Print Email Facebook Twitter Adaptive Cruise Control Utilizing Noisy Multi-Leader Measurements Title Adaptive Cruise Control Utilizing Noisy Multi-Leader Measurements: A Learning-Based Approach Author Ni, Y. (Student TU Delft; ETH Zürich) Knoop, V.L. (TU Delft Transport and Planning) Kooij, J.F.P. (TU Delft Intelligent Vehicles) van Arem, B. (TU Delft Transport and Planning) Date 2024 Abstract A substantial number of vehicles nowadays are equipped with adaptive cruise control (ACC), which adjusts the vehicle speed automatically. However, experiments have found that commercial ACC systems which only detect the direct leader amplify the propagating disturbances in the platoon. This can cause severe traffic congestion when the number of ACC-equipped vehicles increases. Therefore, an ACC system which also considers the second leader further downstream is required. Such a system enables the vehicle to achieve multi-anticipation and hence ensure better platoon stability. Nevertheless, measurements collected from the second leader may be comparatively inaccurate given the limitations of current state-of-the-art sensor technology. This study adopts deep reinforcement learning to develop ACC controllers that besides the input from the first leader exploits the additional information obtained from the second leader, albeit noisy. The simulation experiment demonstrates that even under the influence of noisy measurements, the multi-leader ACC platoon shows smaller disturbance and jerk amplitudes than the one-leader ACC platoon, indicating improved string stability and ride comfort. Practical takeaways are twofold: first, the proposed method can be used to further develop multi-leader ACC systems. Second, even noisy data from the second leader can help stabilize traffic, which makes such systems viable in practice. Subject Adaptive cruise controlcar-followingdeep reinforcement learningmeasurement noisemulti-anticipationNoiseNoise measurementRadarRadar detectionStability criteriastring stabilityUncertaintyVehicle dynamics To reference this document use: http://resolver.tudelft.nl/uuid:1721f48d-a44e-4b3e-b156-4ca6e05324e1 DOI https://doi.org/10.1109/OJITS.2024.3395149 ISSN 2687-7813 Source IEEE Open Journal of Intelligent Transportation Systems, 5, 251-264 Part of collection Institutional Repository Document type journal article Rights © 2024 Y. Ni, V.L. Knoop, J.F.P. Kooij, B. van Arem Files PDF Adaptive_Cruise_Control_U ... proach.pdf 2.23 MB Close viewer /islandora/object/uuid:1721f48d-a44e-4b3e-b156-4ca6e05324e1/datastream/OBJ/view