Optimization of Road Reference Profiles based on Highway Design for Connected and Automated Vehicles

Advances in Connected and Automated Vehicles (CAVs) have developed a level in which high-definition maps can be used to improve road safety. Data compactness and robustness on road characterization is essential for the proper handling of vehicles under curves. In this paper, an optimization scheme that relates highway-design road curvature and optimal speed of travel is defined to safely navigate through a given road. The scheme is divided in two main steps. First a nonlinear optimization problem, in which curvature profiles are fitted from a model that based on street design standards as per the American Association of State Highway and Transportation Officials (AASHTO). Secondly, the optimized curvature profile is subject to a secondary optimization problem that uses vehicle dynamics for both constraints and objective function derivation. Guidance reference parameters such as curvature and velocity, at different levels of friction are analyzed. Results show that, even in sparse datasets, the algorithm can leverage on highway design to generate proper velocity profiles. These profiles in turn can be used to enhance existing wireless communication infrastructure and autonomous vehicle technology.