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Sustainability
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Sustainable Traffic Operations and Mobility Services
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Sustainable Traffic Operations and Mobility Services

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

Deadline for manuscript submissions: closed (31 October 2021) | Viewed by 13471

Special Issue Editors

Prof. Davide Giglio

E-Mail Website
Guest Editor
Department of Mechanical, Energy, Management and Transportation Engineering, University of Genoa, 16126 Genova, Italy
Interests: urban mobility optimization; modelling and control of urban traffic networks; optimization of logistics systems and supply chains; logistics of hazardous materials
Dr. Alice Consilvio

E-Mail Website
Guest Editor
Department of Mechanical, Energy, Management and Transportation Engineering, University of Genoa, 16126 Genova, Italy
Interests: rail transport; multimodal transportation; transport modelling and simulation; mobility-as-a-service; optimization and decision-support

Special Issue Information

Dear Colleagues,

The planning and control of transport services play a key role in the achievement of sustainability goals in transportation systems. The optimization of operations can have significant direct or indirect impacts on economic, environmental and social sustainability, improving the efficiency, reducing the emissions of pollutants and increasing the inclusiveness of transport services. These aspects involve all the transport modes, considered separately or in an integrated way, including both passengers and freight sectors. Some significant examples are road traffic control, trains operations, inland waterways management, and the synchronization of transport flows. In this scenario, the introduction of ICT and automation has paved the way towards advanced intelligent transportation systems (ITS) able to reach a high level of performance in traffic control, in a more integrated and cooperative way, exploiting data availability. Recent events, such as the COVID-19 pandemic, have also shown the importance of sustainability strategies in long-term and mid-/short-term transportation planning.

 The scope of the Special Issue is to gather state-of-the-art contributions in the field of sustainable transportation, with a particular focus on models and methods for optimizing and controlling traffic operations and mobility services, at the various decision levels. Analytical and simulative models, innovative approaches, new technologies and novel applications aimed at further improving current practices for sustainable transportation are welcomed.

Topics of interest include, but are not limited to:

  • optimization and control of transport networks
  • real-time management of transport operations
  • advanced simulation models in transportation
  • disruptions and emergency management
  • day-to-day and within day traffic assignment models
  • intelligent transportation systems (ITS) technologies and automated transport solutions
  • passengers flow control and crowd management
  • users’ choice modelling and advanced traveller information systems.
  • electric mobility and charging infrastructure
  • multimodal mobility solutions
  • artificial intelligence (AI) for smarter mobility

Prof. Davide Giglio
Dr. Alice Consilvio
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. 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 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

  • sustainable transportation
  • traffic optimization
  • traffic control
  • network management
  • simulation models
  • transportation planning
  • multimodal transportation
  • transport services
  • mobility-as-a-service
  • transport demand
  • passengers’ behaviour
  • ITS
  • automated transport
  • disruption management
  • emergency management
  • crowd management
  • flow control

