Toward Automated Vehicle Control Beyond the Stability Limits: Drifting Along a General Path

Jonathan Y Goh,J Christian Gerdes,Tushar Goel

doi:10.1115/1.4045320

Abstract

Abstract Professional drivers in drifting competitions demonstrate accurate control over a car's position and sideslip while operating in an open-loop unstable region of state-space. Could similar approaches help autonomous cars contend with excursions past the stable handling limits, thereby improving overall safety outcomes? As a first step toward answering that question, this paper presents a novel controller framework for automated drifting along a path. The controller is derived for the general case, without reference to a nearby equilibrium point. This leads to the physically insightful result that one can use the rotation rate of the vehicle's velocity vector to track the path, while simultaneously using the yaw acceleration to stabilize sideslip. Nonlinear model inversion, in concert with low-level wheelspeed control, is then used to achieve these required state derivatives over a broad range of conditions. Experiments on MARTY, a modified 1981 DMC DeLorean, demonstrate excellent tracking of a path with varying curvature, speed, and sideslip. Comparisons to a test run without wheelspeed control highlight the importance of accounting for the rear saturated-tire wheelspeed dynamics.

Highlights

Exceeding a vehicle’s handling limits can lead to strong input coupling and instability—conditions that overwhelm traditional control architectures with independent lateral/longitudinal control and that explicitly assume open-loop stable sideslip dynamics
It is interesting to note that velocity stays quite close to the quasiequilibrium values
This suggests that the closed-loop velocity dynamics are stable, which is expected since the states never leave the volume (Fig. 7) wherein we hypothesize this to be true

Summary

Introduction

Exceeding a vehicle’s handling limits can lead to strong input coupling and instability—conditions that overwhelm traditional control architectures with independent lateral/longitudinal control and that explicitly assume open-loop stable sideslip dynamics. Drivers in “drifting” competitions routinely operate in this region of state-space, while achieving precise control over both sideslip and the vehicle’s path. Developing controllers for automated drifting could provide great insight into the general problem of fully utilizing the entire state-space and ensuring that the widest possible range of maneuvers is available to an autonomous vehicle, should the need arise. This could be relevant when navigating inclement weather or difficult terrain: work by Acosta et al [1], for example, suggests that driver assistance systems that can access these regimes greatly outperform traditional stability control on gravel surfaces. Due to restrictive assumptions in vehicle modeling or controller formulation, these approaches cannot be extended to more complex trajectories

Methods

Results

Conclusion