Route Generation Methodology for Energy Efficiency Evaluation of Connected and Automated Vehicles

Evaluation of the energy savings potential of Connected and Automated Vehicles (CAVs) technologies necessitates a representative baseline that accounts for the inherent variability due to route, terrain, traffic, traffic lights, etc., in real-world driving conditions. While considerable work has been done in the field of optimal energy management, eco-driving and eco-routing of CAVs, few contributions have addressed the creation of a representative baseline to realistically evaluate the energy savings potential of these technologies. This work proposes a route generation methodology based on leveraging a high-dimension driving dataset to construct diverse subset of synthetic driving trips and synthetic routes for large scale evaluation of energy consumption of CAVs. The generated synthetic routes can then be used to extract real-world routes from open-source mapping platforms, which have similar characteristics as the generated synthetic routes.