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Smart Sensors for the Improvement of Sustainable Transport Modes and Road Safety

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

Deadline for manuscript submissions: closed (20 July 2023) | Viewed by 9142

Special Issue Editors

Dr. Alessandro Vitale

E-Mail Website
Guest Editor
Department of Civil Engineering, University of Calabria, Rende, Italy
Interests: intelligent transportation systems (ITS); microsimulation; artificial intelligence; road safety; public transport
Special Issues, Collections and Topics in MDPI journals
Dr. Vittorio Astarita

E-Mail Website
Guest Editor
Department of Civil Engineering, University of Calabria, 87036 Rende, Italy
Interests: transportation; road traffic simulation; road traffic safety; mobile computing applied to transportation systems; smart traffic lights; road safety performances
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Giuseppe Guido

E-Mail Website
Guest Editor
Department of Civil Engineering, University of Calabria, 87036 Rende, Italy
Interests: intelligent transportation systems; road safety; smart cities; smart devices; transit systems; traffic control; traffic flow model; driver behavior
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Due to a generalized doubling in road travels in each country with an even greater increase in costs of congestion and road accidents related social costs, an essential and challenging task for transportation researchers and planners is ensuring the promotion of sustainable transport modes and safety to road networks. To address these important objectives an interdisciplinary approach is needed, especially considering the recent rapid developments and advancements in transportation technologies and smart sensors. The motivation behind the special issue is provide concepts, approaches, techniques, and deployment strategies on the improvement of Road Safety through the employment of ITS technologies and Internet of things (IoT) based solutions.

Dr. Alessandro Vitale
Prof. Dr. Vittorio Astarita
Prof. Dr. Giuseppe Guido
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

  • Sustainable transport modes
  • Road safety
  • Intelligent transportation systems
  • Smart sensors
  • Simulation
  • Vehicle to vehicle communication
  • Vehicle to infrastructure communication
  • Big Data
  • Internet of Things

Published Papers (4 papers)

