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Design and Experimental Analysis of an Adaptive Cruise Control

Stephan Sundermann, Daniel Göhring, Raúl Rojas – 2022

Nowadays, cars are equipped with quite a few Advanced Driver Assistant Systems(ADAS) to increase comfortability and safety while driving. Adaptive Cruise Control (ACC) is one of these ADAS systems that keeps a certain distance to a heading vehicle in front by smoothly adapting the vehicle’s speed. Usually, this is implemented using a separate PID controller for the velocity and distance or a MIMO system. This paper proposes a novel Fuzzy Logic approach for an autonomous model car called Autominy. The AutoMiny platform was developed at Dahlem Center for Machine Learning and Robotics at Freie Universität Berlin. It is equipped with a software stack for fully autonomous driving with custom modules for localization, control, and navigation. AutoMiny navigates using a pre-build vector force field approach. The proposed Fuzzy Logic controller can handle two states with different profiles. We extend the evaluating between our approach against a standard PID controller approach.

Design and Experimental Analysis of an Adaptive Cruise Control
Advanced Driver Assistance Systems, Adaptive Cruise Control, Fuzzy logic; Vector force field
DOI: 10.1007/978-3-031-19650-8_4
Erschienen in
Proceedings of the First International Conference, ROBOVIS 2020, Virtual Event, November 4-6, 2020, and Second International Conference, ROBOVIS 2021, Virtual Event, October 27-28, 2021, Revised Selected Papers
Alomari, K., Sundermann, S., Goehring, D., Rojas, R. (2022). Design and Experimental Analysis of an Adaptive Cruise Control. In: Galambos, P., Kayacan, E., Madani, K. (eds) Robotics, Computer Vision and Intelligent Systems. ROBOVIS ROBOVIS 2020 2021. Communications in Computer and Information Science, vol 1667. Springer, Cham. https://doi.org/10.1007/978-3-031-19650-8_4
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22 pages
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