Driving Behaviour Analysis Software for Data-Driven Path Planning Functionalities for Automated Vehicles
Autonomous driving is currently one of the most challenging Artificial Intelligence (AI) problems as it requires combination of state-of-the-art solutions in multiple areas including computer vision, sensor fusion, control theory and software engineering. Deep learning has been pivotal to solving some of these problems, especially in computer vision. This enabled some autonomous vehicle companies started leveraging the benefits of deep learning for creating smooth, natural, human-like motion planning systems. In particular, the plethora of driving data captured from modern cars is a key enabler for training data-driven path planning systems. , Developing deep learning-powered systems relies heavily on big and high-quality data required for training of the models, in which the intrinsic statistics of the data that the model is trained on can result in different agent behavior in different scenarios.