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Research

12 pages, 882 KiB  
Article
A New Form of Train Detection as a Solution to Improve Level Crossing Closing Time
by Michał Zawodny, Maciej Kruszyna, Wojciech Kazimierz Szczepanek and Mariusz Korzeń
Sensors 2023, 23(14), 6619; https://doi.org/10.3390/s23146619 - 23 Jul 2023
Viewed by 1473
Abstract
The critical points on the rail and road network are their intersections, i.e., level crossings. During a train crossing, car traffic is stopped. This reduces the fluidity of traffic on the road and, consequently, can cause congestion. The problem increases with the number [...] Read more.
The critical points on the rail and road network are their intersections, i.e., level crossings. During a train crossing, car traffic is stopped. This reduces the fluidity of traffic on the road and, consequently, can cause congestion. The problem increases with the number of cars and trains. Frequently, due to national regulations, level crossing closure times are long. It is mainly dictated by safety issues. Building two-level intersections is not always a good solution, mainly because of the high cost of implementation. In the article, the authors proposed the use of sensors to reduce level crossing closure times and improve the Level of Service on the road network. The analyzed railroad lines are local agglomeration lines, mainly due to safety (low speed of commuter trains) and high impact on the road network. The sensors proposed in the article are based on radar/LIDAR. Formulas similar to HCM methods are proposed, which can be implemented in a railroad crossing controller. Simulations using the PTV Vissim program are carried out and the results are worked out based on the obtained data. The considered method can reduce the level crossing closure time by 68.6%, thereby increasing the Level of Service on roads near railroads. Full article
(This article belongs to the Special Issue Smart Sensors for the Improvement of Sustainable Transport Modes and Road Safety)
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25 pages, 40349 KiB  
Article
BSafe-360: An All-in-One Naturalistic Cycling Data Collection Tool
by Suzana Duran Bernardes and Kaan Ozbay
Sensors 2023, 23(14), 6471; https://doi.org/10.3390/s23146471 - 17 Jul 2023
Cited by 1 | Viewed by 1081
Abstract
The popularity of bicycles as a mode of transportation has been steadily increasing. However, concerns about cyclist safety persist due to a need for comprehensive data. This data scarcity hinders accurate assessment of bicycle safety and identification of factors that contribute to the [...] Read more.
The popularity of bicycles as a mode of transportation has been steadily increasing. However, concerns about cyclist safety persist due to a need for comprehensive data. This data scarcity hinders accurate assessment of bicycle safety and identification of factors that contribute to the occurrence and severity of bicycle collisions in urban environments. This paper presents the development of the BSafe-360, a novel multi-sensor device designed as a data acquisition system (DAS) for collecting naturalistic cycling data, which provides a high granularity of cyclist behavior and interactions with other road users. For the hardware component, the BSafe-360 utilizes a Raspberry Pi microcomputer, a Global Positioning System (GPS) antenna and receiver, two ultrasonic sensors, an inertial measurement unit (IMU), and a real-time clock (RTC), which are all housed within a customized bicycle phone case. To handle the software aspect, BSafe-360 has two Python scripts that manage data processing and storage in both local and online databases. To demonstrate the capabilities of the device, we conducted a proof of concept experiment, collecting data for seven hours. In addition to utilizing the BSafe-360, we included data from CCTV and weather information in the data analysis step for verifying the occurrence of critical events, ensuring comprehensive coverage of all relevant information. The combination of sensors within a single device enables the collection of crucial data for bicycle safety studies, including bicycle trajectory, lateral passing distance (LPD), and cyclist behavior. Our findings show that the BSafe-360 is a promising tool for collecting naturalistic cycling data, facilitating a deeper understanding of bicycle safety and improving it. By effectively improving bicycle safety, numerous benefits can be realized, including the potential to reduce bicycle injuries and fatalities to zero in the near future. Full article
(This article belongs to the Special Issue Smart Sensors for the Improvement of Sustainable Transport Modes and Road Safety)
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17 pages, 10557 KiB  
Article
Practical Application of Drive-By Monitoring Technology to Road Roughness Estimation Using Buses in Service
by Kyosuke Yamamoto, Ryota Shin, Katsuki Sakuma, Masaaki Ono and Yukihiko Okada
Sensors 2023, 23(4), 2004; https://doi.org/10.3390/s23042004 - 10 Feb 2023
Cited by 2 | Viewed by 1470
Abstract
The efficiency of vehicles and travel comfort are maintained by the effective management of road pavement conditions. Pavement conditions can be inspected at a low cost by drive-by monitoring technology. Drive-by monitoring technology is a method of collecting data from sensors installed on [...] Read more.
The efficiency of vehicles and travel comfort are maintained by the effective management of road pavement conditions. Pavement conditions can be inspected at a low cost by drive-by monitoring technology. Drive-by monitoring technology is a method of collecting data from sensors installed on a running vehicle. This technique enables quick and low-cost inspections. However, most existing technologies assume that the vehicle runs at a constant speed. Therefore, this study devises a theoretical framework that estimates road unevenness without prior information about the vehicle’s mechanical parameters even when the running speed changes. This paper also shows the required function of sensors for this scheme. The required ability is to collect the three-axis acceleration vibration and position data simultaneously. A field experiment was performed to examine the applicability of sensors with both functions to the proposed methods. Each sensor was installed on a bus in service in this field experiment. The vehicle’s natural frequency estimated from the measured data ranges from 1 to 2 Hz, but the natural frequency estimated by the proposed method is 0.71 Hz. However, the estimated road unevenness does not change significantly with changes in the vehicle’s estimated parameters. The results found that the accuracy of road unevenness estimation seems to be acceptable with the conventional method and the new method. Future work will include improving the algorithm and accuracy verification of the schemes. Full article
(This article belongs to the Special Issue Smart Sensors for the Improvement of Sustainable Transport Modes and Road Safety)
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18 pages, 5175 KiB  
Article
One Metre Plus (1M+): A Multifunctional Open-Source Sensor for Bicycles Based on Raspberry Pi
by Andres Henao, Philippe Apparicio and David Maignan
Sensors 2021, 21(17), 5812; https://doi.org/10.3390/s21175812 - 29 Aug 2021
Cited by 5 | Viewed by 3930
Abstract
During the last decade, bicycles equipped with sensors became an essential tool for research, particularly for studies analyzing the lateral passing distance between motorized vehicles and bicycles. The objective of this article is to describe a low-cost open-source sensor called one metre plus [...] Read more.
During the last decade, bicycles equipped with sensors became an essential tool for research, particularly for studies analyzing the lateral passing distance between motorized vehicles and bicycles. The objective of this article is to describe a low-cost open-source sensor called one metre plus (1m+) capable of measuring lateral passing distance, registering the geographical position of the cyclist, and video-recording the trip. The plans, codes, and schematic design are open and therefore easily accessible for the scientific community. This study describes in detail the conceptualization process, the characteristics of the device, and the materials from which they are made. The study also provides an evaluation of the product and describes the sensor’s functionalities and its field of application. The objective of this project is to democratize research and develop a platform/participative project that offers tools to researchers worldwide, in order to standardize knowledge sharing and facilitate the comparability of results in various contexts. Full article
(This article belongs to the Special Issue Smart Sensors for the Improvement of Sustainable Transport Modes and Road Safety)
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