Real-time vehicle measurements using digital image correlation

Abstract

The tyre-road interface is one of the most important research topics in the field of vehicle dynamics. This is largely due to all the vehicle excitation forces (besides aerodynamic forces) being generated at this interface. There are many parameters which govern the generation of tyre forces, of which the side-slip angle is of utmost importance. Vehicle side-slip angle can be used as a measure of vehicle stability. Stability control schemes require side-slip angle and typically estimate this parameter instead of using a direct measurement. The relationship between tyre lateral force and tyre side-slip allows the lateral force generated by the tyre to be determined from the tyre side-slip angle. Therefore, real-time measurement of side-slip angle is important in tyre research and vehicle stability. Solutions exist to measure the side-slip angle, however, do not perform well at low speeds or over rough terrain and are prohibitively expensive. In terramechanics, tyre soil deformation in the form of rut depth is a widely researched topic as it can be used as a measure of the vehicle’s ability to traverse the terrain, estimate soil characteristics and for vehicle environmental impact studies. Currently, these measurements are labour intensive and are typically conducted by hand. Other solutions exist however they are developed for road use and are prohibitively expensive. The research field would, therefore, benefit largely from online rut depth measurements. Digital Image Correlation is the mathematical process of tracking changes in digital images. The development of robust algorithms and ease of implementation has allowed many fields to be adapt this non-contact based, optical technique for application-specific measurements. Previous studies (Botha, 2015) have proved DIC to be a viable candidate for measuring the side-slip angle and rut depth that overcome current measuring hurdles. However, the analysis was conducted in post-processing from pre-recorded footage due to the large computational expense of the image processing. This opens the opportunity to adapt and optimise these techniques to achieve real-time processing speeds required for these camera-based sensors. This study builds on Botha (2015) with a real-time implementation which allows for online measurements to be made using inexpensive, off-the-shelf cameras with dedicated software. This will eventually provide systems such as ABS, stability control schemes and semi-active suspension with real time vehicle side-slip angle and rut depth with a cost-effective camera-based sensor. The aim of the present study is to develop and test two systems that can measure the side-slip angle and rut depth in real-time. The side-slip angle is measured using a single camera pointing down on the terrain and digital image correlation. It is shown to measure accurately and in real-time. The sensor is tested on a flat surface using a rig that allows for validation. The rut depth is measured using multiple cameras pointing at the terrain and digital image correlation to create a 3D map of the terrain. Three methods for determining the rut depth from the 3D map is investigated, with varying degree of accuracy and processing speed.