An IVC-Based Nuclear Emergency Parallel Evacuation System

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Abstract
Nuclear emergency evacuation is challenging and dangerous, with time constraints, resource limitations, and radiation exposure risks. The development of the Internet of Things (IoT) and artificial intelligence enables us to build an intelligent evacuation system to help mitigate this problem a great deal. In this article, we design the nuclear emergency parallel evacuation system based on the artificial systems (A), computational experiments (C), and parallel execution (P) approach and intelligent vehicle collaborative systems (IVCs). In this system, the evacuation risks of different regions under various possible scenarios are simulated and evaluated in the artificial systems. With data adversarially generated from the artificial systems and collected from sensors all over the area, an optimization model is proposed to find the optimal evacuation plans for emergent evacuation scenarios in the computational experiments. Eventually, the most suitable running strategy of autonomous buses will be selected and carried out based on the parallel execution in accordance with the real scene. A case study is conducted, and results indicate that the system can serve as an efficient tool for future nuclear emergency evacuation planning.
Funding Information
  • National Natural Science Foundation of China (61702519, U1811463)
  • National Key Research and Development Program of China (2018AAA0101502)
  • The Young Elite Scientists Sponsorship Program of China Association of Science and Technology (2017QNRC001)
  • Intel Collaborative Research Institute on Intelligent and Automated Connected Vehicles

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