Evolution of Driving Styles of Driving Agent for Automated Control of Scale Car

在这个项目中，我们开发了一种进化方法来进化驱动代理的驾驶方式。代理自动控制称重车。此外，我们还开发了一种受自然启发的方法来实时定位和绘制障碍物。最后，我们开发了一个增强现实框架来模拟障碍物，并解决了处理真实障碍物的问题。这些问题是对汽车和障碍物的物理损坏，重新定位缓慢，以及移动中的真实障碍物部件的机械磨损。

In this project we developed an evolutionary approach to evolve the driving style of driving agent. The agent automatically controls a scale car. Also, we developed an nature-inspired approach for real-time localization and mapping of obstacle. Finally, we developed an augmented reality framework in order to simulate the obstacle and solve the problems of dealing with real obstacles. These problems are physical damage to the car and obstacle, slow repositioning, and mechanical wear of the components of moving real obstacle.