Autonomous Vehicle (AV) technology has the potential to fundamentally transform the automotive industry, reorient transportation infrastructure, and significantly impact the energy sector. Rapid progress is being made in the core artificial intelligence engines that form the basis of AV technology. However, without a quantum leap in testing and verification, the full capabilities of AV technology will not be realized. Critical issues include finding and testing complex functional scenarios, verifying that sensor and object recognition systems accurately detect the external environment independent of weather conditions, and building a regulatory regime that enables accumulative learning. The significant contribution of this article is to outline a novel methodology for solving these issues by using the Florida Poly AV Verification Framework (FLPolyVF).
Autonomous Vehicles Scenario Testing Framework and Model of Computation
Sae Intl. J Cav
Sae International Journal of Connected and Automated Vehicles ; 2 , 4 ; 205-218
18.12.2019
14 pages
Aufsatz (Konferenz)
Englisch
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