducted by Richardson et al [14], Wandtner et al [15], and Holländer et al [12]. All three studies found positive effects; Richardson et al [14] discovered time-and distance-based predictive HMIs for conditionally automated trucks to lower workload, and increase acceptance and usability compared to a baseline HMI with no predictive elements. No difference was found between the predictive HMIs.…”

“…However, post-study questions revealed distance-based HMI to be the favorite. Richardson et al [14] assume the professional truck drivers' background to be the reason for this preference. Positive effects on usability were also found by Holländer et al [12].…”

“…Common to all three studies was the location of the predictive HMI close by or even integrated in the NDRA device and the predetermined NDRA. In Richardson et al [14], the NDRA was given as watching a video on the central information display where also the remaining time or distance was displayed. Holländer et al [12] assessed different NDRA (email correction, text messenger, video task); all three displayed on a central information display with the predictive HMI elements integrated.…”