Multimodel Approach to Personalized Autonomous Adaptive Cruise Control

Adaptive Cruise Control with Safety Guarantees for Autonomous Vehicles

This paper addresses the problem of following a vehicle with varying acceleration in a comfortable and safe manner. Our architecture consists of a nominal controller (here: model predictive control) and a safety controller. Although model predictive control attempts to keep a safe distance, it cannot formally guarantee it, due to the assumptions on the behavior of the leading vehicle. We addres...

Driver Support in Intelligent Autonomous Cruise Control

A supervised Actor-Critic approach for adaptive cruise control

A novel supervised Actor–Critic (SAC) approach for adaptive cruise control (ACC) problem is proposed in this paper. The key elements required by the SAC algorithm namely Actor and Critic, are approximated by feed-forward neural networks respectively. The output of Actor and the state are input to Critic to approximate the performance index function. A Lyapunov stability analysis approach has be...

Resilient Adaptive Control with Application to Vehicle Cruise Control

Abstract. This work address the general problem of resilient control of unknown stochastic linear time-invariant (LTI) systems in the presence of sensor attacks. Motivated by a vehicle cruise control application, this work considers a first order system with multiple measurements, of which a bounded subset may be corrupted. A frequency-domain-designed resilient adaptive controller is introduced...

A Model Predictive Control Approach to Design a Parameterized Adaptive Cruise Control

The combination of different desirable characteristics and situation-dependent behavior cause the design of adaptive cruise control (ACC) systems to be time consuming and tedious. This chapter presents a systematic approach for the design and tuning of an ACC, based on model predictive control (MPC). A unique feature of the synthesized ACC is its parameterization in terms of the key characteris...