Corroborative Evaluation of the Real-world Energy Saving Potentials of InfoRich Eco-Autonomous Driving (iREAD) System 2020-01-0588
There has been an increasing interest in exploring the potentials of reducing energy consumption of future connected and automated vehicles (CAVs). People have extensively studied various eco-driving implementation that leverages preview information provided by on-board sensors and connectivity, as well as the control authority enabled by automation. To quantitatively evaluate the benefits of eco-driving in a real-world setting is a challenging task. The regulatory standard driving cycles that are being used for exhaust emissions and fuel economy measurements are not truly representative of real-world driving. To adequately take into account the real-world or “off-cycle” driving behavior, this paper presents four collaborative evaluation methods: large-scale simulation, in-depth simulation, vehicle-in-the-loop test, and vehicle road test. These four approaches, each focuses on certain aspects, evaluate the real-world fuel economy benefits with different ranges and resolutions. The large-scale simulation analyses real-world human driving data to generate statistical results of eco-driving benefits in various road network and to suggest representative routes for further evaluation. Based on the representative routes, in-depth simulation relies on high-fidelity models and looks into how different traffic scenarios can impact the eco-driving performance. Vehicle-in-the-loop (VIL) setup reinforces the in-depth study by conducting tests with actual vehicle operated on chassis dyno and providing consistent energy-saving measurement. In the end, limited but representative road test with the fully-integrated vehicle will be conducted to demonstrate the eco-driving capability and conclude the overall test results.