Mixed H2−H∞ control for automated highway driving. (February 2019)

• Record Type: Journal Article
• Authors: Schmied, Roman; Colaneri, Patrizio
• Is Part Of: Mechatronics. Volume 57(2019)
• Page Start: 63
• Page End: 72
• Publication Date: 2019-02
• Subjects: Automated driving -- Mixed H2−H∞ control -- Minimum entropy control; Computer integrated manufacturing systems -- Periodicals; Flexible manufacturing systems -- Periodicals; Mechatronics -- Periodicals; Productique -- Périodiques; Fabrication, Systèmes flexibles de -- Périodiques; Mécatronique -- Périodiques; Computer integrated manufacturing systems; Flexible manufacturing systems; Mechatronics; Periodicals; 629.89
• DOI: 10.1016/j.mechatronics.2018.11.001
• Languages: English
• ISSNs: 0957-4158

Abstract

Abstract: Automated highway driving combining longitudinal vehicle control and lane decision represents an important part on the way to autonomous driving. The general goal in this work is to investigate an ego-vehicle control approach for automated highway driving. For this, a multi-lane and multi-vehicle environment is considered where the vehicles around the controlled ego-vehicle represent disturbance inputs. The control law should be designed to increase local traffic flow stability around the ego-vehicle. The novelty in this work is represented by considering string stability in a multi-lane and multi-vehicle context, i.e. effects of ego-vehicle lane changes on surrounding traffic. The lane decision process results in a switching law based on the concept of minimum entropy control which represents a mixed H 2 − H ∞ control design method. Since it is well known that string stability is implied by bounding the H ∞ norm of a vehicle to vehicle transfer function it seems reasonable to apply this control strategy for automated highway driving. Thereby, each lane is assigned with an entropy value based on the actual traffic situation and the target lane is decided to balance local unequal distributions of traffic density. Lane changes are allowed only if local string stability can be assured. Longitudinal ego-vehicle control is realized with a compensator blending strategy where a dynamic compensator is derived targeting H 2 and H ∞ performance measure. The overall automated highway driving approach is evaluated by means of two test cases, namely a merging scenario and a highway driving scenario in a multi-lane and multi-vehicle traffic environment implemented in the high fidelity vehicle simulation tool IPG CarMaker .