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GPS Based Real-Time Tire-Road Friction Coefficient Identification

TLDR
In this paper, the authors developed a real-time tire-road friction coefficient estimation system for snowplows that can reliably estimate different road surface friction levels and quickly detect abrupt changes in friction coefficient.
Abstract
This project concentrates on the development of real- time tire-road friction coefficient estimation systems for snowplows that can reliably estimate different road surface friction levels and quickly detect abrupt changes in friction coefficient. Two types of systems are developed - a vehicle-based system and a wheel-based system. The vehicle-based friction measurement system utilizes vehicle motion measurements from differential global positioning system (GPS) and other on-board vehicle sensors. The wheel-based friction measurement system utilizes a redundant wheel that is mounted at a small angle to the longitudinal axis of the vehicle. Complete technical details on the vehicle-based friction measurement system are presented in this report. Compared to previously published results in literature, the advantage of the vehicle-based system developed here is that it is applicable during both vehicle acceleration and braking and works reliably for a wide range of slip ratios, including high slip conditions. The system can be used on front/rear-wheel drive as well as all-wheel drive vehicles. Extensive results are presented from experimental results conducted on various surfaces with a winter maintenance vehicle called the Safeplow. The experimental results show that the system performs reliably and quickly in estimating friction coefficient on different road surfaces during various vehicle maneuvers.

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Citations
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Journal ArticleDOI

A technical survey on tire-road friction estimation

TL;DR: This literature survey introduces different approaches, which have been widely used to estimate the friction or other related parameters, and covers the recent literature that contains these methodologies.
Proceedings ArticleDOI

An experimental study with alternate measurement systems for estimation of tire-road friction coefficient

TL;DR: Compared to the vehicle-based system, the wheel and the tire based systems have significantly better ability to estimate friction reliably in the absence of significant cornering or acceleration/deceleration in the vehicle.

MnROAD Lessons Learned

TL;DR: The Minnesota Road Research Project (MnROAD) as discussed by the authors was the first major test track since the AASHO Road Test of the 1950s and 1960s and has learned a number of lessons on behalf of the greater pavement community.
Dissertation

The Application of Intelligent Tires and Model Base Estimation Algorithms in Tire-road Contact Characterization

TL;DR: Five model based tire-road friction estimation algorithms, which are widely used for tire road friction estimation, were introduced in this study and the performance of each algorithm was evaluated in high slip and low slip maneuvers.
Journal ArticleDOI

Pavement slipperiness detection using wheel speed and acceleration sensor data

Jinhwan Jang
TL;DR: In this article, the wheel slip-based and wheel acceleration-based approaches are suggested for detecting road slipperiness using sensor data from a digital tachograph (DTG), which is mandatory in commercial vehicles.
References
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Book

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TL;DR: In this article, the authors attempt to find a middle ground by balancing engineering principles and equations of use to every automotive engineer with practical explanations of the mechanics involved, so that those without a formal engineering degree can still comprehend and use most of the principles discussed.
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TL;DR: This chapter discusses Signal Estimation, which automates the very labor-intensive and therefore time-heavy and expensive process of manually cataloging and changing the values of coefficients in a model to facilitate change detection.
Journal ArticleDOI

Slip-based tire-road friction estimation

TL;DR: An approach to estimate the tire-road friction using only the wheel slip, that is, the relative difference in wheel velocities, is presented and an adaptive estimator is presented for a model linear in parameters, designed to work for periods of poor excitation, errors in variables, simultaneous slow and fast parameter drifts and abrupt changes.
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