In the section Components of an AV system we outlined several modules, necessary for a self-driving system. In this section we'll discuss how to implement one of them - the driving policy - with the help of DL. One way to do this is with RL, where the car is the agent and the environment is, well, the environment. Another popular approach is imitation learning, where the model (network) learns to imitate the actions of an expert (human). Let's see the properties of imitation learning in the AV scenario:
- We'll use a type of imitation learning, known as behavioral cloning. This simply means that we'll train our network in a supervised way. Alternatively, we have imitation learning in RL scenario, which is known as Inverse RL.
- The output of the network is the driving policy, represented by desired steering angle and/or acceleration...
