Visible to the public Selecting Flow Optimal System Parameters for Automated Driving Systems Conflict Detection Enabled

TitleSelecting Flow Optimal System Parameters for Automated Driving Systems
Publication TypeConference Proceedings
Year of Publication2019
AuthorsHauer, Florian, Raphael Stern, Alexander Pretschner
Conference Name22nd International Conference on Intelligent Transportation Systems
PublisherIEEE
Conference LocationNew Zealand
KeywordsACC, adaptive cruise control, automotive, autonomous driving, autonomous driving system parameters, Driver assistance systems, highway assistants, model-based optimization, optimization and control, Safety, simulation and modeling, string stable, traffic, Traffic flow, Transportation
Abstract

Driver assist features such as adaptive cruise control (ACC) and highway assistants are becoming increasingly prevalent on commercially available vehicles. These systems are typically designed for safety and rider comfort. However, these systems are often not designed with the quality of the overall traffic flow in mind. For such a system to be beneficial to the traffic flow, it must be string stable and minimize the inter-vehicle spacing to maximize throughput, while still being safe. We propose a methodology to select autonomous driving system parameters that are both safe and string stable using the existing control framework already implemented on commercially available ACC vehicles. Optimal parameter values are selected via model-based optimization for an example highway assistant controller with path planning.

Citation Keynode-62090