Developing Requirements to Validate Autonomous Ground Vehicle Simulations
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Research
Autonomous Vehicles, Simulation Validation, Virtual Testing
Abstract
This project developed a methodology for assessing simulation testing of the United States’ military autonomous vehicle platforms. The authors conducted background research of autonomous vehicles and simulation to determine the best virtual testing methods that provided the strongest evidence of simulation performance. The team created a requirements list for the simulation software of autonomous vehicles to help drive the virtual test development and conducted statistical analyses, pairwise comparisons, and visual analysis tests to assess simulation data compared to data from physical test runs. The authors identified multiple methods of virtual testing that can assess the autonomous vehicle simulation for further development.
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References
476622/sensor-deployment-analysis-with-the-virtual-autonomous-navigation-environment/.
Jokela, Maria, Kutila, Matti, and Pyykonen, Pasi. (2019). Testing and Validation of Automotive Point-Cloud Sensors in Adverse Weather Conditions. Applied Sciences, 9(11), 2341. https://doi.org/10.3390/app9112341.
Jones, R.A., Priddy, J.D. Horner, D.A., and Peters, J.F. (2008). Virtual Autonomous Navigation Environment (VANE). Earth and Space 2008. https://doi.org/10.1061/40988(323)114.
MITRE Staff. (2018). Verification and validation of simulation models. The MITRE Corporation. Retrieved September 27, 2021, https://www.mitre.org/publications/systems-engineering-guide/se-lifecycle-building-blocks/other-se-lifecycle-building-blocks-articles/verification-and-validation-of-simulation-models.
National Research Council. (2002). Technology Development for Army Unmanned Ground Vehicles. Washington, DC: The National Academies Press. https://doi.org/10.17226/10592.
Sargent, R. (2013) Verification and Validation of Simulation Models. J Simulation, 7, 12–24. https://doi.org/10.1057/jos.2012.20 and https://link.springer.com/article/10.1057/jos.2012.20.
Shacklett, M. (2019). LiDAR: Promise and Challenge in Autonomous Vehicles: What happens in Detroit doesn't stay in Detroit when it comes to LiDAR. Point of Beginning, 45(2), 8+. https://link.gale.com/apps/doc/A607581245/PPMI?u=west10360&sid=bookmark-PPMI&xid=25ed7ef0.
United States Army Futures Command. (2022). Who We Are: Cross Functional Teams. Army Futures Command. https://armyfuturescommand.com/cft/.
Zhao, Jian, Li, Yaxin, Zhu, Bing, Deng, Weiwen, and Sun, Bohua (2021). Method and Applications of Lidar Modeling for Virtual Testing of Intelligent Vehicles, IEEE Transactions on Intelligent Transportation Systems, 22(5), 2990–3000. https://doi.org/10.1109/tits.2020.2978438.
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