journal article·2022-07-16Open access

Research on Transparency Design Based on Shared Situation Awareness in Semi-Automatic Driving

Fang You, Huijun Deng, Preben Hansen, Jun Zhang

Applied Sciences· Volume 12· Issue 14

Abstract

While automated driving has attracted more and more attention, human drivers still play an important role. Drivers must be aware of their surroundings and potential danger to take over the vehicle’s control immediately when the automation system cannot function, which could otherwise pose a road safety risk. The transparent design of the human–machine interface can accurately convey the perceived information of the machine to help drivers understand the dynamic environment. We designed the scenario where the rear vehicle is about to overtake the ego vehicle and has a dangerous tendency to collide with the ego vehicle by stepping on the lane line. We analyzed the information shared by the intelligent system in this scenario to make “transparent” the intelligent system. According to the requirements of the task model of transparency and the three stages of situation awareness, we formed three designs. Then we analyzed the availability, situation awareness, and workload of different designs. Results showed that the transparency design according to the shared situation awareness stage can have a positive impact on the usability of the intelligent system. Therefore, the effective transparency-based design in automated driving can enhance the user’s understanding of the system and improve their experience.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Human-Automation Interaction and Safety · Safety Warnings and Signage · Traffic and Road Safety

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Car Interaction Design Lab, College of Arts and Media, Tongji University, Shanghai 201804, China

Shenzhen Research Institute, Sun Yat-Sen University, Shenzhen 518057, China

Department of Computer and Systems Sciences, Stockholm University, 114 19 Stockholm, Sweden

College of Design and Innovation, Tongji University, Shanghai 200092, China

Funding

National Social Science Fund of China · CES-Kingfar Excellent Young Scholar Joint Research Funding · China Scholarship Council Foundation · Shenzhen Collaborative Innovation Project · Shenzhen Basic Research Program for Shenzhen Virtual University Park

References (21)

Show source-provided references
1. Nof, S. (2009). Automation: What It Means to Us Around the World. Springer Handbook of Automation, Springer.10.1007/978-3-540-78831-7 ↗
2. Haidegger, T. (2021). Taxonomy and Standards in Robotics. Encyclopedia of Robotics, Springer.10.1007/978-3-642-41610-1_190-1 ↗
3. (2016). Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles (Standard No. J3016_202104).
4. Evans, L., and Schwing, R.C. (1985). A critical view of driver behavior models: What do we know, what should we do?. Human Behavior and Traffic Safety, Springer Science & Business Media.10.1007/978-1-4613-2173-6 ↗
5. Trust in automation: Designing for appropriate reliance10.1518/hfes.46.1.50.30392 ↗
6. Lyons, J.B. (2013, January 25–27). Being transparent about transparency: A model for human- robot interaction. Proceedings of the AAAI Spring Symposium: Trust and Autonomous System, Palo Alto, CA, USA.
7. Designing Human-Machine Interface for Autonomous Vehicles10.1016/j.ifacol.2016.10.629 ↗
8. How to make automated systems team players
9. Meixner, G., and Müller, C. (2017). From Car-Driver-Handovers to Cooperative Interfaces: Visions for Driver–Vehicle Interaction in Automated Driving. Automotive User Interfaces, Springer.10.1007/978-3-319-49448-7 ↗
10. Endsley, M.R. (1988, January 24–28). Design and evaluation for situation awareness enhancement. Proceedings of the Human Factors & Ergonomics Society Annual Meeting, Anaheim, CA, USA.
11. Intelligent Agent Transparency in Human-Agent Teaming for Multi-UxV Management10.1177/0018720815621206 ↗
12. A model for types and levels of human interaction with automation10.1109/3468.844354 ↗
13. Beggiato, M., Schleinitz, K., and Krems, J. (2015, January 25–26). What would drivers like to know during automated driving? Information needs at different levels of automation. Proceedings of the 7th Conference on Driver Assistance, Munich, Germany.
14. Diels, C., and Thompson, S. (2018). Information expectations in highly and fully automated vehicles. Advances in Human Aspects of Transportation, Proceedings of the International Conference on Applied Human Factors and Ergonomics, Los Angeles, CA, USA, 17–21 July 2017, Springer.10.1007/978-3-319-60441-1_71 ↗
15. Principles of transparency for autonomous vehicles: First results of an experiment with an augmented reality human–machine interface10.1007/s10111-019-00552-9 ↗
16. Driver error or designer error: Using the Perceptual Cycle Model to explore the circumstances surrounding the fatal Tesla crash on 7th May 201610.1016/j.ssci.2017.12.023 ↗
17. Handover Process of Autonomous Vehicles–Technology and Application Challenges10.12700/APH.16.9.2019.9.13 ↗
18. Experiment Research on HMI Usability Test Environment Based on Driving Simulator
19. Psychometric evaluation of an after-scenario questionnaire for computer usability studies: The ASQ10.1145/122672.122692 ↗
20. Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research10.1016/S0166-4115(08)62386-9 ↗
21. Endsley, M.R. (2000). Direct Measurement of Situation Awareness: Validity and Use of SAGAT. Situation Awareness Analysis and Measurement, Lawrence Erlbaum Associates Publishers.10.1201/b12461 ↗