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Vehicle manufacturers are racing to create autonomous navigation and steeringcontrol algorithms for their vehicles. These software are made to handlevarious real-life scenarios such as obstacle avoidance and lane maneuvering.There is some ongoing research to incorporate pothole avoidance into theseautonomous systems. However, there is very little research on the effect ofhitting a pothole on the autonomous navigation software that uses cameras tomake driving decisions. Perturbations in the camera angle when hitting apothole can cause errors in the predicted steering angle. In this paper, wepresent a new model to compensate for such angle perturbations and reduce anyerrors in steering control prediction algorithms. We evaluate our model onperturbations of publicly available datasets and show our model can reduce theerrors in the estimated steering angle from perturbed images to 2.3%, makingautonomous steering control robust against the dash cam image angleperturbations induced when one wheel of a car goes over a pothole.

Towards Increasing the Robustness of Predictive Steering-Control  Autonomous Navigation Systems Against Dash Cam Image Angle Perturbations Due  to Pothole Encounters