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Vehicles
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Recent Developments in the Intelligent Transportation System (ITS)
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Recent Developments in the Intelligent Transportation System (ITS)

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

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 19017

Special Issue Editors

Dr. Hocine Imine

E-Mail Website
Guest Editor
Laboratoire sur la Perception, les Interactions, les Comportements et la Simulation des usagers de la route et de la rue (PICS-L), Université Gustave Eiffel, Marne la Vallée, France
Interests: intelligent transportation systems; simulators and vehicles modeling; nonlinear observation; nonlinear control
Special Issues, Collections and Topics in MDPI journals
Dr. Claudio Lantieri

E-Mail Website
Guest Editor
Department of Civil, Chemical, Environmental, and Materials Engineering, Alma Mater Studiorum Università di Bologna, Bologna, Italy
Interests: road maintenance; safety; road materials; skid resistance and surface characteristics of road pavement
Special Issues, Collections and Topics in MDPI journals
Dr. Mehdi Azimi

E-Mail Website
Guest Editor
Department of Transportation Studies, College of Science, Engineering and Technology, Texas Southern University, Houston, TX 77004, USA
Interests: intelligent transportation system (ITS) technologies and applications; connected and automated vehicles (CAVs); freight transportation and logistics; big data an-alytics; transportation security and cyber resilience

Special Issue Information

Dear Colleagues,

Intelligent transportation systems (ITSs) use emerging technologies (information, sensing, computing, and communications) to advance transportation safety, to improve mobility and operating efficiencies and reliability, to enhance user productivity, and to maintain transportation sustainability and reduce the environmental impact of the growing travel demand. These technologies target the transportation infrastructure, vehicles, and travelers, as well as integrated applications among them. ITSs are also a key component of the movement towards connected and smart communities, which incorporate connected transportation and travelers to ensure that data, technologies, and applications are fully integrated with other systems across a community. Intelligent transportation systems cover all modes of transportation, including ground transportation such as private automobiles, commercial vehicles, and public transit, but also rail, marine, and air.

For this Special Issue of Vehicles, entitled “Recent Developments in the Intelligent Transportation System (ITS)”, we encourage the submission of interdisciplinary research involving vehicles and the transportation infrastructure, as well as integrated applications between the two. Topics include, but are not limited to:

  • Automated vehicle (AV) technology;
  • Connected and automated vehicle (CAV);
  • Cooperative driving automation (CDA);
  • Vehicle to everything (V2X) technologies, including vehicle to pedestrian (V2P), vehicle to vehicle (V2V), and vehicle to infrastructure (V2I);
  • Intelligent traffic control systems and next-generation traffic management systems;
  • Intelligent commercial vehicle systems;
  • Advanced transit systems;
  • Privacy and security of ITS.

Dr. Hocine Imine
Dr. Claudio Lantieri
Dr. Mehdi Azimi
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. 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

  • intelligent transportation system
  • ITS

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Related Special Issue

Published Papers (5 papers)

