Estimation of road inclination and bank angle in automotive vehicles

Abstract

Abstract-We extend an observer design for estimation of the vehicle sideslip angle on horizontal surfaces to include estimation of the road inclination angle and the road bank angle. The design makes use of a nonlinear road-tire friction model, and the nonlinearity of the road-tire friction forces are taken into account in the theoretical analysis of the design. Using an absolute-stability argument we show that, under a set of technical assumptions, the origin of the observer error dynamics is globally exponentially stable. Taking unknown road-surface conditions into account, we discuss simultaneous estimation of the road bank angle and a road-tire friction parameter, which is complicated by the dependence of the friction-parameter estimation on lateral excitation of the vehicle. To improve performance on low-friction surfaces, we modulate the observer gains based on a set of practical conditions. Using experimental data from a passenger car, we investigate the performance of the approach.

Vehicle state estimation for anti-lock control with nonlinear observer

“…Again, an ISS result similar to that for u t 0 obs ( ) ≠ holds also for this input. In order to reduce the impact of road grade and bank angles on the accuracy of the estimated vehicle states, algorithms for the road grade and bank angles adaptations, such as those in Zhao et al (2009) andSuissa (2009), can be added into the existing estimator structure in the future.…”

Automatic estimation of road inclinations by fusing GPS readings with OSM and ASTER GDEM2 data

“…Many scientific studies have been conducted to validate the relevance and accuracy of ASTER and SRTM data, sometimes from very precise GPS readings [8], [9]. However, due to their horizontal resolution, it is not possible to achieve a high level of accuracy in road inclination estimation by using DEMs only, while the slope is a very important parameter to guarantee the safety of exceptional road convoys [10]. This is why the proposed method is based on the fusion of GPS, OSM and DEM data that relies on an unscented Kalman filter (UKF).…”

A General Framework for 3-D Parameters Estimation of Roads Using GPS, OSM and DEM Data

“…Considering the horizontal resolution of ASTER DEM data, an elevation information is available about every 30 m. This low spatial sampling can be a major drawback of the ASTER data. In a process of estimating the slope of roads, it is hard to achieve a high level of accuracy using ASTER DEM only [ 11 ]. The possibility to use DEM only solutions is indeed related to the spatial dimensions of the tiles that are for now not small enough.…”