The goal of this study is to generate a better route for the car under certain conditions (minimise energy usage) while taking battery, motor, traffic time, and other factors into consideration.
Take a moment to download the following Python files: main.py, Environment.py, DoubleDQN.py, battery.py, and motor.py.
- In main.py, enter your starting location using the name or geocode (lat, lng)
- Enter the name of the position or the geocode for your destination in main.py (lat, lng)
- Enter the step length in main.py as each step's length. line 78, which is higher but less precise (ex: 1000m takes less time to train compare to 100m) in main.py, type the number of episodes you wish to train.
- Main.py has to have several file and folder path names updated to meet your situation.
- During the training process, make sure you have access to the internet and Google Maps.