Internet of Vehicles and Vehicles Engineering

A special issue of Vehicles (ISSN 2624-8921).

Deadline for manuscript submissions: closed (20 November 2022) | Viewed by 14817

Special Issue Editor

Institute of Solid Mechanics, Romanian Academy, 030167 București, Romania
Interests: mechatronics and robotics; mechanical engineering; rapid prototyping and rapid manufacturing; manufacturing technologies; advanced technologies and nano-technologies; applied statistics in engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are living in a changing and challenging world, and the aim for various types of activities is to achieve targets in the shortest amount of time.

When the challenge is moving from one place to another, there are many options to consider: riding or driving, by train, by plane or by another type of aircraft. In the context of travelling in the shortest amount of time, when dealing with transportation, it has to be fast, safe and suitable for the needs of the people or goods being transported.

The planet faces severe climate change, which has important impacts on mankind from in terms of economic, social and political aspects. That is why mandatory measures must be taken for reducing GHG emissions, in the transportation industry and in other sectors.

The amazing development of AI and its application in everyday life—in terms of assistive devices, 4G and 5G technologies, and smart city infrastructure—has a huge impact on the concepts, designs and manufacturing of vehicles, as well the users’ perceptions and requirements.

To enable large-scale and ubiquitous automotive network access, traditional vehicle-to-everything (V2X) technologies are evolving in the Internet of Vehicles (IoV) for increasing demands on emerging advanced vehicular applications, such as intelligent transportation systems (ITS) and autonomous vehicles.

The scope of this Special Issue, "Internet of Vehicles and Vehicles Engineering", is to bring together scientists, engineers, managers and users of vehicles in these times of advanced communication and manufacturing technologies, so as to share their experience and scientific results.

Dr. Mihaiela Iliescu
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. Vehicles is an international peer-reviewed open access quarterly 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 1600 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

  • concept and design of vehicles
  • IoVs
  • fuel vehicles
  • hybrid and EV vehicle
  • advanced manufacturing technology for smart vehicles
  • smart city infrastructure
  • risk management for smart vehicles

Published Papers (4 papers)

