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Autonomous driving is no longer just an idea of technology vision instead a real technical trend all over the world. The continuing development to a further level of autonomy requires more on mobile robots safety while bringing more challenges to human-vehicle interaction. A robot autonomous vehicle (AV) as a research platform operates an experimental study on human-AV-interaction (HAVI) and performs a novel method for mobile robot safety assurance. Not only autonomous driving technology itself but human cognition also performs an essential role in how to ensure better autonomous mobile robot safety. A Wizard-of-Oz experiment in the university combing a survey-based study indicates public attitudes towards driverless robot vehicles. HAVI experiment have been carried through light patterns designed for experiment. This paper presents an attempt to investigate humans’ acceptance and emotions as well as a validation to bring the mobile robot vehicle to a high-level autonomy.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
114--125
Opis fizyczny
Bibliogr. 30 poz., rys., tab.
Twórcy
autor
- Tallinn University of Technology, Tallinn, Estonia
autor
- Tallinn University of Technology, Tallinn, Estonia
autor
- Tallinn University of Technology, Tallinn, Estonia
autor
- Tallinn University of Technology, Tallinn, Estonia
autor
- Tallinn University of Technology, Tallinn, Estonia
Bibliografia
- [1] ROTHENBUCHER D., LI J., SIRKIN D., MOK B., JU W., 2016, Ghost Driver: A Field Study Investigating the Interaction Between Humans tnd Driverless Vehicles, 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN), 795–802.
- [2] LAGSTRÖM T., LUNDGREN V.M., 2015, AVIP – Autonomous Vehicles Interaction with Humans, Chalmers University, Retrieved from http://publications.lib.chalmers.se/records/fulltext/238401/238401.pdf
- [3] CLAMANN M., AUBERT M., CUMMINGS M.L., 2017, Evaluation of Vehicle-to-Human Communication Displays for Autonomous Vehicles, 96th Annual Transportation Research Board Meeting, Washington DC.
- [4] DAHLBÄCK N., JÖNSSON A., AHRENBERG L., 1993, Wizard of Oz Studies – Why and How, Knowledge-Based Syst., 6/4, 258–266.
- [5] Automated Driving Roadmap, 2015, Brussels, Belgium.
- [6] KYRIAKIDIS M., HAPPEE R., DE WINTER J.C.F., 2015, Public Opinion on Automated Driving: Results of an International Questionnaire Among 5000 Respondents, Transp. Res. Part F Traffic Psychol. Behav., 32, 127–140.
- [7] SELL R., LEIER M., RASSÕLKIN A., ERNITS J.-P., 2018, Self-Driving Car ISEAUTO for Research and Education, 19th International Conference on Research and Education in Mechatronics (REM 2018).
- [8] EVERINGHAM M., 2015, The Pascal Visual Object Classes Challenge: A Retrospective, Int. J. Comput. Vis., 111/1, 98–136.
- [9] LIN T.Y., 2014, Microsoft COCO: Common Objects in Context, Springer, Cham, 740–755.
- [10] RASSÕLKIN A., GEVORKOV L., VAIMANN T., KALLASTE A., SELL R., 2018, Calculation of the Traction Effort of ISEAUTO Self-Driving Vehicle, 25th International Workshop on Electric Drives: Optimization in Control of Electric Drives (IWED), 1–5.
- [11] RASSÕLKIN A., VAIMANN T., KALLASTE A., 2018, Propulsion Motor Drive Topology Selection for Further Development of ISEAUTO Self-Driving Car, 59th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON).
- [12] SELL R., RASSÕLKIN A., RUXIN W., OTTO T., 2019, Integration of Autonomous Vehicles and Industry 4.0, Proceedings of the Estonian Academy of Sciences, 68/4, 389–394.
- [13] DEB S., WARNER B., POUDEL S.R., BHANDARI S., 2016, Identification of External Design Preferences in Autonomous Vehicles, Proceedings of the Industrial and Systems Engineering Research Conference, Anaheim, California.
- [14] TURNER C., MCCLURE R., 2003, Age and Gender Differences in Risk-Taking Behaviour as an Explanation for High Incidence of Motor Vehicle Crashes as a Driver in Young Males, Inj. Control Saf. Promot., 10/3, 123–130.
- [15] LIU P., ZHANG Y., HE Z., 2019, The Effect of Population Age on The Acceptable Safety of Self-Driving Vehicles, Reliab. Eng. Syst. Saf., 185, 341–347.
- [16] ALESSANDRINI A., ALFONSI R., SITE P.D., STAM D., 2014, Users’ Preferences Towards Automated Road Public Transport: Results from European Surveys, Transp. Res. Procedia, 3, 139–144.
- [17] KUTS V., OTTO T., TÄHEMAA T., BONDARENKO Y., 2019. Digital Twin Based Synchronised Control and Simulation of The Industrial Robotic Cell Using Virtual Reality, Journal of Machine Engineering, 19/1, 128−145.
- [18] DAVIS F.D., 1989, Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS Q., 13/3, 319–340.
- [19] XU Z., 2018, What Drives People to Accept Automated Vehicles? Findings From a Field Experiment, Transp. Res. Part C Emerg. Technol., 95, 320–334.
- [20] ZHANG T., 2019, The Roles of Initial Trust and Perceived Risk in Public’s Acceptance of Automated Vehicles, Transp. Res. Part C Emerg. Technol., 98, 207–220.
- [21] PARASURAMAN R., SHERIDAN T.B., WICKENS C.D., 2000, A Model for Types and Levels of Human Interaction with Automation, IEEE Trans. Syst. Man, Cybern. – Part A Syst. Humans, 30/3, 286–297.
- [22] LEE J.D., SEE K.A., 2004, Trust in Automation: Designing for Appropriate Reliance, Hum. Factors J. Hum. Factors Ergon. Soc., 46/1, 50–80.
- [23] KÖRBER M., BASELER E., BENGLER K., 2018, Introduction Matters: Manipulating Trust in Automation and Reliance in Automated Driving, Appl. Ergon., 66, 18–31.
- [24] WILKINSON R.G., PICKETT K. E., 2006, Income Inequality and Population Health: A Review and Explanation of the Evidence, Soc. Sci. Med., 62/7, 1768–1784.
- [25] DEB S., RAHMAN M.M., STRAWDERMAN L.J., GARRISON T.M., 2018, Pedestrians’ Receptivity Toward Fully Automated Vehicles: Research Review and Roadmap for Future Research, IEEE Trans. Human–Machine Syst., 48/3, 279–290.
- [26] MARANGUNIĆ N., GRANIĆ A., 2015, Technology Acceptance Model: A Literature Review from 1986 to 2013, Univers. Access Inf. Soc., 14/1, 81–95.
- [27] DAVIS F.D., BAGOZZI R.P., WARSHAW P.R., 1989, User Acceptance of Computer Technology: A Comparison of Two Theoretical Models, Management Science, 35/8, 982–1003.
- [28] MOKHTARZADEH A.A., YANGQING Z.J., 2018, Human-Robot Interaction and Self-Driving Cars Safety Integration of Dispositif Networks, IEEE Inter. Conference on Intelligence and Safety for Robotics (ISR), 494–499.
- [29] BROOKS R., 2017, The Big Problem With Self-Driving Cars Is People, IEEE Spectrum, Retrieved from https://spectrum.ieee.org/transportation/self-driving/the-big-problem-with-selfdriving-cars-is-people
- [30] SELL R., OTTO T., 2008, Remotely Controlled Multi Robot Environment, Proceedings of 19th EAEEIE Annual Conference, Tallinn, Estonia, 20−25.
Typ dokumentu
Bibliografia
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