Special Issue "Intelligent Mobility: Technologies, Applications and Services"

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

Deadline for manuscript submissions: 15 April 2022.

Special Issue Editors

Prof. Dr. Sadko Mandzuka
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Guest Editor
ITS Department, Faculty of Transport and Traffic Sciences, University of Zagreb, Croatia
Interests: intelligent transport systems; intelligent mobility; cooperative systems; implication of autonomous vehicles on traffic and society; smart city; sustainability
Dr. Kresimir Vidovic
E-Mail
Guest Editor
Ericsson Nikola Tesla d.d., Zagreb, Croatia
Interests: intelligent transport systems; application of ICT technologies in traffic and transport; intelligent mobility; application of data science in traffic and logistics; transport planning; mobility indicators

Special Issue Information

Dear Colleagues,

The main objective of this Special Issue is to present contemporary R & D achievements in urban mobility known as intelligent mobility. Modern urban traffic problems can no longer be solved solely by old approaches expanding various transport capacities. This approach only leads to more traffic induced by greater demands. The intelligent mobility approach addresses the problem of urban transport using information and communication technologies, via novel knowledge on how to plan and control such complex systems and processes and new business models in the transport of passengers and goods. The leading principles of intelligent mobility are: efficiency, safety, human friendliness, flexibility, sustainability, integration, and clean technologies. In that sense, intelligent mobility is one of the main avenues of the smart city concept.

Prof. Dr. Sadko Mandzuka
Dr. Kresimir Vidovic
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 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

  • Intelligent transport systems
  • Cooperative systems
  • Autonomous vehicles
  • Business models for new mobility platforms
  • Intelligent mobility and smart city
  • Sustainability
  • Technologies for intelligent transport planning
  • Sensor networks
  • Big data in urban mobility

Published Papers (2 papers)

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Research

Article
Influence of Variable Speed Limit Control on Fuel and Electric Energy Consumption, and Exhaust Gas Emissions in Mixed Traffic Flows
Sustainability 2022, 14(2), 932; https://doi.org/10.3390/su14020932 - 14 Jan 2022
Viewed by 150
Abstract
Modern urban mobility needs new solutions to resolve high-complexity demands on urban traffic-control systems, including reducing congestion, fuel and energy consumption, and exhaust gas emissions. One example is urban motorways as key segments of the urban traffic network that do not achieve a [...] Read more.
Modern urban mobility needs new solutions to resolve high-complexity demands on urban traffic-control systems, including reducing congestion, fuel and energy consumption, and exhaust gas emissions. One example is urban motorways as key segments of the urban traffic network that do not achieve a satisfactory level of service to serve the increasing traffic demand. Another complex need arises by introducing the connected and autonomous vehicles (CAVs) and accompanying additional challenges that modern control systems must cope with. This study addresses the problem of decreasing the negative environmental aspects of traffic, which includes reducing congestion, fuel and energy consumption, and exhaust gas emissions. We applied a variable speed limit (VSL) based on Q-Learning that utilizes electric CAVs as speed-limit actuators in the control loop. The Q-Learning algorithm was combined with the two-step temporal difference target to increase the algorithm’s effectiveness for learning the VSL control policy for mixed traffic flows. We analyzed two different optimization criteria: total time spent on all vehicles in the traffic network and total energy consumption. Various mixed traffic flow scenarios were addressed with varying CAV penetration rates, and the obtained results were compared with a baseline no-control scenario and a rule-based VSL. The data about vehicle-emission class and the share of gasoline and diesel human-driven vehicles were taken from the actual data from the Croatian Bureau of Statistics. The obtained results show that Q-Learning-based VSL can learn the control policy and improve the macroscopic traffic parameters and total energy consumption and can reduce exhaust gas emissions for different electric CAV penetration rates. The results are most apparent in cases with low CAV penetration rates. Additionally, the results indicate that for the analyzed traffic demand, the increase in the CAV penetration rate alleviates the need to impose VSL control on an urban motorway. Full article
(This article belongs to the Special Issue Intelligent Mobility: Technologies, Applications and Services)
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Article
Data-Driven Methodology for Sustainable Urban Mobility Assessment and Improvement
Sustainability 2021, 13(13), 7162; https://doi.org/10.3390/su13137162 - 25 Jun 2021
Cited by 1 | Viewed by 603
Abstract
The transport system is sensitive to external influences generated by various economic, social and environmental changes. The society and the environment are changing extremely fast, resulting in the need for rapid adjustment of the transport system. Traffic system management, especially in urban areas, [...] Read more.
The transport system is sensitive to external influences generated by various economic, social and environmental changes. The society and the environment are changing extremely fast, resulting in the need for rapid adjustment of the transport system. Traffic system management, especially in urban areas, is a dynamic process, which is why transport planners are in need of a proven and validated methodology for fast and efficient transport data collection, fusion and analytics that will be used in sustainable urban mobility policy creation. The paper presents a development of a methodology in data rich reality that combines traditional and novel data science approach for transport system analysis and planning. The result is overall process consisting of 150 steps from first desktop research to final solution development. It enables urban mobility stakeholders to identify transport problems, analyze the urban mobility situation and to propose dedicated measures for sustainable urban mobility strengthening. The methodology is based on a big data research and analysis on anonymized big data sets originating from mobile telecommunication network, where the extraction of mobility data from the big dataset is the most innovative part of the proposed process. The extracted mobility data were validated through a “conventional” field research. The methodology was, for additional testing, applied in a pilot study, performed in the City of Rijeka in Croatia. It resulted in a set of alternative measures for modal shift from passenger cars to sustainable mobility modes, that were validated by the local public and urban mobility stakeholders. Full article
(This article belongs to the Special Issue Intelligent Mobility: Technologies, Applications and Services)
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