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Research

20 pages, 13227 KiB  
Article
Antennas in the Internet of Vehicles: Application for X Band and Ku Band in Low-Earth-Orbiting Satellites
by Ming-An Chung, Kuo-Chun Tseng and Ing-Peng Meiy
Vehicles 2023, 5(1), 55-74; https://doi.org/10.3390/vehicles5010004 - 04 Jan 2023
Cited by 4 | Viewed by 2655
Abstract
This paper proposes a simple and small-dimensioned antenna that can provide X band and Ku band for the low-earth-orbiting (LEO) satellite system in an Internet of vehicles system. The antenna is designed on the substrate Arlon DiClad 880. The antenna structure consists of [...] Read more.
This paper proposes a simple and small-dimensioned antenna that can provide X band and Ku band for the low-earth-orbiting (LEO) satellite system in an Internet of vehicles system. The antenna is designed on the substrate Arlon DiClad 880. The antenna structure consists of an inverted triangle geometry and an inverted U-shaped slot. The dimensions of the antenna are 12.5 × 5 mm2, and the area of the substrate is 30 × 13 × 0.254 mm3. The antenna is easy to make, and the manufacturing cost is low. The measurement results of the reflection coefficient (lower than −10 dB) of the antenna show that the working frequency band can cover the X-band (10.87–12.76 GHz) and the Ku band (15.19–16.02 GHz). The measured and simulated results are fairly similar. The efficiency of the antenna in the X-band is about 50–80.8%. The efficiency of the antenna in the Ku-band is about 50–74%. The gains of the antennas are about 3.34–6.08 dBi and 3.50–4.65 dBi in the X-band and Ku band, respectively, and the highest gain is 6.08 dBi. The antenna design can realize the features of low cost and small dimensions in autonomous vehicles and vehicle networking communication system equipment and achieve good wireless transmission capabilities from vehicles to the base station in the IOV. Full article
(This article belongs to the Special Issue Internet of Vehicles and Vehicles Engineering)
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23 pages, 558 KiB  
Article
Internet of Vehicles and Real-Time Optimization Algorithms: Concepts for Vehicle Networking in Smart Cities
by Ferran Adelantado, Majsa Ammouriova, Erika Herrera, Angel A. Juan, Swapnil Sadashiv Shinde and Daniele Tarchi
Vehicles 2022, 4(4), 1223-1245; https://doi.org/10.3390/vehicles4040065 - 03 Nov 2022
Cited by 6 | Viewed by 2979
Abstract
Achieving sustainable freight transport and citizens’ mobility operations in modern cities are becoming critical issues for many governments. By analyzing big data streams generated through IoT devices, city planners now have the possibility to optimize traffic and mobility patterns. IoT combined with innovative [...] Read more.
Achieving sustainable freight transport and citizens’ mobility operations in modern cities are becoming critical issues for many governments. By analyzing big data streams generated through IoT devices, city planners now have the possibility to optimize traffic and mobility patterns. IoT combined with innovative transport concepts as well as emerging mobility modes (e.g., ridesharing and carsharing) constitute a new paradigm in sustainable and optimized traffic operations in smart cities. Still, these are highly dynamic scenarios, which are also subject to a high uncertainty degree. Hence, factors such as real-time optimization and re-optimization of routes, stochastic travel times, and evolving customers’ requirements and traffic status also have to be considered. This paper discusses the main challenges associated with Internet of Vehicles (IoV) and vehicle networking scenarios, identifies the underlying optimization problems that need to be solved in real time, and proposes an approach to combine the use of IoV with parallelization approaches. To this aim, agile optimization and distributed machine learning are envisaged as the best candidate algorithms to develop efficient transport and mobility systems. Full article
(This article belongs to the Special Issue Internet of Vehicles and Vehicles Engineering)
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14 pages, 2338 KiB  
Article
Framework for Building Low-Cost OBD-II Data-Logging Systems for Battery Electric Vehicles
by Clarence Ramai, Veeresh Ramnarine, Shankar Ramharack, Sanjay Bahadoorsingh and Chandrabhan Sharma
Vehicles 2022, 4(4), 1209-1222; https://doi.org/10.3390/vehicles4040064 - 28 Oct 2022
Cited by 4 | Viewed by 6344
Abstract
With the electrification of transport (BEVs) and the growing benefits of smart vehicles, there is a need for a simple solution to perform real-time monitoring of the BEV and its battery for diagnostics and coordinated charging. The On-Board Diagnostics (OBD) system, originally designed [...] Read more.
With the electrification of transport (BEVs) and the growing benefits of smart vehicles, there is a need for a simple solution to perform real-time monitoring of the BEV and its battery for diagnostics and coordinated charging. The On-Board Diagnostics (OBD) system, originally designed for internal combustion engine cars (ICE), can be used to extract the necessary BEV data. This paper presents a developed framework for a low-cost solution to online monitoring of BEVs. A Raspberry Pi Zero W, along with other auxiliary components, was installed in two Hyundai Ioniq Battery Electric cars to communicate with the vehicles via the OBD-II port. A python script was developed to periodically request the vehicle data by sending various Parameter IDs to the vehicles and storing the raw response data. A web server was created to process the hexadecimal encoded data and visualize the data on a dashboard. The key parameters, such as the battery state of health (SOH), state of charge (SOC), battery temperature, cell voltages and cumulative energy consumption, were successfully captured and recorded, which can now facilitate trending for battery diagnostics and future integration with smart chargers for coordinated charging. Full article
(This article belongs to the Special Issue Internet of Vehicles and Vehicles Engineering)
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14 pages, 1663 KiB  
Article
A Fuzzy Logic Approach for Determining Driver Impatience and Stress Leveraging Internet of Vehicles Infrastructure
by Kevin Bylykbashi, Ermioni Qafzezi, Phudit Ampririt, Makoto Ikeda, Keita Matsuo and Leonard Barolli
Vehicles 2022, 4(2), 553-566; https://doi.org/10.3390/vehicles4020032 - 02 Jun 2022
Cited by 1 | Viewed by 1891
Abstract
Drivers are held responsible for the vast majority of traffic crashes. Although most of the errors causing these accidents are involuntary, a significant number of them are caused by irresponsible driving behaviors, which must be utterly preventable. Irresponsible driving, on the other hand, [...] Read more.
Drivers are held responsible for the vast majority of traffic crashes. Although most of the errors causing these accidents are involuntary, a significant number of them are caused by irresponsible driving behaviors, which must be utterly preventable. Irresponsible driving, on the other hand, is often associated with driver stress and the impatience they show while driving. In this paper, we consider the factors that cause drivers to become impatient and experience stress and propose an integrated fuzzy logic system that determines the stress level in real time. Based on the stress level, the proposed system can take the appropriate action that improves the driving situation and consequently road safety. By using inputs, such as the unnecessary maneuvers that drivers make, the time pressure, and the number of times they are forced to stop, a fuzzy logic controller determines the driver’s impatience, which is then considered alongside other factors, such as the driving experience and history, the behavior of other drivers, and the traffic condition to determine the stress level. We show, through simulations, the feasibility of the proposed approach to accurately determine driver stress and demonstrate some actions that can be performed when stress exceeds certain levels. Full article
(This article belongs to the Special Issue Internet of Vehicles and Vehicles Engineering)
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