Abstract

Simulations are 3D environments that are based on real-world scenarios. As technology is evolving in automobiles, the need for advancement in Artificial Intelligence (AI) of automobiles and to train AI systems of the automobiles are getting expansive. This study investigates the problem of collecting reference data for the testing and evaluation algorithms for autonomous vehicles using unity simulation. Using computer simulations is one way to solve this issue. A genuine system modeled using computer simulations, including all of its static and dynamic properties. There are 4 modules: forward & backward collision, speed warning, traffic light & sign detection, and lane departure system. All the modules are implemented in C# language and the unity-3d platform. The composite collider module is used for the lane departure in which the line render algorithm is applied for forwarding/backward collision. This method reduces the testing period while ensuring accuracy and efficiency in data collection. The construction of a simulation environment based on Unity with the ability to test sensors and algorithms for autonomous cars and display deviations from reference data is the goal of this research work. Roads, sidewalks, buildings, traffic signs, and automobiles are among the common city players, and items in the simulation model are presented in the simulation. The simulation is tested by the methods like black box testing, use case testing, performance testing, stress testing, module testing, Software-In-the-loop, Driver-in-the loop testing.