Autonomous and Connected Vehicles

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 2338

Special Issue Editor


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Guest Editor
Faculty of Computer Science and Telecommunications, Maritime University of Szczecin, 70500 Szczecin, Poland
Interests: artificial intelligence in navigation; computer science in navigation; automation and control systems in navigation; control of ship motion; autonomous ships

Special Issue Information

Dear Colleagues,

The aim of this Special Issue is to bring together researchers and practitioners involved in the autonomous vehicles field. Autonomy in vehicles is broadly understood as connected vehicles, vehicles with navigational decision support system, vehicles with a limited crew, remotely controlled vehicles, and fully autonomous vehicles. In this Special Issue, articles describing innovative discoveries, methods, systems, and solutions that impact the advancement of vehicle autonomy, especially in the field of navigation, are welcomed.

As part of this Special Issue, we plan to publish selected papers presented at the 13th International Scientific and Technical Conference, EXPLO-SHIP 2024.

The topics of particular interest include, but are not limited to:

  • Autonomous vehicles;
  • Connected vehicles;
  • Autonomous navigation;
  • The application of artificial intelligence methods in autonomous vehicles;
  • Autonomous vehicle control systems;
  • Expert systems in autonomous vehicles;
  • Navigational decision support system;
  • Computational mathematics in navigation;
  • Cybersecurity in autonomous vehicles.

Dr. Piotr Borkowski
Guest Editor

Manuscript Submission Information

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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. Electronics is an international peer-reviewed open access semimonthly 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
  • connected vehicles
  • autonomous navigation
  • artificial intelligence
  • control systems
  • expert systems
  • decision support system
  • computational mathematics
  • cybersecurity

Published Papers (3 papers)

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Research

28 pages, 1782 KiB  
Article
Searching for a Cheap Robust Steering Controller
by Trevor Vidano and Francis Assadian
Electronics 2024, 13(10), 1908; https://doi.org/10.3390/electronics13101908 - 13 May 2024
Viewed by 458
Abstract
The study of lateral steering control for Automated Driving Systems identifies new control solutions more often than new control problems. This is likely due to the maturity of the field. To prevent repeating efforts toward solving already-solved problems, what is needed is a [...] Read more.
The study of lateral steering control for Automated Driving Systems identifies new control solutions more often than new control problems. This is likely due to the maturity of the field. To prevent repeating efforts toward solving already-solved problems, what is needed is a cohesive way of evaluating all developed controllers under a wide variety of environmental conditions. This work serves as a step in this direction. Four controllers are tested on five maneuvers representing highways and collision avoidance trajectories. Each controller and maneuver combination is repeated on five sets of environmental conditions or Operational Design Domains (ODDs). The design of these ODDs ensures the translation of these experimental results to real-world applications. The commercial software, CarSim 2020, is extended with Simulink models of the environment, sensor dynamics, and state estimation performances to perform highly repeatable and realistic evaluations of each controller. The results of this work demonstrate that most of the combinations of maneuvers and ODDs have existing cheap controllers that achieve satisfactorily safe performance. Therefore, this field’s research efforts should be directed toward finding new control problems in lateral path tracking rather than proposing new controllers for ODDs that are already solved. Full article
(This article belongs to the Special Issue Autonomous and Connected Vehicles)
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23 pages, 27139 KiB  
Article
Enhancing the Safety of Autonomous Vehicles in Adverse Weather by Deep Learning-Based Object Detection
by Biwei Zhang, Murat Simsek, Michel Kulhandjian and Burak Kantarci
Electronics 2024, 13(9), 1765; https://doi.org/10.3390/electronics13091765 - 2 May 2024
Viewed by 629
Abstract
Recognizing and categorizing items in weather-adverse environments poses significant challenges for autonomous vehicles. To improve the robustness of object-detection systems, this paper introduces an innovative approach for detecting objects at different levels by leveraging sensors and deep learning-based solutions within a traffic circle. [...] Read more.
Recognizing and categorizing items in weather-adverse environments poses significant challenges for autonomous vehicles. To improve the robustness of object-detection systems, this paper introduces an innovative approach for detecting objects at different levels by leveraging sensors and deep learning-based solutions within a traffic circle. The suggested approach improves the effectiveness of single-stage object detectors, aiming to advance the performance in perceiving autonomous racing environments and minimizing instances of false detection and low recognition rates. The improved framework is based on the one-stage object-detection model, incorporating multiple lightweight backbones. Additionally, attention mechanisms are integrated to refine the object-detection process further. Our proposed model demonstrates superior performance compared to the state-of-the-art method on the DAWN dataset, achieving a mean average precision (mAP) of 99.1%, surpassing the previous result of 84.7%. Full article
(This article belongs to the Special Issue Autonomous and Connected Vehicles)
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18 pages, 1111 KiB  
Article
Control Performance Requirements for Automated Driving Systems
by Trevor Vidano and Francis Assadian
Electronics 2024, 13(5), 902; https://doi.org/10.3390/electronics13050902 - 27 Feb 2024
Cited by 1 | Viewed by 668
Abstract
This research investigates the development of risk-based performance requirements for the control of an automated driving system (ADS). The proposed method begins by determining the target level of safety for the virtual driver of an ADS. The underlying assumptions are informed by existing [...] Read more.
This research investigates the development of risk-based performance requirements for the control of an automated driving system (ADS). The proposed method begins by determining the target level of safety for the virtual driver of an ADS. The underlying assumptions are informed by existing data. Next, geometric models of the road and vehicle are used to derive deterministic performance levels of the virtual driver. To integrate the risk and performance requirements seamlessly, we propose new definitions for errors associated with the planner, pose, and control modules. These definitions facilitate the derivation of stochastic performance requirements for each module, thus ensuring an overall target level of safety. Notably, these definitions enable real-time controller performance monitoring, thus potentially enabling fault detection linked to the system’s overall safety target. At a high level, this approach argues that the requirements for the virtual driver’s modules should be designed simultaneously. To illustrate this approach, this technique is applied to a research project available in the literature that developed an automated steering system for an articulated bus. This example shows that the method generates achievable performance requirements that are verifiable through experimental testing and highlights the importance in validating the underlying assumptions for effective risk management. Full article
(This article belongs to the Special Issue Autonomous and Connected Vehicles)
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