A Dynamically-Concise Roadmap Framework for Guiding Connected and Automated Vehicles

A new map framework is proposed to improve the guidance and trajectory prediction capabilities of connected and automated vehicles (CAVs), even in challenging conditions of low visibility and adverse environmental effects. Based on the fusion of vehicle dynamics and road design standards, the map framework provides a consolidated collection of critical reference points of roadways, such as centerlines and information about the shape of the roadway in the vicinity of a vehicle, including curvature and road alignment angle. Roads are discretized using reference points, and simple parameters are used to connect adjacent segments representing the road shape. Additional data can be appended to the map, including elevation and roadside slope data, variable speed limits, and lane controls.