Utility assessment in automated driving for cooperative human–machine systems
- 4 Downloads
Currently, car manufacturers, suppliers, and IT companies are surpassing each other with ambitious plans regarding their driving automation technology. However, even the most optimistic announcements grant that, for a certain time, a human driver cannot be replaced in all driving situations. Hence, human drivers will still be a part of future traffic by working together with automation systems. Analyzing the joint decision-making process of such a human–machine system in automated driving provides a better understanding of the resulting traffic system. In this paper, a driving simulator study with 33 participants focusing on the utility of cooperative driver–vehicle systems with the use case of highway driving is presented. Based on the study’s results, a model that explains the linkage between subjective measures such as the perceived utility and objective driving data is derived. Moreover, on an individual level, models are parameterized by using driving states as predictors and the individual utility perceived in a driving situation as response. This individual utility can be used for predicting driving actions such as the initiation of overtaking maneuvers.
KeywordsAutonomous vehicles Automated driving Human–machine systems Decision-making Cooperative guidance and control Game theory
The research conducted was partly funded by the Deutsche For-schungsgemeinschaft (DFG) within the project “SPP 1835: Systemergonomie für kooperativ interagierende Automobile: Nachvollziehbarkeit des Automationsverhaltens und Eingriffsmöglichkeiten des Menschen im Normalbetrieb, a Systemgrenzen und bei Systemausfall”, and partly by RWTH Aachen University.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
Informed consent was obtained from all individual participants included in the study.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
- Abbink D (2006) Neuromuscular analysis of haptic gas pedal feedback during car following (Dissertation). TU Delft, DelftGoogle Scholar
- Altendorf EEO, Baltzer MCA, Heesen M, Kienle M, Weißgerber T, Flemisch FO (2016) H-Mode. In: Winner H, Hakuli S, Lotz F, Singer C (eds.) Handbook of driver assistance systems: basic information, components and systems for active safety and comfort. Springer International Publishing, Cham, pp. 1499–1518. https://doi.org/10.1007/978-3-319-12352-3_60
- Altendorf EEO, SchreckC, Flemisch FO (2017) A new method and results for analyzing decision-making processes in automated driving on highways. In: Stanton NA, Landry S, Di Bucchianico G, Vallicelli A (eds.) Advances in human aspects of transportation: proceedings of the AHFE 2016 international conference on human factors in transportation. Springer International Publishing, Cham, pp. 571–583. https://doi.org/10.1007/978-3-319-41682-3_48
- Baltzer MCA, Flemisch FO, Altendorf EEO, Meier ST (2014) Mediating the interaction between human and automation during the arbitration processes in cooperative guidance and control of highly automated vehicles. In: Proceedings of the 5th international conference on applied human factors and ergonomics AHFEGoogle Scholar
- Baltzer MCA, López D, Flemisch F (2019) Towards an interaction pattern language for human machine cooperation and cooperative movement. Cognition, Technology & Work, 1–14Google Scholar
- Biester L (2008) Cooperative automation in automobiles. Humboldt-Universität, BerlinGoogle Scholar
- Bortz J, Schuster C (2016) Statistik für Human- und Sozialwissenschaftler: Mit 163 Tabellen (Limitierte Sonderausgabe, 7., vollständig überarberarbeitete und, erweiterte edn. Springer, Berlin)Google Scholar
- Bubb H (1993) Ergonomie. 3. Aufl., Kap. 5.3 Systemergonomische Gestaltung, (S. 390–420). Carl Hanser, MünchenGoogle Scholar
- Eggert J, Klingelschmitt S, Damerow F (2015) The foresighted driver: future adas based on generalized predictive risk estimation. In: FAST-zero 2015 symposiumGoogle Scholar
- Field A (2013) Discovering statistics using IBM SPSS statistics. Sage, Thousand OaksGoogle Scholar
- Flemisch FO, Adams CA, Conway SR, Goodrich KH, Palmer MT, Schutte PC (2003) The H-Metaphor as a guideline for vehicle automation and interaction (NASA Technical Memorandum No. NASA/TM-2003-212672)Google Scholar
- Flemisch F, Kelsch J, Löper C, Schieben A, Schindler J, Heesen M (2008) Cooperative control and active interfaces for vehicle assistance and automation. In: FISITA World automotive congress vol 1, pp. 301–310Google Scholar
- Flemisch FO, Abbink D, Itoh M, Pacaux-Lemoine M-P, Weßel G (2016) Shared control is the sharp end of cooperation: towards a common framework of joint action, shared control and human machine cooperation. In: 13th IFAC/IFIP/IFORS/IEA symposium on analysis, design, and evaluation of human–machine systems. Kyoto, JapanGoogle Scholar
- Flemisch FO, Winner H, Bruder R, Bengler KJ (2016b) Cooperative guidance, control, and automation. In: Winner H, Hakuli S, Lotz F, Singer C (eds) Handbook of driver assistance systems: basic information, components and systems for active safety and comfort. Springer International Publishing, Cham, pp 1471–1481. https://doi.org/10.1007/978-3-319-12352-3_58 CrossRefGoogle Scholar
- Flemisch FO, Abbink D, Itoh M, Pacaux-Lemoine M-P, Weßel G (2019) Shared control is the sharp end of cooperation: Towards a common framework of joint action, shared control and human machine cooperation. Cogn Technol Work 19 (accepted) Google Scholar
- Kita H (1999) A merging–giveway interaction model of cars in a merging section: a game theoretic analysis. Transp Res Part A 33:305–312Google Scholar
- Michon JA (1985) A critical view of driver behavior models: what do we know, what should we do? In: Evans L, Schwing RC (eds) Human behavior and traffic safety. Springer, BostonGoogle Scholar
- Millot P, Pacaux-Lemoine M (1998) An attempt for generic concepts toward human-machine cooperation. In: SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No. 98CH36218) Vol 1, pp 1044–1049, IEEEGoogle Scholar
- Rasmussen E (2000) Games and information: an introduction to game theory, 3rd edn. Blackwell Publishers Inc., New YorkGoogle Scholar
- Sheridan TB (2002) Humans and automation: system design and research issues. Wiley, New YorkGoogle Scholar
- Weßel G, Altendorf EEO, Schwalm M, Canpolat Y, Burghardt C, Flemisch FO (2019) Nudge me please: Self-determined decisions in human-machine interaction. Cogn Technol Work (accepted) Google Scholar
- Winner H, Schopper M (2016) Adaptive cruise control. In: Winner H, Hakuli S, Lotz F, Singer C (eds) Handbook of driver assistance systems: basic information, components and systems for active safety and comfort. Springer International Publishing, Cham, pp 1093–1148. https://doi.org/10.1007/978-3-319-12352-3_46 CrossRefGoogle Scholar
- Zijlstra FRH (1995) Efficiency in work behaviour: a design approach for modern tools (Dissertation). TU Delft, DelftGoogle Scholar
- Zijlstra FRH, van Doorn L (1985) The construction of a subjective effort scale. Delft University of Technology, DelftGoogle Scholar