Models and Predictive Control for Nonplanar Vehicle Navigation

TL;DR

This paper introduces a generalized vehicle model for nonplanar roads using a parametric surface, enabling improved path planning and control on complex terrains with enhanced safety and performance.

Contribution

The paper presents a novel parametric surface-based vehicle model that generalizes existing planar models, and applies it to predictive control for complex nonplanar road navigation.

Findings

Improved speed and lane following on complex roads.

Enhanced control on off-camber turns.

Better mitigation of control loss on complex surfaces.

Abstract

We present a simplified model of a vehicle driving on a nonplanar road. A parametric surface is used to describe the nonplanar road which can describe any combination of curvature, bank and slope. We show that the proposed modeling approach generalizes planar vehicle models that reference a centerline, such as the Frenet model. We use the proposed approach for vehicle path planning and following using model predictive control. We also model and control vehicle contact with the road surface. We demonstrate that the proposed controller improves speed and lane following on complex roads compared to planar vehicle controllers, and mitigates loss of control on complex road surfaces including off-camber turns.