vobject / deep-nfshp

Deep neural network trained to drive Need For Speed III: Hot Pursuit

Train a convolutional neural network to play Need For Speed III

Deep neural network trained to drive Need For Speed III: Hot Pursuit (1998).

The model's input is an image of the current situation on screen and outputs a steering angle.

See it in action here: https://youtu.be/V_uwjSzxC84

Overview

TODO: files, parameters, preconditions

File	Description
collect.py	Capture training data from a running NFS process while driving
train.py	Train the model
drive.py	Load a trained model and predict steering for a running NFS process
model-XYZ.h5	Trained model weights

Training

TODO: screen captures, input captures, image proprocessing, data generation, model training, epochs, Tensorboard

Testing

TODO: load model, predict steering angle, send input

Future

A few ideas for improvements. Suggestions or pull requests welcome.

Drive faster

The model has no sense of speed. The speed is artificially capped around 80-90 km/h by using manual transmission and always drive in gear 1. I have a few ideas on how to approach this but nothing backed by research or experience.

Drive all tracks in the game

NFS III: HP comes with 9 race tracks. The current model is only trained on the Summit track and performs well. It also does a decent job driving the never seen Country Woods but it is useless on all other tracks. A future goal is be to train and generalize enough to drive all the tracks in the game.

Stretch goals

• Avoid traffic. The game fills the tracks with traffic if opponents are turned off.
• Manual transmission.
• Script and control the game process from within Python. Would make development and evaluation easier.
• Perform with different camera settings. The CNN was trainged solely on the bumper cam. Other settings work much poorer.
• Perform with different resolutions. The CNN was trainged running the game in 1024x768 windows mode. Other settings work poorer.

References

• Original inspiration was Harrison Kinsley's pygta5: https://github.com/Sentdex/pygta5

• NVIDIA End-to-End Deep Learning for Self-Driving Cars: https://devblogs.nvidia.com/parallelforall/deep-learning-self-driving-cars/

• Modified NVIDIA model: https://github.com/naokishibuya/car-behavioral-cloning

• VEG's Need For Speed III Modern Patch v1.6.1: http://veg.by/en/projects/nfs3/

• Xbox-360-Controller-for-Python: https://github.com/r4dian/Xbox-360-Controller-for-Python

• pyvjoy: https://github.com/tidzo/pyvjoy