Stochastic Optimal Approach to the Steering of an Autonomous Vehicle through a Sequence of Roadways | IEEE Conference Publication | IEEE Xplore

Stochastic Optimal Approach to the Steering of an Autonomous Vehicle through a Sequence of Roadways


Abstract:

This paper discusses the implementation of a stochastic optimal controller for steering a vehicle to robustly follow an unpredictably winding road. The controller is base...Show More

Abstract:

This paper discusses the implementation of a stochastic optimal controller for steering a vehicle to robustly follow an unpredictably winding road. The controller is based on a bicycle model and the road is defined as a sequence of roadways. Each roadway has a fixed position, but its orientation is uncertain. To anticipate this uncertainty, we model the orientation with a Brownian stochastic process, which serves as a stochastic process model for the orientation observations. The stochastic controller based on such a model implicitly creates a robust road following controller. The control design is illustrated with numerical simulations and implemented for steering a car in a high-fidelity car simulator.
Date of Conference: 10-12 July 2019
Date Added to IEEE Xplore: 29 August 2019
ISBN Information:

ISSN Information:

Conference Location: Philadelphia, PA, USA

I. Introduction

With an increasing interest in the use and deployment of self-driving cars, there is a pressing need to analyze and develop robust steering strategies for these automated vehicles. These strategies need to be able to steer an autonomous car in such a way that it smoothly guides itself and stays on the road even when the curves are unpredictable. To achieve that, we propose a stochastic optimal steering controller based on a bicycle kinematics model. This nonholonomic model has been frequently used in the literature as an approximation of car kinematics [1]–[3].

Contact IEEE to Subscribe

References

References is not available for this document.