Journal of Research and Development
Open Access

Department of Computer Science, India

Publications

• Review Article   
  A Comparative Analysis of CARLA and AirSim Simulators: Investigating Implementation Challenges in Autonomous Driving
  Author(s): Manav Khambhayata*
  
  The advancement of autonomous driving technologies relies heavily on effective training methodologies for self-driving car AI. Reinforcement learning has emerged as a promising approach in this domain. In this paper, we present a comparative analysis of training strategies for self-driving cars using two popular simulators: CARLA and AirSim. We focus solely on the comparison between the two simulators by implementing them using current technology, analyzing their ease of implementation, and identifying the associated challenges. CARLA offers ease of setup and a realistic environment, while AirSim provides excellent overall performance despite its challenging setup process. However, integrating CARLA with TensorFlow poses certain difficulties. To conduct the comparative analysis, we implemented reinforcement learning algorithms on both simulators and evaluated their performance metrics.. View More»
  

  Abstract PDF