Orchestration of driving simulator scenarios based on dynamic actor preparation and automated action planning |
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| Institution: | 1. Research Centre for Integrated Transportation Innovation (rCITI), School of Civil and Environmental Engineering, The University of New South Wales, UNSW, Sydney, NSW 2052, Australia;2. Institute for Transport Studies and School of Computing, University of Leeds, Leeds LS2 9JT, United Kingdom;3. Swedish National Road and Transport Research Institute (VTI), SE-581 95 Linköping, Sweden;4. Linköping University, Department of Science and Technology (ITN), SE-601 74 Norrköping, Sweden;1. Bureau of Labor Statistics, Census of Fatal Occupational Injuries, 2 Massachusetts Avenue NE, Room 3180, Washington, DC 20212 USA;2. National Institute for Occupational Safety and Health, Division of Safety Research, 1095 Willowdale Road, Mail Stop H-1808, Morgantown, WV 26505 USA;1. College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, PR China;2. Department of Mechanical Engineering, University of Manitoba, Winnipeg, MB R3T 5V6, Canada;1. State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Beijing 100083, China;2. Institute of Geosciences, Christian-Albrechts-University, Kiel D-24118, Germany;3. China National Offshore Oil Corporation, Beijing, 100010, China;4. Department of Geoscience, University of Wisconsin-Madison, Madison, WI 53706, USA;1. Computer Engineering Department, Tarbiat Modares University, Tehran, Iran;2. Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran;1. Department of Physics, Channabasaveshwara Institute of Technology, VTU affiliated , Gubbi 572216, India;2. Department of Physics, Sree Siddaganga College for Women, Tumkur 572103, India;3. Prof. C.N.R. Rao Centre for Advanced Materials, Tumkur University, Tumkur 572103, India;4. Dayananda Sagar University, Shavige Malleshwara Hills, Kumaraswamy Layout, Bangalore 560078, India;5. Department of Physics, Lal Bahadur Shastry Government First Grade College, Bangalore 560032, India;6. Research Center, Department of Science, East West Institute of Technology, VTU affiliated, Bangalore 560091, India;7. Department of Physics, BMS Institute of Technology, VTU affiliated , Bangalore 560064, India;8. Department of Studies and Research in Environmental Science, Tumkur University, Tumkur 572103, India |
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| Abstract: | In driving simulation, a scenario includes definitions of the road environment, the traffic situation, simulated vehicles’ interactions with the participant’s vehicle and measurements that need to be collected. The scenarios need to be designed in such a way that the research questions to be studied can be answered, which commonly imply exposing the participant for a couple of predefined specific situations that has to be both realistic and repeatable. This article presents an integrated algorithm based on Dynamic Actor Preparation and Automated Action Planning to control autonomous simulated vehicles in the simulation in order to generate predefined situations. This algorithm is thus able to plan driving actions for autonomous vehicles based on specific tasks with relevant contextual information as well as handling longitudinal transportation of simulated vehicles based on the contextual information in an automated manner. The conducted experiment shows that the algorithm is able to guarantee repeatability under autonomous traffic flow. The presented algorithm can benefit not only the driving simulation community, but also relevant areas, such as autonomous vehicle and in-vehicle device design by providing them with an algorithm for target pursue and driving task accomplishment, which can be used to design a human-vehicle cooperation system in the coming era of autonomous driving. |
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| Keywords: | Driving simulators Scenario orchestration Surrounding vehicles Experimental design Autonomous vehicle |
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