Abstract

As the development of autonomous vehicles accelerates, the need for robust and cost-effective testing solutions becomes paramount. This paper explores the concept of zero-cost solutions for testing autonomous vehicle software, aiming to reduce development expenses while maintaining high testing efficacy. We examine various methodologies, tools, and strategies that leverage existing resources to create effective testing frameworks without significant financial investment. Case studies and practical implementations illustrate the feasibility and benefits of these approaches in real-world scenarios.

Keywords

  • hybrid energy system
  • artificial intelligence
  • predictive control
  • thermodynamic efficiency
  • economic efficiency
  • SAEO
  • hydrogen energy
  • renewable energy sources
  • optimization
  • SCADA.

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