Special Issue "Intelligent Transportation Systems Application in Smart Cities"

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: 30 November 2021.

Special Issue Editors

Prof. Zhiyuan Liu
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Guest Editor
School of Transportation, Southeast University; Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 211189, China
Interests: transport network modeling; public transport; big data analytics
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Dr. Xinyuan Chen
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Guest Editor
Department of Logistics and Maritime Studies, Hong Kong Polytechnic University, Hung Hom, Hong Kong
Interests: urban transport network modeling; parallel computing in transport system analysis; big data analytics
Special Issues and Collections in MDPI journals
Dr. Di Huang
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Guest Editor
Department of Logistics and Maritime Studies, Hong Kong Polytechnic University, Hung Hom, Hong Kong
Interests: public transit system; transportation network modeling; urban mobility modeling and optimization
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

We are calling for papers for a Special Issue of the journal Sustainability on research into the intelligent transportation system applications in smart cities. Recently, new technologies on transportation are developing rapidly, such as connected and automated vehicles, and shared mobility services. The rapid evolution of techniques brings great opportunities and challenges to refine the urban transport systems. Successful implementation of intelligent transportation applications depends on multiple factors, including technical, operational, and political aspects. Designing, testing, and implementation of effective intelligent transportation applications require multi-disciplinary and emerging techniques. Meanwhile, new sensing and data resources bring opportunities for data-driven applications to better reflect the features and dynamics of urban transportation systems. The increasingly available data and the complexity of mathematical models also bring the challenge of large-scale computation. Therefore, new algorithms and computation methods have become a significant area of research. The overall objective of this special issue is to collect innovative contributions to the application of advanced transport techniques in smart cities. Proposed papers for this special issue may cover a broad range of modelling, control, design, monitoring, management, and optimization of intelligent transportation system applications, as long as the focus on emerging techniques.

Prof. Zhiyuan Liu
Dr. Xinyuan Chen
Dr. Di Huang
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 papers will be 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. Sustainability 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 1900 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

  • artificial intelligence
  • big data and machine learning
  • ITS deployment experiences
  • ITS innovations
  • smart cities
  • connected vehicle systems
  • mobility as a service systems
  • shared mobility services
  • traffic management and control
  • sustainable transportation

Published Papers (1 paper)

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Research

Article
Unravelling the Impacts of Parameters on Surrogate Safety Measures for a Mixed Platoon
Sustainability 2020, 12(23), 9955; https://doi.org/10.3390/su12239955 - 28 Nov 2020
Viewed by 485
Abstract
With the precedence of connected automated vehicles (CAVs), car-following control technology is a promising way to enhance traffic safety. Although a variety of research has been conducted to analyze the safety enhancement by CAV technology, the parametric impact on CAV technology has not [...] Read more.
With the precedence of connected automated vehicles (CAVs), car-following control technology is a promising way to enhance traffic safety. Although a variety of research has been conducted to analyze the safety enhancement by CAV technology, the parametric impact on CAV technology has not been systematically explored. Hence, this paper analyzes the parametric impacts on surrogate safety measures (SSMs) for a mixed vehicular platoon via a two-level analysis structure. To construct the active safety evaluation framework, numerical simulations were constructed which can generate trajectories for different kind of vehicles while considering communication and vehicle dynamics characteristics. Based on the trajectories, we analyzed parametric impacts upon active safety on two different levels. On the microscopic level, parameters including controller dynamic characteristics and equilibrium time headway of car-following policies were analyzed, which aimed to capture local and aggregated driving behavior’s impact on the vehicle. On the macroscopic level, parameters incorporating market penetration rate (MPR), vehicle topology, and vehicle-to-vehicle environment were extensively investigated to evaluate their impacts on aggregated platoon level safety caused by inter-drivers’ behavioral differences. As indicated by simulation results, an automated vehicle (AV) suffering from degradation is a potentially unsafe component in platoon, due to the loss of a feedforward control mechanism. Hence, the introduction of connected automated vehicles (CAVs) only start showing benefits to platoon safety from about 20% CAV MPR in this study. Furthermore, the analysis on vehicle platoon topology suggests that arranging all CAVs at the front of a mixed platoon assists in enhancing platoon SSM performances. Full article
(This article belongs to the Special Issue Intelligent Transportation Systems Application in Smart Cities)
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