Evaluating How Interfaces Influence the User Interaction with Fully Autonomous Vehicles

Abstract

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Driving Style: How Should an Automated Vehicle Behave?

“…AV's communication capabilities could be displayed on internal [86] and external [46] interfaces available to the users, as this interaction improves the understanding of the vehicle with time [87]. However, the design of the information delivered to the occupants of AVs should take into consideration the related workload, as too much information can have a negative effect, making users anxious [88].…”

How to Interact with a Fully Autonomous Vehicle: Naturalistic Ways for Drivers to Intervene in the Vehicle System While Performing Non-Driving Related Tasks

“…The ranking question was then followed by asking participants to evaluate each input interaction using a 5-point Likert scale (1—very low, 5—very high) based on 7 parameters: “Familiarity”, “Quick to learn”, “Easy to use”, “Satisfactory”, “Naturalistic”, “Controlling”, “Useful”, and overall participant satisfaction. Previous studies have found that these seven parameters are paramount for general user interface design, particularly for in-vehicle infotainment systems [ 18 , 48 , 63 ]. Since the evaluation of “Familiarity” and “Quick to learn” parameters are not affected with a change in NDRTs, these parameters where evaluated once in each survey.…”

“…While developments in interior design [ 5 , 9 , 18 ] were studied to better accommodate drivers, their interaction needs inside FAVs have yet to be fully addressed [ 10 , 19 , 20 ]. Researchers should consider the conditions of individual drivers and what they might need to do.…”

“…Since FAVs integrate more technology and require a broader variety of interaction than nonautonomous vehicles [ 24 ], identifying the best input interactions will also enhance AV acceptance and allow drivers to seamlessly continue performing NDRTs safely, efficiently, and intuitively. In other words, these input interactions should be easy to learn and intuitive to use, and must not increase driver stress [ 18 , 19 , 20 ]. Our goal is to understand the most natural input interactions that allow drivers to perform multiple intervention scenarios while engaged in different levels of NDRTs.…”

“…Proposed Intervention Scenarios: Our study presented six intervention scenarios that cover both Maneuver-Based Interventions (MBIs) (four scenarios) and Nonmaneuver-Based Interventions (NMBI) (two scenarios). MBIs include lateral control, longitudinal control, stopping the vehicle at a designated area [ 12 , 17 , 53 ], and rerouting the navigation [ 18 ]. NMBIs include requesting information (e.g., about an interesting building or available parking near the final destination) [ 12 , 17 , 53 ] which is then shown on the head-up display, the most preferred display [ 25 , 54 ], and controlling in-vehicle features, such as playing a video using the in-vehicle infotainment system [ 11 , 21 ], ( Table 2 ).…”