Road-following with continuous learning

A neural network-based road-following system is proposed to take vision sensor input (road boundary images) and generate steering control output while maintaining the vehicle moving within road boundaries. Unlike many existing neural network-based systems that only use the supervised mode of neural learning, the proposed system also uses a reinforcement learning mode to eliminate the need for external supervision and at the same time provides the system with continuous learning ability similar to human driving practice. The simulation results demonstrate the system´s good road-following and continuous learning capability. The future plans include a full scale simulation and the construction of a real system