Optimal Control of Autonomous Vehicles

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Vehicle Engineering".

Deadline for manuscript submissions: 20 May 2024 | Viewed by 803

Special Issue Editor

*
E-Mail Website
Guest Editor
Mechanical Engineering Department, Oakland University, Rochester, MI 48309, USA
Interests: electrified and intelligent vehicle modeling, simulation, controls development and testing, and optimization
* Retired in August 2022 from Mechanical Engineering Department, Wayne State University, Detroit, MI 48202, USA

Special Issue Information

Dear Colleagues,

The last few years witnessed tremendous progress in all areas of autonomous vehicle technology. However, even with unprecedented growth in computing power and algorithm, improvements are still sought to advance the field of control with emphasis in optimizing various aspects of vehicle performance, including drivability, safety critical function, energy efficiency, and environmental and societal impacts. This Special Issue aims to bring together researchers in industry and academics to present recent technological advancements or to provide comprehensive reviews or forward-looking visions and insights in the field of optimal control. Proposed topics include, but are not limited to

  • Autonomous vehicle optimal control;
  • Vehicle dynamics modeling and control;
  • Chassis control;
  • Vehicle safety control;
  • Autonomous vehicle path planning;
  • Energy-efficient connected and automated vehicles.

Dr. Jerry C. Ku
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • autonomous vehicles
  • optimal control
  • motion control
  • chassis control systems
  • vehicle dynamics control
  • safety control
  • path planning

Published Papers (1 paper)

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Research

17 pages, 11867 KiB  
Article
Design of Active Suspension Controller for Ride Comfort Enhancement and Motion Sickness Mitigation
by Yonghwan Jeong and Seongjin Yim
Machines 2024, 12(4), 254; https://doi.org/10.3390/machines12040254 - 11 Apr 2024
Cited by 1 | Viewed by 601
Abstract
This paper presents a method for designing an active suspension controller for ride comfort enhancement and motion sickness mitigation. For this, it is necessary to design an active suspension controller, which aims to reduce the vertical acceleration and pitch rate of a sprung [...] Read more.
This paper presents a method for designing an active suspension controller for ride comfort enhancement and motion sickness mitigation. For this, it is necessary to design an active suspension controller, which aims to reduce the vertical acceleration and pitch rate of a sprung mass in a vehicle. A half-car vehicle model was selected. For the controller design, a static output feedback (SOF) control was selected instead of a full-state feedback control because it is hard to measure all state variables in real vehicles. With the available signals, three types of SOF controller were proposed. To determine the gains of the SOF controllers, a linear quadratic optimal control methodology and a simulation-based optimization method were adopted. To validate the proposed method, a simulation was carried out using vehicle simulation software. The simulation results show that the proposed method is quite effective for ride comfort enhancement and motion sickness mitigation. Full article
(This article belongs to the Special Issue Optimal Control of Autonomous Vehicles)
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