A Multi-layer Autonomous Vehicle and Simulation Validation Ecosystem Axis: ZalaZONE

2018 
Developing autonomous driving technologies is complex and needs to be approached from multiple directions. However, these vectors of development need to intersect at one point and our answer is ZalaZONE. This proving ground design is unique when it comes to the development of automated driving technologies and has grass-root origins in higher education and industry. However, the proving ground is not the total solution, but acts as a catalyst and synergistic hub for the different directional vectors addressing autonomous vehicle development. ZalaZONE in its role as an education and research centre from the secondary to the highest trinary educations levels supports this basic progressive vector and creates the first layer. A second layer concerns the proving ground’s core function, being used not only for classical dynamic testing, but focusing on the evaluation of the most troublesome “use cases” that simulation indicates. The evaluation of these indicated “use cases” will required autonomous vehicles to be tested at their dynamic limits in a 100% controlled and safe environment. Similarly, the proving ground is designed to calibrate and validate current and future simulation systems, also a significant technological metamorphosis. Public road testing is a third layer or point of axis supported by the PG. Legislative changes in Hungary offer a flexible regulatory environment within Europe for autonomous vehicle testing and this allows the PG to be a one stop hub for launching test in various environments, from live urban to the usage of a tri-national testbed road network in the Hungarian, Slovenian, Austrian enclave. Fourth and fifth layers nurtured by ZalaZONE are “sample vehicles fleet services” and “crowd-sourced traffic cloud” data collection and analysis. This paper will discuss all these 5 complex and integrated axis points and how ZalaZONE provides this synergistic role in this new Multi-layer autonomous vehicle and simulation validation Ecosystem.
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