Investigating Platoon Formation With Reduced-Scale Robots

Zhuopeng Xie, Mohsen Ramezani and David Levinson
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David Levinson: TransportLab, School of Civil Engineering, University of Sydney

Working Papers from University of Minnesota: Nexus Research Group

Abstract: Keywords: platooning longitudinal dynamics traffic flow theory traffic simulation autonomous driving This research investigates platoon formation and retention in various traffic conditions using five well-known car-following models, implemented as controllers on reduced-scale mobile robots (RSMRs). Our study moves beyond traditional simulations by directly applying these controllers in a controlled physical environment to observe and measure the dynamic interactions within a platoon of RSMRs. We adapted the Gazis-Herman-Rothery (GHR) model, Gipps model, intelligent driver model (IDM), proportional-integral-derivative (PID) model, and adaptive cruise control (ACC) model into controllers. Experiments were designed to assess controller performance across steady-flow, congested, and stop-and-go traffic conditions, with a preliminary scaling test to support comparison with full-scale vehicles. Overall, the IDM-inspired controller achieved the best safety-efficiency balance, with compact platooning and the smallest speed fluctuations, while ACC was typically second-best; PID and Gipps showed larger oscillations and gaps, and GHR led to collisions. The results also demonstrate noticeable differences between physical and simulation experiments, highlighting the necessity of studying platooning in a physical environment. The fundamental diagram analysis confirms that theoretical and experimental results are generally consistent, reinforcing the usefulness of RSMRs in studying traffic dynamics and providing reproducible baselines for controller evaluation. ⋆ This research was partially funded by the Australian Research Council (ARC) Discovery Project DP220100882. ∗ Corresponding author zhuopeng.xie@sydney.edu.au (Z. Xie); mohsen.ramezani@sydney.edu.au (M. Ramezani); david.levinson@sydney.edu.au (D. Levinson) ORCID (s): Zhuopeng Xie et al.: Preprint submitted to Elsevier Page 1 of 36 Platoon Formation and Retention Nomenclature ð ‘Ž acceleration of vehicles ð ‘Žmax maximum acceleration of vehicles ð ‘ most severe deceleration of vehicles ð ‘‘ð ‘–,𠑖−1 distance between the front of vehicle ð ‘– and the rear of vehicle ð ‘– − 1 ð ‘‘e expected distance between vehicles ð ‘‘K distance between the first and fourth RSMRs used to calculate the density ð ‘‘last final distance between two RSMRs ð ‘‘max maximum distance between two RSMRs ð ‘‘min minimum distance between two RSMRs ð ‘‘s expected static distance between vehicles ð ‘‘steady steady-state inter-vehicle distance * ð ‘‘max maximum distance between two RSMRs during the stable following stage * ð ‘‘min minimum distance between two RSMRs during the stable following stage * ð ‘‘std standard deviation of the distance between two RSMRs during the stable following stage ð ‘’ input error of the PID controller ð ‘– vehicle index ð ‘— summation index in the discrete PID term 𠑘 density derived from the IDM formula ð ¾d derivative gain of the PID controller ð ¾F density obtained through physical experiment ð ¾i integral gain of the PID controller ð ¾p proportional gain of the PID controller 𠑙𠑣 length of vehicles ð ¿âˆž string-stability amplification ratio (peak-to-peak) ð ‘ž flow derived from the IDM formula ð ‘„F flow obtained through physical experiment ð ‘ âˆ— IDM desired spacing for Δ𠑣 = 0 ð ‘¡ time index ð ‘¡e expected time headway between vehicles ð ‘¡min minimum time headway between two RSMRs ð ‘¡*min minimum time headway between two RSMRs during the stable following stage Zhuopeng Xie et al.: Preprint submitted to Elsevier Page 2 of 36 Platoon Formation and Retention ð ‘¡Q duration for the fourth RSMR to reach the position of the first RSMR used to calculate the flow TTC time-to-collision between two vehicles ð ‘£ speed of vehicles 𠑣𠑙 speed of the leader ð ‘£s safe speed of vehicles ð ‘£*mean mean speed of the following RSMRs during the stable following stage ð ‘£*std standard deviation of the speed of following RSMRs during the stable following stage ð ‘£stable target steady speed used for ð ¿âˆž computation 𠑉 expected speed of vehicles 𠑉F time mean speed obtained through physical experiment Δ𠑡 time step for state/command updates (PID controller) Δ𠑣 relative speed to the leader 𠛿𠑣𠑖 speed deviation of vehicle ð ‘– from ð ‘£stable used in ð ¿âˆž ð ‘ , 𠑘1 , 𠑘2 , ð ‘™, ð ‘š, ð ›¿ constants Zhuopeng Xie et al.: Preprint submitted to Elsevier Page 3 of 36 Platoon Formation and Retention

Keywords: transportation (search for similar items in EconPapers)
JEL-codes: R40 (search for similar items in EconPapers)
Date: 2026
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Published in Transportation Research Part C: Emerging Technologies 188 105671

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https://doi.org/10.1016/j.trc.2026.105671 Published version landing page, 2026 (text/html)

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Persistent link: https://EconPapers.repec.org/RePEc:nex:wpaper:paper-2026-13

DOI: 10.1016/j.trc.2026.105671

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