Towards Increasing the Robustness of Predictive Steering-Control
  Autonomous Navigation Systems Against Dash Cam Image Angle Perturbations Due
  to Pothole Encounters
Shivam Aarya
Vehicle manufacturers are racing to create autonomous navigation and steering
control algorithms for their vehicles. These software are made to handle
various real-life scenarios such as obstacle avoidance and lane maneuvering.
There is some ongoing research to incorporate pothole avoidance into these
autonomous systems. However, there is very little research on the effect of
hitting a pothole on the autonomous navigation software that uses cameras to
make driving decisions. Perturbations in the camera angle when hitting a
pothole can cause errors in the predicted steering angle. In this paper, we
present a new model to compensate for such angle perturbations and reduce any
errors in steering control prediction algorithms. We evaluate our model on
perturbations of publicly available datasets and show our model can reduce the
errors in the estimated steering angle from perturbed images to 2.3%, making
autonomous steering control robust against the dash cam image angle
perturbations induced when one wheel of a car goes over a pothole.