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Sensors and Sensor Fusion in Autonomous Vehicles
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Sensors and Sensor Fusion in Autonomous Vehicles

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: 20 May 2024 | Viewed by 4877

Special Issue Editors

Prof. Dr. Jianhua Ma

E-Mail Website
Guest Editor
Faculty of Computer and Information Science, Hosei University, 2 Chome-17-1 Fujimi, Chiyoda, Tokyo 102-8160, Japan
Interests: ubiquitous/pervasive computing and smart environment; u-Things, u-Intelligence and u-Science; cyber space, science and sociology; service and social computing; mobile multimedia and wireless network; IoT/iThings and Wisdom Web of Things (W2T); location and context-aware application; autonomic, trusted and ubisafe computing; hyperspace/hyperworld and cyber-I (digital colone)
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Qun Jin

E-Mail Website
Guest Editor
Department of Human Informatics and Cognitive Sciences, Faculty of Human Sciences, Waseda University, Tokyo 169-8050, Japan
Interests: behavior and cognitive informatics; big data; intelligence computing; blockchain; cyber security
Special Issues, Collections and Topics in MDPI journals
Dr. Gábor Kiss

E-Mail Website
Guest Editor
Institute of Mechanical Engineering and Security Science, Obuda University, H-1034 Budapest, Hungary
Interests: information security of self-driving vehicles
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In order to place autonomous cars slowly into our everyday lives from the world of science fiction, there was a need for new, or rather more accurate sensors and also a major development of artificial intelligence. This Special Issue of Sensors seeks the submission of review and original research articles related to sensors and sensor fusion in autonomous vehicles. Papers can focus on safety mistakes, security aggression, and achievable countermoves for self-driving vehicles, as well as Blockchain-based security attacks, flexible patterns for self-driving cars, and the STPA method and six-step model to integrate autonomous vehicle safety and security. Other research can give an overview of autonomous vehicle safety or study the cybersecurity of self-driving and remotely controlled transportation. The Special Issue is open to contributions dealing with many aspects of autonomous vehicle sensors and their fusion, such as multisensor fusion, big data processing for autonomous vehicles, sensor-related research, algorithms/technical development, and artificial intelligence methods for autonomous vehicle navigation.

Prof. Dr. Jianhua Ma
Prof. Dr. Qun Jin
Dr. Gábor Kiss
Guest Editors

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. Sensors 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 2600 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

  • self-driving
  • autonomous vehicle
  • safety
  • security
  • big data
  • sensor
  • fusion
  • navigation

Published Papers (2 papers)

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Research

18 pages, 28847 KiB  
Article
Hierarchical Multi-Objective Optimization for Dedicated Bus Punctuality and Supply–Demand Balance Control
by Chunlin Shang, Fenghua Zhu, Yancai Xu, Xiaoming Liu and Tianhua Jiang
Sensors 2023, 23(9), 4552; https://doi.org/10.3390/s23094552 - 07 May 2023
Cited by 1 | Viewed by 1424
Abstract
Public transportation is a crucial component of urban transportation systems, and improving passenger sharing rates can help alleviate traffic congestion. To enhance the punctuality and supply–demand balance of dedicated buses, we propose a hierarchical multi-objective optimization model to optimize bus guidance speeds and [...] Read more.
Public transportation is a crucial component of urban transportation systems, and improving passenger sharing rates can help alleviate traffic congestion. To enhance the punctuality and supply–demand balance of dedicated buses, we propose a hierarchical multi-objective optimization model to optimize bus guidance speeds and bus operation schedules. Firstly, we present an intelligent decision-making method for bus driving speed based on the mathematical description of bus operation states and the application of the Lagrange multiplier method, which improves the overall punctuality rate of the bus line. Secondly, we propose an optimization method for bus operation schedules that respond to passenger needs by optimizing departure time intervals and station schedules for supply–demand balance. The experiments were conducted in Future Science City, Beijing, China. The results show that the bus line’s punctuality rate has increased to 90.53%, while the retention rate for platform passengers and the intersection stop rate have decreased by 36.22% and 60.93%, respectively. These findings verify the effectiveness and practicality of the proposed hierarchical multi-objective optimization model. Full article
(This article belongs to the Special Issue Sensors and Sensor Fusion in Autonomous Vehicles)
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28 pages, 1957 KiB  
Article
Information Fusion in Autonomous Vehicle Using Artificial Neural Group Key Synchronization
by Mohammad Zubair Khan, Arindam Sarkar, Hamza Ghandorh, Maha Driss and Wadii Boulila
Sensors 2022, 22(4), 1652; https://doi.org/10.3390/s22041652 - 20 Feb 2022
Cited by 5 | Viewed by 2434
Abstract
Information fusion in automated vehicle for various datatypes emanating from many resources is the foundation for making choices in intelligent transportation autonomous cars. To facilitate data sharing, a variety of communication methods have been integrated to build a diverse V2X infrastructure. However, information [...] Read more.
Information fusion in automated vehicle for various datatypes emanating from many resources is the foundation for making choices in intelligent transportation autonomous cars. To facilitate data sharing, a variety of communication methods have been integrated to build a diverse V2X infrastructure. However, information fusion security frameworks are currently intended for specific application instances, that are insufficient to fulfill the overall requirements of Mutual Intelligent Transportation Systems (MITS). In this work, a data fusion security infrastructure has been developed with varying degrees of trust. Furthermore, in the V2X heterogeneous networks, this paper offers an efficient and effective information fusion security mechanism for multiple sources and multiple type data sharing. An area-based PKI architecture with speed provided by a Graphic Processing Unit (GPU) is given in especially for artificial neural synchronization-based quick group key exchange. A parametric test is performed to ensure that the proposed data fusion trust solution meets the stringent delay requirements of V2X systems. The efficiency of the suggested method is tested, and the results show that it surpasses similar strategies already in use. Full article
(This article belongs to the Special Issue Sensors and Sensor Fusion in Autonomous Vehicles)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Lidar's possibilities in traffic collision situations

Authors: Takáč Ondrej, Végh Ladislav, Czakóová Krisztina 

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