scholarly journals Context-Adaptive Availability Notifications for an SAE Level 3 Automation

2021 ◽  
Vol 5 (4) ◽  
pp. 16
Author(s):  
Simon Danner ◽  
Alexander Feierle ◽  
Carina Manger ◽  
Klaus Bengler

Context-adaptive functions are not new in the driving context, but even so, investigations into these functions concerning the automation human–machine interface (aHMI) have yet to be carried out. This study presents research into context-adaptive availability notifications for an SAE Level 3 automation in scenarios where participants were surprised by either availability or non-availability. For this purpose, participants (N = 30) took part in a driving simulator study, experiencing a baseline HMI concept as a comparison, and a context-adaptive HMI concept that provided context-adaptive availability notifications with the aim of improving acceptance and usability, while decreasing frustration (due to unexpected non-availability) and gaze deviation from the road when driving manually. Furthermore, it was hypothesized that participants, when experiencing the context-adaptive HMI, would activate the automated driving function more quickly when facing unexpected availability. None of the hypotheses could be statistically confirmed; indeed, where gaze behavior was concerned, the opposite effects were found, indicating increased distraction induced by the context-adaptive HMI. However, the trend in respect to the activation time was towards shorter times with the context-adaptive notifications. These results led to the conclusion that context-adaptive availability notifications might not always be beneficial for users, while more salient availability notifications in the case of an unexpected availability could be advantageous.

Information ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 114 ◽  
Author(s):  
Barbara Metz ◽  
Johanna Wörle ◽  
Michael Hanig ◽  
Marcus Schmitt ◽  
Aaron Lutz

Most studies on users’ perception of highly automated driving functions are focused on first contact/single usage. Nevertheless, it is expected that with repeated usage, acceptance and usage of automated driving functions might change this perception (behavioural adaptation). Changes can occur in drivers’ evaluation, in function usage and in drivers’ reactions to take-over situations. In a driving simulator study, N = 30 drivers used a level 3 (L3) automated driving function for motorways during six experimental sessions. They were free to activate/deactivate that system as they liked and to spend driving time on self-chosen side tasks. Results already show an increase of experienced trust and safety, together with an increase of time spent on side tasks between the first and fourth sessions. Furthermore, attention directed to the road decreases with growing experience with the system. The results are discussed with regard to the theory of behavioural adaptation. Results indicate that the adaptation of acceptance and usage of the highly automated driving function occurs rather quickly. At the same time, no behavioural adaptation for the reaction to take-over situations could be found.


Information ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 73 ◽  
Author(s):  
Tobias Hecht ◽  
Stefan Kratzert ◽  
Klaus Bengler

Automated driving research as a key topic in the automotive industry is currently undergoing change. Research is shifting from unexpected and time-critical take-over situations to human machine interface (HMI) design for predictable transitions. Furthermore, new applications like automated city driving are getting more attention and the ability to engage in non-driving related activities (NDRA) starting from SAE Level 3 automation poses new questions to HMI design. Moreover, future introduction scenarios and automated capabilities are still unclear. Thus, we designed, executed, and assessed a driving simulator study focusing on the effect of different transition frequencies and a predictive HMI while freely engaging in naturalistic NDRA. In the study with 33 participants, we found transition frequency to have effects on workload and acceptance, as well as a small impact on the usability evaluation of the system. Trust, however, was not affected. The predictive HMI was used and accepted, as can be seen by eye-tracking data and the post-study questionnaire, but could not mitigate the above-mentioned negative effects induced by transition frequency. Most attractive activities were window gazing, chatting, phone use, and reading magazines. Descriptively, window gazing and chatting gained attractiveness when interrupted more often, while reading magazines and playing games were negatively affected by transition rate.


2020 ◽  
Vol 4 (3) ◽  
pp. 36
Author(s):  
Tobias Hecht ◽  
Simon Danner ◽  
Alexander Feierle ◽  
Klaus Bengler

Current research in human factors and automated driving is increasingly focusing on predictable transitions instead of urgent and critical take-overs. Predictive human–machine interface (HMI) elements displaying the remaining time until the next request to intervene were identified as a user need, especially when the user is engaging in non-driving related activities (NDRA). However, these estimations are prone to errors due to changing traffic conditions and updated map-based information. Thus, we investigated a confidence display for Level 3 automated driving time estimations. Based on a preliminary study, a confidence display resembling a mobile phone connectivity symbol was developed. In a mixed-design driving simulator study with 32 participants, we assessed the impact of the confidence display concept (within factor) on usability, frustration, trust and acceptance during city and highway automated driving (between factor). During automated driving sections, participants engaged in a naturalistic visual NDRA to create a realistic scenario. Significant effects were found for the scenario: participants in the city experienced higher levels of frustration. However, the confidence display has no significant impact on the subjective evaluation and most participants preferred the baseline HMI without a confidence symbol.


