In this project, we implemented an end-to-end system that takes in combined visual features of video frames from a normal camera and depth information from a cloud points scanner, and predicts driving policies (vehicle speed and steering angle). We verified the safety of our system by comparing the predicted results with standard behaviors by real-world experienced drivers. Our test results show that the predictions can be considered as accurate in at lease half of the testing cases (50% 80%, depending on the model), and using combined features improved the performance in most cases than using video frames only.

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