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Research

14 pages, 3014 KiB  
Article
A Vehicle Crash Simulator Using Digital Twin Technology for Synthesizing Simulation and Graphical Models
by Su Man Nam, Jieun Park, Chaeyeon Sagong, Yujin Lee and Hyung-Jong Kim
Vehicles 2023, 5(3), 1046-1059; https://doi.org/10.3390/vehicles5030057 - 28 Aug 2023
Cited by 1 | Viewed by 3140
Abstract
Computer vehicle simulators are used to model real-world situations to overcome time and cost limitations. The vehicle simulators provide virtual scenarios for real-world driving. Although the existing simulators precisely observe movement on the basis of good-quality graphics, they focus on a few driving [...] Read more.
Computer vehicle simulators are used to model real-world situations to overcome time and cost limitations. The vehicle simulators provide virtual scenarios for real-world driving. Although the existing simulators precisely observe movement on the basis of good-quality graphics, they focus on a few driving vehicles instead of accident simulation. In addition, it is difficult to represent vehicle collisions. We propose a vehicle crash simulator with simulation and animation components. The proposed simulator synthesizes and simulates models of vehicles and environments. The simulator animates corresponding to the simulation through the execution results. The simulation results validate that the proposed simulator provides collision and non-collision results according to the speed of two vehicles at an intersection. Full article
(This article belongs to the Special Issue Recent Developments in the Intelligent Transportation System (ITS))
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18 pages, 10488 KiB  
Article
Road Condition Monitoring Using Vehicle Built-in Cameras and GPS Sensors: A Deep Learning Approach
by Cuthbert Ruseruka, Judith Mwakalonge, Gurcan Comert, Saidi Siuhi and Judy Perkins
Vehicles 2023, 5(3), 931-948; https://doi.org/10.3390/vehicles5030051 - 7 Aug 2023
Cited by 8 | Viewed by 6959
Abstract
Road authorities worldwide can leverage the advances in vehicle technology by continuously monitoring their roads’ conditions to minimize road maintenance costs. The existing methods for carrying out road condition surveys involve manual observations using standard survey forms, performed by qualified personnel. These methods [...] Read more.
Road authorities worldwide can leverage the advances in vehicle technology by continuously monitoring their roads’ conditions to minimize road maintenance costs. The existing methods for carrying out road condition surveys involve manual observations using standard survey forms, performed by qualified personnel. These methods are expensive, time-consuming, infrequent, and can hardly provide real-time information. Some automated approaches also exist but are very expensive since they require special vehicles equipped with computing devices and sensors for data collection and processing. This research aims to leverage the advances in vehicle technology in providing a cheap and real-time approach to carry out road condition monitoring (RCM). This study developed a deep learning model using the You Only Look Once, Version 5 (YOLOv5) algorithm that was trained to capture and categorize flexible pavement distresses (FPD) and reached 95% precision, 93.4% recall, and 97.2% mean Average Precision. Using vehicle built-in cameras and GPS sensors, these distresses were detected, images were captured, and locations were recorded. This was validated on campus roads and parking lots using a car featured with a built-in camera and GPS. The vehicles’ built-in technologies provided a more cost-effective and efficient road condition monitoring approach that could also provide real-time road conditions. Full article
(This article belongs to the Special Issue Recent Developments in the Intelligent Transportation System (ITS))
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17 pages, 975 KiB  
Article
Cloud-Based Reinforcement Learning in Automotive Control Function Development
by Lucas Koch, Dennis Roeser, Kevin Badalian, Alexander Lieb and Jakob Andert
Vehicles 2023, 5(3), 914-930; https://doi.org/10.3390/vehicles5030050 - 2 Aug 2023
Cited by 1 | Viewed by 2455
Abstract
Automotive control functions are becoming increasingly complex and their development is becoming more and more elaborate, leading to a strong need for automated solutions within the development process. Here, reinforcement learning offers a significant potential for function development to generate optimized control functions [...] Read more.
Automotive control functions are becoming increasingly complex and their development is becoming more and more elaborate, leading to a strong need for automated solutions within the development process. Here, reinforcement learning offers a significant potential for function development to generate optimized control functions in an automated manner. Despite its successful deployment in a variety of control tasks, there is still a lack of standard tooling solutions for function development based on reinforcement learning in the automotive industry. To address this gap, we present a flexible framework that couples the conventional development process with an open-source reinforcement learning library. It features modular, physical models for relevant vehicle components, a co-simulation with a microscopic traffic simulation to generate realistic scenarios, and enables distributed and parallelized training. We demonstrate the effectiveness of our proposed method in a feasibility study to learn a control function for automated longitudinal control of an electric vehicle in an urban traffic scenario. The evolved control strategy produces a smooth trajectory with energy savings of up to 14%. The results highlight the great potential of reinforcement learning for automated control function development and prove the effectiveness of the proposed framework. Full article
(This article belongs to the Special Issue Recent Developments in the Intelligent Transportation System (ITS))
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11 pages, 3238 KiB  
Article
Assessing the Accessibility of Cycling Infrastructure for Wheelchair Users: Insights from an On-Road Experiment and Online Questionnaire Study
by Murad Shoman and Hocine Imine
Vehicles 2023, 5(1), 321-331; https://doi.org/10.3390/vehicles5010018 - 2 Mar 2023
Cited by 1 | Viewed by 2923
Abstract
In this paper, we pay significant attention to the most vulnerable road users (i.e., people with disabilities) when interacting with cyclists. The special needs of these groups are studied by distributing an online questionnaire about their perception and interaction with cyclists besides conducting [...] Read more.
In this paper, we pay significant attention to the most vulnerable road users (i.e., people with disabilities) when interacting with cyclists. The special needs of these groups are studied by distributing an online questionnaire about their perception and interaction with cyclists besides conducting an on-road experiment to test the possibility of sharing cycling infrastructure with wheelchair users. In an authentic case study, 2 cyclists and 5 wheelchair users were asked to ride their vehicles on a cycling lane in Madrid, in order to evaluate wheelchair users’ interaction with cyclists and reaction to the infrastructure by applying objective and subjective measures. The participants were provided with GPS, a speed sensor, and a head-mounted camera to record the experiment. The results show that people with disabilities feel threatened by cyclists who share the sidewalk with them; the respondents to the questionnaire suggested making the sidewalk free of cyclists to avoid conflict and improve safety. Moreover, the outputs of the experiment show positive feedback from wheelchair users when sharing cycling infrastructure regarding the improvement of speed and safety feeling. However, it is recommended to increase the number of wheelchair users to obtain more reliable and generalizable results. Full article
(This article belongs to the Special Issue Recent Developments in the Intelligent Transportation System (ITS))
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20 pages, 11817 KiB  
Article
Does the Condition of the Road Markings Have a Direct Impact on the Performance of Machine Vision during the Day on Dry Roads?
by Abdessamad El Krine, Maxime Redondin, Joffrey Girard, Christophe Heinkele, Aude Stresser and Valérie Muzet
Vehicles 2023, 5(1), 286-305; https://doi.org/10.3390/vehicles5010016 - 24 Feb 2023
Cited by 2 | Viewed by 2309
Abstract
The forthcoming arrival of automated vehicles (AV) on the roads requires the re-evaluation or even adaptation of existing infrastructures as they are currently designed on the basis of human perception. Indeed, advanced driver-assistance systems (ADAS) do not necessarily have the same needs as [...] Read more.
The forthcoming arrival of automated vehicles (AV) on the roads requires the re-evaluation or even adaptation of existing infrastructures as they are currently designed on the basis of human perception. Indeed, advanced driver-assistance systems (ADAS) do not necessarily have the same needs as drivers to detect road markings. One of the main challenges related to AV is the optimisation of the vehicle–infrastructure pair in order to guarantee the safety of all users. In this context, we compared the performance of a vehicle equipped with an ADAS machine-vision system with a dynamic retroreflectometer during the daytime on a road section. Our results questioned the reliability of the literature thresholds of the luminance contrast ratio on a dry road under sunny conditions. Despite the presence of old and worn road markings, the ADAS camera was able to detect the edge lines in more than 90% of the cases. The non-detections were not related to the poor condition of the markings but to the environmental conditions or the complexity of the infrastructure. Full article
(This article belongs to the Special Issue Recent Developments in the Intelligent Transportation System (ITS))
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