Title: An empirical vehicle speed model for tuning throttle controller parameters

Authors: Christopher Goodin; Marc N. Moore; Daniel W. Carruth; Christopher R. Hudson; Lucas D. Cagle; Paramsothy Jayakumar

Addresses: Center for Advanced Vehicular Systems, Mississippi State University, Starkville, MS, USA ' Center for Advanced Vehicular Systems, Mississippi State University, Starkville, MS, USA ' Center for Advanced Vehicular Systems, Mississippi State University, Starkville, MS, USA ' Center for Advanced Vehicular Systems, Mississippi State University, Starkville, MS, USA ' Center for Advanced Vehicular Systems, Mississippi State University, Starkville, MS, USA ' US Army DEVCOM, Ground Vehicle Systems Center, Warren, MI, USA

Abstract: Modelling vehicle longitudinal dynamics is critical for developing speed-control strategies. In this work an empirical model of vehicle longitudinal dynamics is proposed. The purpose of the empirical model is to facilitate the tuning of proportional-integral-differential (PID) parameters for a real-world vehicle. With a short series of measurements, a predictive model of the vehicle speed was developed by fitting the model to the measured data. The empirical model presented in this work has the advantages that it is simple - it does not require any detailed measurements of the vehicle properties but is rather easily fit to real measurements. The model is also flexible, being applicable to a range of different vehicles. In this work, the development of the model is outlined and an application of the model is shown for two different vehicles, the Polaris MRZR4 and the Clearpath Warthog, which have different drive-train and suspension characteristics. The applicability of the empirical model is demonstrated by tuning and testing a real PID controller for the MRZR4.

Keywords: dynamic systems and control; autonomous vehicles; vehicle dynamics; autonomous driving.

DOI: 10.1504/IJVP.2024.137690

International Journal of Vehicle Performance, 2024 Vol.10 No.2, pp.196 - 214

Received: 28 Nov 2022
Accepted: 12 Mar 2023
Published online: 02 Apr 2024 *

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