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Applied Sciences
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Future Intelligent Transportation System for Tomorrow and Beyond, 2nd Volume
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Future Intelligent Transportation System for Tomorrow and Beyond, 2nd Volume

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".

Deadline for manuscript submissions: closed (20 October 2023) | Viewed by 3702

Special Issue Editor

Prof. Dr. Dongsoo Har

E-Mail Website
Guest Editor
Cho Chun Shik Graduate School of Green Transportation, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
Interests: intelligent transportation system; sensor networking and its applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

An intelligent transportation system (ITS) can be broadly defined as a transportation system exploiting IT technologies. Raw traffic data collected by vehicular and infrastructure sensors require analysis and integration at a traffic control center for the eventual dissemination to traffic data consumers. These sequential processes dealing with traffic data involve the use of various scientific and engineering techniques. Considering various types of transportation modes, such as airway transport, railway transport, roadway transport, and waterway transport, the scope of ITS is immense.

This Special Issue is focused on scientific and engineering techniques for future ITS. Review articles on the evolution of each subfield of ITS as well as research articles on the state-of-the-art developments related to ITS will be considered for publication. Topics of interest for this Special Issue include but are not limited to the development of traffic sensors for roadway/railway transportation systems, 5G/6G connectivity of autonomous roadway vehicles, flight control of unmanned airway vehicles (UAV), and artificial intelligence (AI) for roadway/railway traffic analysis.

Prof. Dr. Dongsoo Har
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. Applied Sciences 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 2400 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
  • traffic sensor
  • 5G connectivity
  • autonomous vehicle
  • UAV
  • AI for ITS
  • traffic control
  • traffic data
  • transportation mode

Published Papers (2 papers)

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Research

17 pages, 5203 KiB  
Article
Location Optimization of Emergency Bell Based on Coverage Analysis for Crime Prevention
by Sun-Woo Lee, Hoi-Jeong Lim and Bo-Gyun Choi
Appl. Sci. 2023, 13(19), 10686; https://doi.org/10.3390/app131910686 - 26 Sep 2023
Viewed by 1033
Abstract
Typically, emergency bells are security facilities that, when activated, trigger an alarm and immediately dispatch a police car to prevent crime. However, there currently exists an ambiguity in the criteria for emergency bell installation. Consequently, this study aims to find an optimal location [...] Read more.
Typically, emergency bells are security facilities that, when activated, trigger an alarm and immediately dispatch a police car to prevent crime. However, there currently exists an ambiguity in the criteria for emergency bell installation. Consequently, this study aims to find an optimal location for emergency bells whilst considering several factors like cumulative crime incidents. In particular, we exploited emergency bell location data, data on five major crimes, and the geographic information of administrative dongs (primary division of districts) in this study. Specifically, we performed correlation analysis, principal component analysis, and K-means clustering for exploratory data analysis. To effectively cover all 17,437 crimes, which are not covered by the existing emergency bells in Gwangju metropolitan city from 2018 to 2021, the results from the implementation of the emergency bell location set-covering problem revealed the need for about 6228 emergency bells. More precisely, the emergency bell maximal covering location problem was employed to derive the coverage percentage for 250, 500, 800, 1000, and 1500 emergency bells. The results showed that 2850 emergency bells were required to cover over 80% of crime occurrence coordinates, saving over half of the budget compared with covering them all. Overall, this study is noteworthy in its potential role as a roadmap for the optimal placement of emergency bells for future crime prevention. Full article
(This article belongs to the Special Issue Future Intelligent Transportation System for Tomorrow and Beyond, 2nd Volume)
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15 pages, 4366 KiB  
Article
Targeting Lane-Level Map Matching for Smart Vehicles: Construction of High-Definition Road Maps Based on GIS
by Tian Lei, Gaoyao Xiao and Xiaohong Yin
Appl. Sci. 2023, 13(2), 862; https://doi.org/10.3390/app13020862 - 8 Jan 2023
Cited by 3 | Viewed by 2194
Abstract
The development of smart vehicles has increased the demand for high-definition road maps. However, traditional road maps for vehicle navigation systems are not sufficient to meet the requirements of intelligent vehicle systems (e.g., autonomous driving). The present work comes up with a method [...] Read more.
The development of smart vehicles has increased the demand for high-definition road maps. However, traditional road maps for vehicle navigation systems are not sufficient to meet the requirements of intelligent vehicle systems (e.g., autonomous driving). The present work comes up with a method of generating high-definition map models based on the geographic information system (GIS). A systematic map construction framework including the road layer, intersection connection layer, and lane layer is proposed based on the GIS database. Specifically, the constrained Delaunay triangular network method is applied to extract road layer network models, which are then used as linear reference networks to construct lane-level road maps. To further examine the feasibility of the proposed framework, a field experiment is then conducted to build a high-definition road map. Furthermore, a lane-level map matching test is conducted in the constructed road map using the trajectory data collected from a probe vehicle. The results show that the proposed method provides an efficient way of extracting lane-level information from urban road networks and can be applied for lane-level map matching with good performance. Full article
(This article belongs to the Special Issue Future Intelligent Transportation System for Tomorrow and Beyond, 2nd Volume)
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