Translated Abstract
For the practical implementation of autonomous driving, it is required that a single operator remotely monitors multiple vehicles and performs recovery operations as needed. To achieve this, it is essential to reduce the burden on operators during recovery operations. This study evaluates the impact of information presentation of remote monitoring systems on the operator’s workload and work efficiency. The remote monitoring systems used in previous autonomous driving demonstration experiments can be classified into two types based on the differences in their expression of the recognition and judgment of autonomous driving systems. We conducted experiments simulating these two systems and analyzed the characteristics and challenges of each system. The results indicated that the system providing system-level information allowed operators to pay attention to objects that humans typically do not focus on, while it might increase annoyance in high-traffic situations. On the other hand, in the system that presents information concisely with diagrams, although there are objects that are difficult to notice, if the provided information is appropriate for situation understanding, it can guide operators’ attention and potentially reduce the operation time.
References
- [1] Secretariat of the Council for the Realization of the Vision for a Digital Garden City Nation, Cabinet Secretariat: Comprehensive Strategy for the Vision for a Digital Garden City Nation (DIGIEN), Secretariat of the Council for the Realization of the Vision for a Digital Garden City Nation, Cabinet Secretariat (online), available from (https://www.cas.go.jp/jp/seisaku/digital denen/pdf/20221223 gaiyou-e.pdf) (accessed 2024-5-31).
- [2] 愛知県:平成30年度自動運転実証推進事業成果報告書(概要版) ,愛知県(オンライン) , 入手先(https://www.pref.aichi.jp/uploaded/attachment/299708.pdf) (参照2024-5-31).
- [3] SAE International: J3016 Level of Automated Driving.
- [4] Du, N., Haspiel, J., Zhang, Q., Tilbury, D., Pradhan , A. K., Yang , X. J., Robert Jr, L. P.: Look who’s talking now: Implications of AV’s explanations on driver’s trust, AV preference, anxiety and mental workload, Transportation research part C: emerging technologies, Vol.104, pp.428-442 (2019).
- [5] Koo, J., Kwac, J., Ju, W., Steinert, M., Leifer, L., Nass, C.: Why did my car just do that? Explaining semi-autonomous driving actions to improve driver understanding, trust, and performance, International Journal on Interactive Design and Manufacturing (IJIDeM), Vol.9, pp.269-275 (2015).
- [6] Körber, M., Prasch, L., Bengler K.: Why Do I Have to Drive Now? Post Hoc Explanations of Takeover Requests, Human factors, Vol.60, No.3, pp.305-323 (2018).
- [7] Yokota, M., Tsutsumi, S., Hayakawa, S., Ikeura, R.: Research on effects and influence by presenting information on priority order and oncoming vehicle to operators for teleoperation of multiple autonomous vehicles, Journal of Physics: Conference Series, Vol. 2107, No. 1 (2021).
- [8] Yasui, T., Otsu, K., Izumi, T.: Verification of Continuous Recovery Operation with Teleoperation System for Autonomous Vehicles, The transaction of Human Interface Society, Vol.26, No.1, pp.125-136 (2024) (in Japanese).
- [9] The Subcommittee on Business Discussions on Autonomous Driving Technologies: Progress reporton efforts to support the development of autonomous driving technologies and create adequate policies version 4.0.
- [10] Siemens : Simcenter Prescan software (online), available from (https://plm.sw.siemens.com/en-US/simcenter/autonomous-vehiclesolutions/prescan/) (accessed 2024-06-04).
- [11] Github: Ultralytics(online), available from (https://github.com/ultralytics/ultralytics) (accessed 2024-6-8).
- [12] Tobii : Tobii Pro Glasses 3 (online), available from (https://www.tobii.com/products/eye-trackers/wearables/tobii-pro-glasses-3) (accessed 2024-6-8).
- [13] Haga, S., Mizukami, N.: Japanese version of NASA Task Load Index: Sensitivity of its workload score to difficulty of three different laboratory task, The Japanese journal of ergonomics, Vol.32, No.2, pp.71-79 (1996) (in Japanese).
- [14] Zang, Y., Kumada, T.: Relationship between workload and mind-wandering in simulated driving, PloS one, 12(5) (2017).
- [15] Jin, H., Zhu, L., Li, M., Duffy, VG.: Recognition and evaluation of mental workload in different stages of perceptual and cognitive information processing using a multimodal approach, Ergonomics, Vol.67, Issue 3, pp.377-397 (2023).
- [16] Wu, L., Zhu, Z., Li, B.: Influence of information overload on operator’s user experience of human-machine interface in LED manufacturing system, Cognition, Techinology & Work, Vol.18, pp.161-173 (2016).