Human-Centered Intervention Based on Tactical-Level Input in Unscheduled Takeover Scenarios for Highly-Automated Vehicles

Due to functional limitations in certain situations, the driver receives a request to intervene from automated vehicles operating level 3. Unscheduled intervention of control authority would lead to insufficient situational awareness, then this will make dangerous situations. The purpose of this study is thus to propose tactical-level input (TLI) method with a multimodal driver-vehicle interface (DVI) for the human-centered intervention. The proposed DVI system includes touchscreen, hand-gesture, and haptic interfaces that enable interaction between driver and vehicle, and TLI along with such DVI system can enhance situational awareness. We performed unscheduled takeover experiments using a driving simulator to evaluate the proposed intervention system. The experimental results indicate that TLI can reduce reaction time and driver workload, and moreover, most drivers preferred the use of TLI than manual takeover.

[1]  Klaus Bengler,et al.  “Take over!” How long does it take to get the driver back into the loop? , 2013 .

[2]  Neville A. Stanton,et al.  Take-Over Time in Highly Automated Vehicles , 2018, Driver Reactions to Automated Vehicles.

[3]  Jean Scholtz,et al.  Beyond usability evaluation: analysis of human-robot interaction at a major robotics competition , 2004 .

[4]  John A. Michon,et al.  A critical view of driver behavior models: What do we know , 1985 .

[5]  David B. Kaber,et al.  The effects of level of automation and adaptive automation on human performance, situation awareness and workload in a dynamic control task , 2004 .

[6]  Joost C. F. de Winter,et al.  A Review and Framework of Control Authority Transitions in Automated Driving , 2015 .

[7]  Natasha Merat,et al.  Driver Inattention During Vehicle Automation: How Does Driver Engagement Affect Resumption Of Control? , 2015 .

[8]  Shigeki Sugano,et al.  Analysis of Preference for Autonomous Driving Under Different Traffic Conditions Using a Driving Simulator , 2015, J. Robotics Mechatronics.

[9]  Frederik Naujoks,et al.  Testing Scenarios for Human Factors Research in Level 3 Automated Vehicles , 2017 .

[10]  Mark S. Young,et al.  Vehicle automation and driving performance , 1998 .

[11]  Erwin R. Boer,et al.  Development of a steering entropy method for evaluating driver workload , 1999 .

[12]  Neville A. Stanton,et al.  Takeover Time in Highly Automated Vehicles: Noncritical Transitions to and From Manual Control , 2017, Hum. Factors.

[13]  Shigeki Sugano,et al.  A haptic feedback driver-vehicle interface for controlling lateral and longitudinal motions of autonomous vehicles , 2016, 2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM).

[14]  Shigeki Sugano,et al.  A multimodal human-machine interface enabling situation-adaptive control inputs for highly automated vehicles , 2017, 2017 IEEE Intelligent Vehicles Symposium (IV).