Automated Driving Capabilities using advanced software tools to improve optimization for Autonomous Vehicle in Industry 4.0

Autonomous vehicles are still evolving in Industry 4.0 and moving closer to becoming a reality. As technology advances in the context of intelligent world capabilities for self-driving cars, systems become more complicated and humans as engineers must employ several techniques to produce a product with fewer flaws. The graphical representation of technological developments is rising quickly over time and will reach its apex soon. Since it is extremely difficult to create a product from zero in this market, developers may benefit greatly from the industry's cutting-edge tools like MATLAB & Simulink for creation, analysis, simulation, testing, and verification. These tools for software development offer excellent solutions at every stage of creating a strong and efficient targeted goal. The self-driving car and its advancements, including ADAS levels, functional building blocks, smart sensors, sensor fusion capabilities, and the integration of these physical systems with cutting-edge software tools to address problems that arise in the real world, are the focus of this research. Additionally, autonomous cars can use interdisciplinary elements to strengthen them. Finally, we have proposed a strategy that entails building an effective architecture, employing data optimization techniques for efficient data processing, using the V-Model testing and verification cycle for autonomous cars, and integrating Auto Code generation into independent standalone application deployment features.