Is a level 2 self driving system that performs functions like Adaptive cruise control (ACC), Automated Lane Centering (ALC), Fowards Collision Warning (FCW) and Lane Departure Wanring (LDW) and uses data from it vision system to determine the appropriate driving path, speed, throtle and velocity.
We system is built in python and will be deployed in c++ to increase speed and efficiency. We use normal computer vision to get data from a camera module installed as a dashcam. The data from the camera goes through various processes (ie.) Lane detection, object detection, semantic segmentation, Visual Odometry and motion planning to output a driving signals. The signals are then sent to the car ECU via an OBD2 port connection in the car.
Using basic computer vision comes with its fair of downsides (ie.):
our goal is to use supervised LSTM in Reinforcement Learning combine both of its advantages (context and dynamic) nature to create a full end-to-end driving module that is dynamic and applies context from it pervious experience to output driving signals
Me !!!!!