Model Validation of Adaptive Cruise Control in Vehicles Utilizing Real-World Driving Data

Adaptive Cruise Control (ACC) is one of the most significant Advanced Driver Assistance System (ADAS) features. To fully comprehend and quantitatively analyze the impact of the on-road automation on vehicles and transportation systems, it is necessary to validate the models of ACC systems in currently available vehicles. This paper presents a workflow for the modeling and validation of the stock ACC system on the 2018 Cadillac CT6 with the Super Cruise system. The approach makes use of the real-world test-driving data collected by the instrumented test vehicle, analyzes its behavior in various driving scenarios, formulates the ACC system model based on the data, and conducts validation with both simplified vehicle kinetics and the high-fidelity Cadillac CT6 powertrain model by using the energy-focused connected and automated vehicle (CAV) simulator developed by Argonne National Laboratory.