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Sensors and Modern Technologies for Road, Robotic, and Intelligent Vehicle
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Sensors and Modern Technologies for Road, Robotic, and Intelligent Vehicle

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

Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 21210

Special Issue Editors

Prof. Dr. Adam Idzkowski

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Guest Editor
Department of Electrical Engineering, Bialystok University of Technology, 15-351 Bialystok, Poland
Interests: robotic sensors; applications of sensors in transportation; wireless sensor networks; signal processing; renewable energy; energy harvesting; metrology; measurement uncertainty
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Vytautas Bucinskas

E-Mail Website
Guest Editor
Department of Mechatronics, Robotics, and Digital Manufacturing, Vilnius Gediminas Technical University, LT-10105 Vilnius, Lithuania
Interests: robotic process automation; artificial intelligence in robotics; virtual and augmented reality in industry; smart sensors and systems; flexible sensors
Special Issues, Collections and Topics in MDPI journals
Dr. Damian Grzechca

E-Mail Website
Guest Editor
Department of Electronics, Electrical Engineering and Microelectronics, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, 16 Akademicka Street, 44-100 Gliwice, Poland
Interests: predictive maintenance of electronic sensors/systems; failure analysis; ADAS methodology; signal processing and data analysis; positioning and localization systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Reza Malekian

E-Mail Website
Guest Editor
Department of Computer Science and Media Technology, Malmö University, SE-211 19 Malmö, Sweden
Interests: Internet of things; connectivity; advanced sensor networks; intelligent transportation systems; vehicular networks
Special Issues, Collections and Topics in MDPI journals
Dr. Andrius Dzedzickis

E-Mail Website
Guest Editor
Department of Mechatronics, Robotics, and Digital Manufacturing, Vilnius Gediminas Technical University, LT-10105 Vilnius, Lithuania
Interests: robotic process automation; artificial intelligence in robotics; virtual and augmented reality in industry; digital twins of industrial systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The aim of this Special Issue is to contribute to the state-of-the-art and to introduce current developments concerning modern vehicles, i.e., sensors and applications in measuring and automation control systems, power management systems, and artificial intelligence-based systems. We encourage potential authors to submit contributions of original research, novel developments, and substantial experimental works concerning road, robotic, and intelligent vehicles.

In recent years, different sensing technologies have been implemented in the automotive industry. Vehicular electric power systems and energy management are still improving. Electric motors have been applied to electric and hybrid-electric vehicles (HEV). Energy recovery systems that can harvest energy from the motion of a vehicle are still being developed. Additionally, robotic and intelligent vehicles are used in many sensing applications. There is a need to use new algorithms as well as LiDAR, radar, video, thermal imaging devices, and applications. Data are often derived from disparate sources. Therefore, sensor fusion and intelligence deployment are needed. Driving systems have become highly automated. Artificial intelligence algorithms are implemented in autonomous vehicles. Using telemetry for the diagnostic and maintenance of vehicles is also important. Advanced driver-assistance systems (ADAS) and autonomous vehicles are getting more and more popular.

The following are some examples of topics of interest for this issue:

  • Robotic and automotive sensors
  • Drone-based sensor platforms
  • Sensors and applications in measuring and automation control systems
  • Sensor and information fusion
  • Electric and hybrid vehicles
  • Autonomous/intelligent robotic vehicles
  • Energy harvesting for automotive applications
  • Solar power management systems
  • Robotics and machine learning (ML)
  • Artificial intelligence and autonomous vehicles
  • Predictive maintenance of vehicles in smart cities
  • Advanced driver-assistance systems (ADAS) methodology, algorithms, and devices (application of LiDAR, Radar, Video, Thermovision)
  • Industrial applications

Dr. Adam Idzkowski
Prof. Dr. Vytautas Bucinskas
Dr. Damian Grzechca
Prof. Dr. Reza Malekian
Dr. Andrius Dzedzickis
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

  • Vehicle
  • Measurement systems
  • Control systems
  • Power systems
  • Energy harvesting
  • Electric vehicles
  • Robotic vehicles
  • Road vehicles
  • Unmanned vehicles
  • Autonomous vehicles
  • Multisensor data fusion
  • Artificial intelligence
  • Machine learning
  • ADAS

Published Papers (6 papers)