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

14 pages, 1415 KiB  
Article
Challenges of Track Access Charges Model Redesign
by Branislav Bošković, Mirjana Bugarinović, Gordana Savić and Ratko Djuričić
Sustainability 2021, 13(24), 13512; https://doi.org/10.3390/su132413512 - 7 Dec 2021
Cited by 2 | Viewed by 2679
Abstract
It has been exactly 20 years since the common grounds for the design of track access charges (TAC) were laid for the European railways by the publication of Directive 2001/14/EC. However, these grounds were defined broadly, thus resulting in significant divergence both in [...] Read more.
It has been exactly 20 years since the common grounds for the design of track access charges (TAC) were laid for the European railways by the publication of Directive 2001/14/EC. However, these grounds were defined broadly, thus resulting in significant divergence both in the models applied by countries and during the model redesign within one country over the course of time. The participants in the process of charge system redesign includes all stakeholders from a country’s railway sector (infrastructure manager, train operating companies, the ministries responsible for transport, finance and economy, government, and regulatory bodies). Their opinions and requirements are often opposed, and they all need to be acknowledged simultaneously. This paper aims to solve the issue of ensuring continuity in the charge model redesign while achieving a balance between the requirements of all stakeholders. Moreover, it tackles the issue of producing a sustainable long-term TAC model by using survey methods and statistical analysis. The proposed approach was tested in practice during the access charge model redesign for the railways of Montenegro. The results show the importance of continual enhancement in TAC model development as one of the challenges and key precursors for the harmonization of all stakeholders’ requirements. Full article
(This article belongs to the Special Issue Sustainable Traffic Operations and Mobility Services)
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26 pages, 21779 KiB  
Article
Charging Point Usage in Germany—Automated Retrieval, Analysis, and Usage Types Explained
by Philipp A. Friese, Wibke Michalk, Markus Fischer, Cornelius Hardt and Klaus Bogenberger
Sustainability 2021, 13(23), 13046; https://doi.org/10.3390/su132313046 - 25 Nov 2021
Cited by 9 | Viewed by 3678
Abstract
This study presents an approach to collect and classify usage data of public charging infrastructure in order to predict usage based on socio-demographic data within a city. The approach comprises data acquisition and a two-step machine learning approach, classifying and predicting usage behavior. [...] Read more.
This study presents an approach to collect and classify usage data of public charging infrastructure in order to predict usage based on socio-demographic data within a city. The approach comprises data acquisition and a two-step machine learning approach, classifying and predicting usage behavior. Data is acquired by gathering information on charging points from publicly available sources. The first machine learning step identifies four relevant usage patterns from the gathered data using an agglomerative clustering approach. The second step utilizes a Random Forest Classification to predict usage patterns from socio-demographic factors in a spatial context. This approach allows to predict usage behavior at locations for potential new charging points. Applying the presented approach to Munich, a large city in Germany, results confirm the adaptability in complex urban environments. Visualizing the spatial distribution of the predicted usage patterns shows the prevalence of different patterns throughout the city. The presented approach helps municipalities and charging infrastructure operators to identify areas with certain usage patterns and, hence different technical requirements, to optimize the charging infrastructure in order to help meeting the increasing demand of electric mobility. Full article
(This article belongs to the Special Issue Sustainable Traffic Operations and Mobility Services)
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20 pages, 5644 KiB  
Article
The Effect of Vehicle and Road Conditions on Rollover of Commercial Heavy Vehicles during Cornering: A Simulation Approach
by Nurzaki Ikhsan, Ahmad Saifizul and Rahizar Ramli
Sustainability 2021, 13(11), 6337; https://doi.org/10.3390/su13116337 - 3 Jun 2021
Cited by 18 | Viewed by 6025
Abstract
Heavy vehicles make up a relatively small percentage of traffic volume on Malaysian roads compared to other vehicle types. However, heavy vehicles have been reported to be involved in 30,000–40,000 accidents yearly and caused significantly more fatalities. Rollover accidents may also incur cargo [...] Read more.
Heavy vehicles make up a relatively small percentage of traffic volume on Malaysian roads compared to other vehicle types. However, heavy vehicles have been reported to be involved in 30,000–40,000 accidents yearly and caused significantly more fatalities. Rollover accidents may also incur cargo damages and cause environmental or human disasters for vehicles that carry hazardous cargos if these contents are spilled. Thus, in this paper, a comprehensive study was conducted to investigate the effects of vehicle and road conditions on rollover of commercial heavy vehicles during cornering at curved road sections. Vehicle conditions include the heavy vehicle class (based on the axle number and vehicle type), speed and gross vehicle weight, while road conditions include the cornering radius and coefficient of friction values. In order to reduce the risks involved in usage of actual heavy vehicles in crash experiments, a simulation approach using a multi-body vehicle dynamic software was applied in this study, where the verified virtual heavy vehicle model was simulated and the output results were extracted and analyzed. The results showed that a maximum of 40% and a minimum of 23% from the total number of simulations resulted in an unsafe condition (indicated as failed) during the simulations. From the unsafe conditions, two types of rollover accidents could be identified, which were un-tripped and tripped rollovers. The heavy vehicle speed was also found to have a strong correlation to the lateral acceleration (to cause a rollover), followed by gross vehicle weight, coefficient of friction and cornering radius, respectively. Full article
(This article belongs to the Special Issue Sustainable Traffic Operations and Mobility Services)
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