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11.2
6.4
Journals
Smart Cities
Special Issues
Road Safety in Smart Cities
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Road Safety in Smart Cities

A special issue of Smart Cities (ISSN 2624-6511). This special issue belongs to the section "Smart Transportation".

Deadline for manuscript submissions: closed (30 December 2019) | Viewed by 11746

Special Issue Editors

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
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

Special Issue Information

Dear Colleagues,

Economic growth in most of countries has led to more than a doubling in road travels with an even greater increase in costs of congestion and road accident-related social costs, especially in urban areas. In this context, an essential and challenging task for transportation researchers and planners is ensuring the safety of road networks.

To address this important objective, an interdisciplinary approach is needed, especially considering the rapid developments and new advancements in transportation technologies.

As road safety represents an important area of ​​interest for smart city ecosystems, researchers, professionals, and governments look to Intelligent Transportation Systems (ITS) and Internet of Things (IoT) as solutions to transport problems. The employment of ITS technologies and IoT solutions allows for the collection, sharing, and analysis of information about vehicles, road infrastructures, and drivers to prevent accidents and make the driving experience safe and enjoyable for road users.

The motivation behind this Special Issue is the sharing of concepts, approaches, techniques, and deployment strategies on the improvement of road safety through the employment of ITS technologies and IoT-based solutions.

We encourage high-quality, original submissions and innovative research providing significant contributions to the theory and practice of road safety and data-driven decision making.

Prof. Giuseppe Piero Guido
Dr. Alessandro Vitale
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. Smart Cities 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 2000 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

  • Road safety
  • Intelligent transportation systems
  • Driver behavior modeling and simulation
  • Big data and Internet of Things (IOT)
  • Road accidents
  • Smart roads
  • V2V and V2I communication

Published Papers (2 papers)

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Research

17 pages, 1413 KiB  
Article
Mobile Computing for Disaster Emergency Management: Empirical Requirements Analysis for a Cooperative Crowdsourced System for Emergency Management Operation
by Vittorio Astarita, Vincenzo Pasquale Giofrè, Giuseppe Guido, Giulio Stefano and Alessandro Vitale
Smart Cities 2020, 3(1), 31-47; https://doi.org/10.3390/smartcities3010003 - 7 Feb 2020
Cited by 8 | Viewed by 3460
Abstract
In large-scale civil emergencies such as floods, earthquakes, and extreme weather conditions, extended geographic areas and a great number of people may be affected by the unfortunate events. The wireless internet and the widespread diffusion of smart-phones and mobile devices make it possible [...] Read more.
In large-scale civil emergencies such as floods, earthquakes, and extreme weather conditions, extended geographic areas and a great number of people may be affected by the unfortunate events. The wireless internet and the widespread diffusion of smart-phones and mobile devices make it possible to introduce new systems for emergency management. These systems could improve the efficiency of the interventions by transferring information between affected areas and a central decision support system. Information on the state of the infrastructures, on people displacement, and on every other important and urgent issue can be gathered in the disaster area. The central system can manage all the received information and communicate decisions back to people and also facilitate the exchange of information for different people that are still in the disaster area. This paper presents a requirement analysis for these kinds of systems. The presented analysis allows better tailoring of the features of these systems with the aim to meet the real need of emergency management operators and citizens. Full article
(This article belongs to the Special Issue Road Safety in Smart Cities)
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14 pages, 1886 KiB  
Article
Identify a Spoofing Attack on an In-Vehicle CAN Bus Based on the Deep Features of an ECU Fingerprint Signal
by Yun Yang, Zongtao Duan and Mark Tehranipoor
Smart Cities 2020, 3(1), 17-30; https://doi.org/10.3390/smartcities3010002 - 17 Jan 2020
Cited by 33 | Viewed by 7439
Abstract
An in-vehicle controller area network (CAN) bus is vulnerable because of increased sharing among modern autonomous vehicles and the weak protocol design principle. Spoofing attacks on a CAN bus can be difficult to detect and have the potential to enable devastating attacks. To [...] Read more.
An in-vehicle controller area network (CAN) bus is vulnerable because of increased sharing among modern autonomous vehicles and the weak protocol design principle. Spoofing attacks on a CAN bus can be difficult to detect and have the potential to enable devastating attacks. To effectively identify spoofing attacks, we propose the authentication of sender identities using a recurrent neural network with long short-term memory units (RNN-LSTM) based on the features of a fingerprint signal. We also present a way to generate the analog fingerprint signals of electronic control units (ECUs) to train the proposed RNN-LSTM classifier. The proposed RNN-LSTM model is accelerated on embedded Field-Programmable Gate Arrays (FPGA) to allow for real-time detection despite high computational complexity. A comparison of experimental results with the latest studies demonstrates the capability of the proposed RNN-LSTM model and its potential as a solution to in-vehicle CAN bus security. Full article
(This article belongs to the Special Issue Road Safety in Smart Cities)
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