Across the automotive industry, manufacturers have recently released various Partial Automation systems (SAE Level 2) which allow simultaneous/combined execution of both lateral and longitudinal vehicle control at the same time, yet still require active human supervision/engagement. Current reactive trends will be reviewed across major automotive players regarding differences in terminology, HMI input/outputs, and escalation intervals. Scholarly research is also reviewed pertaining to proactive strategies for driver engagement. Additionally, human factors research and findings will be presented regarding recommendations for situation awareness, human machine interfaces, TOR, as well as shared control concepts. The tutorial will conclude with discussion and brainstorming around outlook toward tele-operated remote driving services (Tele-Driving); what they have to offer beyond assisted/automated driving, autonomous vehicles, and ride-hailing/car-sharing paradigms; as well as the design/conduct of human factors research regarding Tele-Driving.

An important research question in the domain of highly automated driving is how to aid drivers in transitions between manual and automated control. Until highly automated cars are available, knowledge on this topic has to be obtained via simulators and self-report questionnaires. Using crowdsourcing, we surveyed 1692 people on auditory, visual, and vibrotactile take-over requests (TORs) in highly automated driving. The survey presented recordings of auditory messages and illustrations of visual and vibrational messages in traffic scenarios of various urgency levels. Multimodal TORs were the most preferred option in high-urgency scenarios. Auditory TORs were the most preferred option in low-urgency scenarios and as a confirmation message that the system is ready to switch from manual to automated mode. For low-urgency scenarios, visual-only TORs were more preferred than vibration-only TORs. Beeps with shorter interpulse intervals were perceived as more urgent, with Stevens’ power law yielding an accurate fit to the data. Spoken messages were more accepted than abstract sounds, and the female voice was more preferred than the male voice. Preferences and perceived urgency ratings were similar in middle- and high-income countries. In summary, this international survey showed that people's preferences for TOR types in highly automated driving depend on the urgency of the situation.

The driver of a conditionally automated car is not required to permanently monitor the outside environment, but needs to take over control whenever the automation issues a “request to intervene” (i.e., take-over request). If the driver misses the take-over request or does not respond in a timely and correct manner, a take-over could result in a safety-critical scenario. Traditionally, warnings in vehicles are conveyed by visual and auditory displays, though recently it has been argued that vibrotactile stimuli could also be a viable approach to present a takeover request to the driver. In this paper, we present a vibrotactile seat designed to convey dynamic vibration patterns to the driver. The seat incorporates 48 vibration motors (eccentric mass rotation) that can be individually controlled. One 6 × 4 matrix, with an average inter-motor distance of approximately 4 cm, is located in the seat back and one in the seat bottom. The DC-voltage to the motors is controlled by three Pulse Width Modulation (PWM) drivers, which in turn are controlled by an Arduino microcontroller. A study with 12 participants was conducted to investigate (1) at which vibration intensity participants find a vibratory stimulus annoying and whether this threshold changes over time, (2) how well participants are able to discriminate vibratory stimuli as a function of spatial separation, and (3) which of six dynamic vibration patterns are regarded as most satisfying. Results showed that participants’ annoyance threshold reduced when they were repeatedly exposed to vibrotactile stimuli. Second, the percentage of correct responses in the two-point discrimination test increased significantly with increasing inter-stimuli distance (i.e., from 4 to 20 cm). Third, participants seemed to be more satisfied when more motors were activated simultaneously (i.e., more spatial overlap). Overall, the results suggest that participants are well able to perceive vibrotractile stimuli in the driver seat. However, the results suggest that repetitive exposure to vibrotactile stimuli may evoke annoyance, a finding that should be taken into account in future designs of vibrotactile displays. Future studies should investigate the possibility to convey complex messages via the vibration seat.

Vibrotactile stimuli can be effective as warning signals, but their effectiveness as directional take-over requests in automated driving is yet unknown. This study aimed to investigate the correct response rate, reaction times, and eye and head orientation for static versus dynamic directional take-over requests presented via vibrating motors in the driver seat. In a driving simulator, eighteen participants performed three sessions: 1) a session involving no driving (Baseline), 2) driving a highly automated car without additional task (HAD), and 3) driving a highly automated car while performing a mentally demanding task (N-Back). Per session, participants received four directional static (in the left or right part of the seat) and four dynamic (moving from one side towards the opposite left or right of the seat) take-over requests via two 6 × 4 motor matrices embedded in the seat back and bottom. In the Baseline condition, participants reported whether the cue was left or right, and in the HAD and N-Back conditions participants had to change lanes to the left or to the right according to the directional cue. The correct response rate was operationalized as the accuracy of the self-reported direction (Baseline session) and the accuracy of the lane change direction (HAD & N-Back sessions). The results showed that the correct response rate ranged between 94% for static patterns in the Baseline session and 74% for dynamic patterns in the N-Back session, although these effects were not statistically significant. Steering wheel touch and steering input reaction times were approximately 200 ms faster for static patterns than for dynamic ones. Eye tracking results revealed a correspondence between head/eye-gaze direction and lane change direction, and showed that head and eye-gaze movements where initiated faster for static vibrations than for dynamic ones. In conclusion, vibrotactile stimuli presented via the driver seat are effective as warnings, but their effectiveness as directional take-over requests may be limited. The present study may encourage further investigation into how to get drivers safely back into the loop.