Self-Driving Car Simulation using Genetic Algorithm

Engineering notes

Key topics: self-driving vehicle, self-driving car, self-driving. See the paper for implementation details and experimental results.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

: For the past decade, there has been a surge of interest in self-driving vehicles. This is because of leaps in the field of deep learning especially Artificial Neural Networks which are trained to perform tasks that regularly require human intervention. Genetic algorithms (GA) apply models to identify patterns and features in the environment making them desirous in cases of uncertainty. In this project we have trained an evolving Neural network by using Genetic Algorithms in Unity Game Engine using the ML-agents provided by them. By repeated simulation of the agent in the environment, using this we have created an agent which learns unique features from the environment based on its input and generates a forecast permitting the vehicle to drive without requiring external commands from the player.

Links and sources

• Official / arXiv page
• PDF from original source

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