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Research

18 pages, 29621 KiB  
Article
Multi-Objective Real-Time Tuning of SVC Used in Electrified Traction Systems
by Mohammad Hossein Bigharaz, Mehdi Amiri Dehcheshmeh, Hadi Givi and Štěpán Hubálovský
Sensors 2022, 22(4), 1584; https://doi.org/10.3390/s22041584 - 17 Feb 2022
Cited by 4 | Viewed by 1832
Abstract
Electric train system is a very large load for the power network. This load consumes a large amount of reactive power. In addition, it causes a massive unbalance to the network, which results in many problems such as voltage drops, high transmission losses, [...] Read more.
Electric train system is a very large load for the power network. This load consumes a large amount of reactive power. In addition, it causes a massive unbalance to the network, which results in many problems such as voltage drops, high transmission losses, reduction in the transformer output ability, negative sequence current, mal-operation of protective relays, etc. In this paper, a novel real-time optimization approach is presented to adjust the static VAR compensator (SVC) for the traction system to realize two objectives; current unbalance reduction and reactive power compensation. A multi-objective optimization technique entitled non-dominated sorting genetic algorithm (NSGA-II) is used to fulfill the regarded objectives simultaneously. A comprehensive simulator has been designed for electric train network modeling that is able to adjust the parameters of SVC in an optimum manner at any time and under any circumstances. The results illustrate that the provided method can efficiently reduce the unbalancing in current as well as supply the demanded reactive power with acceptable precision. Full article
(This article belongs to the Special Issue Sensors and Modern Technologies for Road, Robotic, and Intelligent Vehicle)
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19 pages, 3594 KiB  
Article
FMCW Radar Estimation Algorithm with High Resolution and Low Complexity Based on Reduced Search Area
by Bong-Seok Kim, Youngseok Jin, Jonghun Lee and Sangdong Kim
Sensors 2022, 22(3), 1202; https://doi.org/10.3390/s22031202 - 05 Feb 2022
Cited by 17 | Viewed by 6378
Abstract
We propose a frequency-modulated continuous wave (FMCW) radar estimation algorithm with high resolution and low complexity. The fast Fourier transform (FFT)-based algorithms and multiple signal classification (MUSIC) algorithms are used as algorithms for estimating target parameters in the FMCW radar systems. FFT-based and [...] Read more.
We propose a frequency-modulated continuous wave (FMCW) radar estimation algorithm with high resolution and low complexity. The fast Fourier transform (FFT)-based algorithms and multiple signal classification (MUSIC) algorithms are used as algorithms for estimating target parameters in the FMCW radar systems. FFT-based and MUSIC algorithms have tradeoff characteristics between resolution performance and complexity. While FFT-based algorithms have the advantage of very low complexity, they have the disadvantage of a low-resolution performance; that is, estimating multiple targets with similar parameters as a single target. On the other hand, subspace-based algorithms have the advantage of a high-resolution performance, but have a problem of very high complexity. In this paper, we propose an algorithm with reduced complexity, while achieving the high-resolution performance of the subspace-based algorithm by utilizing the advantages of the two algorithms; namely, the low-complexity advantage of FFT-based algorithms and the high-resolution performance of the MUSIC algorithms. The proposed algorithm first reduces the amount of data used as input to the subspace-based algorithm by using the estimation results obtained by FFT. Secondly, it significantly reduces the range of search regions considered for pseudo-spectrum calculations in the subspace-based algorithm. The simulation and experiment results show that the proposed algorithm achieves a similar performance compared with the conventional and low complexity MUSIC algorithms, despite its considerably lower complexity. Full article
(This article belongs to the Special Issue Sensors and Modern Technologies for Road, Robotic, and Intelligent Vehicle)
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14 pages, 4525 KiB  
Article
An Automotive Ferrofluidic Electromagnetic System for Energy Harvesting and Adaptive Damping
by Tadas Lenkutis, Darius Viržonis, Aurimas Čerškus, Andrius Dzedzickis, Nikolaj Šešok and Vytautas Bučinskas
Sensors 2022, 22(3), 1195; https://doi.org/10.3390/s22031195 - 04 Feb 2022
Cited by 5 | Viewed by 1896
Abstract
Vibration energy harvesting is receiving significant interest due to the possibility of using extra power in various machines and constructions. This paper presents an energy-harvesting system that has a structure similar to that of a linear generator but uses permanent magnets and magnetorheological [...] Read more.
Vibration energy harvesting is receiving significant interest due to the possibility of using extra power in various machines and constructions. This paper presents an energy-harvesting system that has a structure similar to that of a linear generator but uses permanent magnets and magnetorheological fluid insets. The application of a standard vehicle example with low frequencies and amplitudes of the excitations was used for the optimization and experimental runs. The optimization for low excitation amplitudes shows that the best magnetic field change along the slider is obtained using differentially orientated radial magnets of 5 mm in width. This configuration was used for the experimental research, resulting in 1.2–3.28 W of power generated in the coils. The power conditioning system in the experimental research was replaced by loading resistors. Nevertheless, the initial idea of energy harvesting and a damping effect was confirmed by the circuit voltage output. Full article
(This article belongs to the Special Issue Sensors and Modern Technologies for Road, Robotic, and Intelligent Vehicle)
