Effectiveness and Driver Acceptance of Sharing Decision and Control in Automated Driving

• Published in: Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics pp. 4447 - 4452
• Main Authors: Muslim, Husam, Liang, Cho Kiu, Itoh, Makoto
• Format: Conference Proceeding
• Language: English
• Published: IEEE 11.10.2020
• Subjects: Cybernetics; Driver acceptance; Human-machine interface; Lane change; Levels of automation; Man-machine systems; Roads; Shared control; System performance; Task analysis; Usability; Vehicles
• ISSN: 2577-1655
• DOI: 10.1109/SMC42975.2020.9282853

Automated driving systems (ADS) in which human control is not required can only be achieved in limited and well predictable environments. Thus far, ADS users are expected to contribute to the automated process when requested by the system, during critical situations, and to ensure adequate system performance. Using a driving simulator experiment, this study developed a human-machine interface (HMI) in which the drivers can share decisions and control with the ADS to avoid slow traffic on highways. Following within-subjects design, the participants encountered four ADS designs in a randomized order: 1) the driver may regain the vehicle control and avoid the slow traffic manually without ADS support (no sharing); 2) an ADS requests the driver to resume the vehicle control and avoid the slow traffic manually (sharing decisions); 3) an ADS avoids the slow traffic autonomously if the driver approves it (sharing decision and control); and 4) an ADS avoids the slow traffic autonomously without driver's approval. Results indicated that the drivers preferred the first and second ADS designs more than the third and fourth ADS designs. However, significantly better system usability, drivers' engagement, and driving performance have been achieved by the third ADS design compared to other ADS designs. These results have implications for the safe implementation of partial and conditional driving automation systems.