Autonomous robot road following has been widely investigated since the early 1980s and, whilst much progress has been shown, there is still no system which displays 100% generality across all types of problem. This work shows a novel approach to the problem, using the methodology of Evolutionary Robotics to facilitate the autonomous emergence of flexible, robust and general behaviours. One of the unique aspects of this approach is to encourage the evolution of a dynamic strategy of colour perception: facilitating the combination of different channels of the colour space to perceive contrast across a range of scenes where this would otherwise be impossible. The results described herein demonstrate the capability of this methodology to produce controllers capable of generalising across a broad range of road shapes to which the agents have not been previously exposed. They also vindicate the effectiveness of a dynamic colour perception strategy, enabling the controllers to perceive contrast in a challenging variety of situations.