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13 pages, 3359 KiB  
Article
Research of Distorted Vehicle Magnetic Signatures Recognitions, for Length Estimation in Real Traffic Conditions
by Donatas Miklusis, Vytautas Markevicius, Dangirutis Navikas, Mindaugas Cepenas, Juozas Balamutas, Algimantas Valinevicius, Mindaugas Zilys, Inigo Cuinas, Dardan Klimenta and Darius Andriukaitis
Sensors 2021, 21(23), 7872; https://doi.org/10.3390/s21237872 - 26 Nov 2021
Cited by 5 | Viewed by 1825
Abstract
Reliable cost-effective traffic monitoring stations are a key component of intelligent transportation systems (ITS). While modern surveillance camera systems provide a high amount of data, due to high installation price or invasion of drivers’ personal privacy, they are not the right technology. Therefore, [...] Read more.
Reliable cost-effective traffic monitoring stations are a key component of intelligent transportation systems (ITS). While modern surveillance camera systems provide a high amount of data, due to high installation price or invasion of drivers’ personal privacy, they are not the right technology. Therefore, in this paper we introduce a traffic flow parameterization system, using a built-in pavement sensing hub of a pair of AMR (anisotropic magneto resistance) magnetic field and MEMS (micro-electromechanical system) accelerometer sensors. In comparison with inductive loops, AMR magnetic sensors are significantly cheaper, have lower installation price and cause less intrusion to the road. The developed system uses magnetic signature to estimate vehicle speed and length. While speed is obtained from the cross-correlation method, a novel vehicle length estimation algorithm based on characterization of the derivative of magnetic signature is presented. The influence of signature filtering, derivative step and threshold parameter on estimated length is investigated. Further, accelerometer sensors are employed to detect when the wheel of vehicle passes directly over the sensor, which cause distorted magnetic signatures. Results show that even distorted signatures can be used for speed estimation, but it must be treated with a more robust method. The database during the real-word traffic and hazard environmental condition was collected over a 0.5-year period and used for method validation. Full article
(This article belongs to the Special Issue Sensors and Modern Technologies for Road, Robotic, and Intelligent Vehicle)
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20 pages, 21145 KiB  
Article
Environment Mapping Using Sensor Fusion of 2D Laser Scanner and 3D Ultrasonic Sensor for a Real Mobile Robot
by Tien Quang Tran, Andreas Becker and Damian Grzechca
Sensors 2021, 21(9), 3184; https://doi.org/10.3390/s21093184 - 04 May 2021
Cited by 10 | Viewed by 6092
Abstract
Mapping the environment is necessary for navigation, planning and manipulation. In this paper, a fusion framework (as data-in-decision-out) is introduced for a 2D LIDAR and a 3D ultrasonic sensor to achieve three-dimensional mapping without expensive 3D LiDAR scanner or visual processing. Two sensor [...] Read more.
Mapping the environment is necessary for navigation, planning and manipulation. In this paper, a fusion framework (as data-in-decision-out) is introduced for a 2D LIDAR and a 3D ultrasonic sensor to achieve three-dimensional mapping without expensive 3D LiDAR scanner or visual processing. Two sensor models are proposed for the two sensors used for map updating. Furthermore, 2D/3D map representations are discussed for our fusion approach. We also compare different probabilistic fusion methods and discuss criterias for choosing appropriate methods. Experiments are carried out with a real ground robot platform in an indoor environment. The 2D and 3D map results demonstrate that our approach is able to show the surrounding in more details. Sensor fusion provides a better estimation of the environment and the ego-pose whilst lowering the necessary resources. This gives the robot’s perception of the environment more information by using only one additional low-cost 3D ultrasonic sensor. This is especially important for robust and light-weight robots with limited resources. Full article
(This article belongs to the Special Issue Sensors and Modern Technologies for Road, Robotic, and Intelligent Vehicle)
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18 pages, 8897 KiB  
Article
Analysis and Synthesis of Traffic Scenes from Road Image Sequences
by Sheng Yuan, Yuting Chen, Huihui Huo and Li Zhu
Sensors 2020, 20(23), 6939; https://doi.org/10.3390/s20236939 - 04 Dec 2020
Cited by 1 | Viewed by 1738
Abstract
Traffic scene construction and simulation has been a hot topic in the community of intelligent transportation systems. In this paper, we propose a novel framework for the analysis and synthesis of traffic elements from road image sequences. The proposed framework is composed of [...] Read more.
Traffic scene construction and simulation has been a hot topic in the community of intelligent transportation systems. In this paper, we propose a novel framework for the analysis and synthesis of traffic elements from road image sequences. The proposed framework is composed of three stages: traffic elements detection, road scene inpainting, and road scene reconstruction. First, a new bidirectional single shot multi-box detector (BiSSD) method is designed with a global context attention mechanism for traffic elements detection. After the detection of traffic elements, an unsupervised CycleGAN is applied to inpaint the occlusion regions with optical flow. The high-quality inpainting images are then obtained by the proposed image inpainting algorithm. Finally, a traffic scene simulation method is developed by integrating the foreground and background elements of traffic scenes. The extensive experiments and comparisons demonstrate the effectiveness of the proposed framework. Full article
(This article belongs to the Special Issue Sensors and Modern Technologies for Road, Robotic, and Intelligent Vehicle)
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