TY - GEN
T1 - Selecting Flow Optimal System Parameters for Automated Driving Systems
AU - Hauer, Florian
AU - Stern, Raphael
AU - Pretschner, Alexander
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85076807539&partnerID=8YFLogxK
U2 - 10.1109/ITSC.2019.8917047
DO - 10.1109/ITSC.2019.8917047
M3 - Conference contribution
AN - SCOPUS:85076807539
T3 - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
SP - 3776
EP - 3781
BT - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
Y2 - 27 October 2019 through 30 October 2019
ER -