Author(s):  
Davide Maggi ◽  
Richard Romano ◽  
Oliver Carsten

Objective A driving simulator study explored how drivers behaved depending on their initial role during transitions between highly automated driving (HAD) and longitudinally assisted driving (via adaptive cruise control). Background During HAD, drivers might issue a take-over request (TOR), initiating a transition of control that was not planned. Understanding how drivers behave in this situation and, ultimately, the implications on road safety is of paramount importance. Method Sixteen participants were recruited for this study and performed transitions of control between HAD and longitudinally assisted driving in a driving simulator. While comparing how drivers behaved depending on whether or not they were the initiators, different handover strategies were presented to analyze how drivers adapted to variations in the authority level they were granted at various stages of the transitions. Results Whenever they initiated the transition, drivers were more engaged with the driving task and less prone to follow the guidance of the proposed strategies. Moreover, initiating a transition and having the highest authority share during the handover made the drivers more engaged with the driving task and attentive toward the road. Conclusion Handover strategies that retained a larger authority share were more effective whenever the automation initiated the transition. Under driver-initiated transitions, reducing drivers’ authority was detrimental for both performance and comfort. Application As the operational design domain of automated vehicles (Society of Automotive Engineers [SAE] Level 3/4) expands, the drivers might very well fight boredom by taking over spontaneously, introducing safety issues so far not considered but nevertheless very important.


2021 ◽  
Author(s):  
J. B. Manchon ◽  
Mercedes Bueno ◽  
Jordan Navarro

Trust in Automation is known to influence human-automation interaction and user behaviour. In the Automated Driving (AD) context, studies showed the impact of drivers’ Trust in Automated Driving (TiAD), and linked it with, e.g., difference in environment monitoring or driver’s behaviour. This study investigated the influence of driver’s initial level of TiAD on driver’s behaviour and early trust construction during Highly Automated Driving (HAD). Forty drivers participated in a driving simulator study. Based on a trust questionnaire, participants were divided in two groups according to their initial level of TiAD: high (Trustful) vs. low (Distrustful). Declared level of trust, gaze behaviour and Non-Driving-Related Activities (NDRA) engagement were compared between the two groups over time. Results showed that Trustful drivers engaged more in NDRA and spent less time monitoring the road compared to Distrustful drivers. However, an increase in trust was observed in both groups. These results suggest that initial level of TiAD impact drivers’ behaviour and further trust evolution.


Information ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 239 ◽  
Author(s):  
Yannick Forster ◽  
Viktoria Geisel ◽  
Sebastian Hergeth ◽  
Frederik Naujoks ◽  
Andreas Keinath

Research on the role of non-driving related tasks (NDRT) in the area of automated driving is indispensable. At the same time, the construct mode awareness has received considerable interest in regard to human–machine interface (HMI) evaluation. Based on the expectation that HMI design and practice with different levels of driving automation influence NDRT engagement, a driving simulator study was conducted. In a 2 × 5 (automation level x block) design, N = 49 participants completed several transitions of control. They were told that they could engage in an NDRT if they felt safe and comfortable to do so. The NDRT was the Surrogate Reference Task (SuRT) as a representative of a wide range of visual–manual NDRTs. Engagement (i.e., number of inputs on the NDRT interface) was assessed at the onset of a respective episode of automated driving (i.e., after transition) and during ongoing automation (i.e., before subsequent transition). Results revealed that over time, NDRT engagement increased during both L2 and L3 automation until stable engagement at the third block. This trend was observed for both onset and ongoing NDRT engagement. The overall engagement level and the increase in engagement are significantly stronger for L3 automation compared to L2 automation. These results outline the potential of NDRT engagement as an online non-intrusive measure for mode awareness. Moreover, repeated interaction is necessary until users are familiar with the automated system and its HMI to engage in NDRTs. These results provide researchers and practitioners with indications about users’ minimum degree of familiarity with driving automation and HMIs for mode awareness testing.


2018 ◽  
Vol 2 (4) ◽  
pp. 68 ◽  
Author(s):  
Natalie T. Richardson ◽  
Lukas Flohr ◽  
Britta Michel

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.


Author(s):  
Harald Witt ◽  
Carl G. Hoyos

Accident statistics and studies of driving behavior have shown repeatedly that curved roads are hazardous. It was hypothesized that the safety of curves could be improved by indicating in advance the course of the road in a more effective way than do traditional road signs. A code of sequences of stripes put on right edge of the pavement was developed to indicate to the driver the radius of the curve ahead. The main characteristic of this code was the frequency of transitions from code elements to gaps between elements. The effect of these markings was investigated on a driving simulator. Twelve subjects drove on simulated roads of different curvature and with different placement of the code in the approach zone. Some positive effects of the advance information could be observed. The subjects drove more steadily, more precisely, and with a more suitable speed profile.


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