Kibalama, Dennis (The Ohio State University), Spano, Matteo (Politecnico di Torino), Rizzoni, Giorgio (Ohio State Univ)

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

Scheduled for presentation during the Regular Session "Highly Automated and Connected Vehicular Systems-I" (MoAT4), Monday, August 29, 2022, 11:40−12:00, Ballroom

10th IFAC International Symposium on Advances in Automotive Control, August 28-31, 2022, Columbus, Ohio, USA

This information is tentative and subject to change. Compiled on April 24, 2024

Abstract

The 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.