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Sustainability
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Research on Sustainable Transportation and Urban Traffic—2nd Edition
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Research on Sustainable Transportation and Urban Traffic—2nd Edition

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

Deadline for manuscript submissions: 27 December 2024 | Viewed by 1613

Special Issue Editors

Dr. Vincenzo Gallelli

E-Mail Website
Guest Editor
Department of Civil Engineering, University of Calabria, Arcavacata Campus, 87036 Rende, Italy
Interests: transportation modeling; sustainable mobility; transportation planning; ITS mobility management; traffic simulation; road pavement surface performances; sustainable road materials; road safety; traffic microsimulation; surrogate safety indicators; road geometric design and performance analysis of roundabouts
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Rosolino Vaiana

E-Mail Website
Guest Editor
Department of Civil Engineering, University of Calabria, Arcavacata Campus, 87036 Rende, Italy
Interests: road pavement surface performances; bituminous materials; recycled and sustainable road materials; sustainable mobility; road safety and driver behavior; traffic microsimulation; geometric design and performance analysis of roundabouts; surrogate safety indicators
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The role of transport in sustainable development is fundamental to enhancing economic growth and improving accessibility. Sustainable transport achieves better integration of the economy while respecting the environment and improving social equity, health, and resilience of cities. There is an urgent need for transformative action that will accelerate the transition to sustainable transport, especially in urban areas. More evident effects of climate change are driving us to find innovative transport solutions, especially in urban areas. This difficult situation has amplified the centrality of transport in sustainable development, emphasizing existing challenges and creating new ones. Scientific advances and the rapid development of new technologies are essential for the transition to sustainable transport: environmentally friendly fuels and engines, artificial intelligence technology, big data analysis, autonomous vehicles, and intelligent transport systems have become central features of the transport innovation landscape.

Therefore, the aim of this Special Issue is to focus attention on new challenges for sustainable transportation and urban traffic, focusing on how to use intelligent transport systems, big data analysis technology and, IoT applications to improve transportation systems, especially in urban areas.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • IoT sensing, applications, and technologies for smart sustainable cities;
  • Use of new devices to evaluate traffic congestion, traffic emission, and improvement traffic sustainability;
  • Intelligent transport systems for urban smart mobility;
  • New forms of innovative public transport;
  • New traffic calming systems to improve the safety of vulnerable road users in urban areas;
  • Pedestrians and cyclists influence on traffic flow parameters and road safety;
  • Infrastructure-based sensor networks for urban road/traffic monitoring;
  • Big data applications to sustainable transport and transportation planning;
  • Artificial intelligence systems to assist traffic control network managers in planning, monitoring, and managing;
  • Systems to improve the level of vulnerability of urban intersections.

We look forward to receiving your contributions.

Dr. Vincenzo Gallelli
Prof. Dr. Rosolino Vaiana
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 road transport
  • traffic flow modeling
  • smart cities
  • smart roads
  • innovative public transport solutions
  • transportation
  • intelligent transportation systems
  • fuel consumption and emissions
  • safety of vulnerable road users
  • urban intersection

Published Papers (2 papers)

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Research

23 pages, 2551 KiB  
Article
Optimal Placement of Sensors in Traffic Networks Using Global Search Optimization Techniques Oriented towards Traffic Flow Estimation and Pollutant Emission Evaluation
by Gianfranco Gagliardi, Vincenzo Gallelli, Antonio Violi, Marco Lupia and Gianni Cario
Sustainability 2024, 16(9), 3530; https://doi.org/10.3390/su16093530 - 23 Apr 2024
Viewed by 371
Abstract
The relationship between estimating traffic flow and evaluating pollutant emissions lies in understanding how vehicular traffic patterns affect air quality. Traffic flow estimation is a complex field that involves a variety of analytical techniques to understand, predict, and manage the flow of vehicles [...] Read more.
The relationship between estimating traffic flow and evaluating pollutant emissions lies in understanding how vehicular traffic patterns affect air quality. Traffic flow estimation is a complex field that involves a variety of analytical techniques to understand, predict, and manage the flow of vehicles on road networks. Different types of analyses commonly employed in this area are statistical analysis (e.g., descriptive statistics, inferential statistics, time series analysis), mathematical modeling (macroscopic models, microscopic models, mesoscopic models), computational methods (e.g., simulation modeling, machine learning, and AI techniques), geospatial analysis (e.g., geographic information systems (GISs), spatial data analysis), network analysis (e.g., graph theory and network flow models). In sensor network setups, the strategic placement of sensors is crucial, primarily due to the challenges posed by limited energy supplies, restricted storage capabilities, and the demands on processing and communication, all of which significantly impact maintenance costs and hardware limitations. To mitigate the burden on processing and communication, it is essential to deploy a limited number of sensors strategically. In practical applications, achieving an optimal layout of physical sensors (i.e., placing sensors within the network in such a way as to meet a specific optimality criterion, such as identifying the minimum number of sensors required to ensure the ability to design reliable state observers capable of reconstructing the network’s state based on the available data) is essential for the accurate monitoring of large-scale systems, including traffic flow or the distribution networks of water and gas. In the context of traffic systems, addressing the challenge of full link flow observability, that is, the ability to accurately monitor and assess the flow of entities (i.e., vehicles) across all the links or pathways within a network, entails selecting the smallest number of traffic sensors from a larger set to install. The goal is to choose a subset of p sensors, which may include redundancies, from a pool of n>>p potential sensors. This is conducted to maintain the structural observability of the entire traffic network. This concept pertains to deducing the complete internal state (traffic volume on each road link in the network) from external outputs and inputs (measurements from sensors). The traditional concept of system observability serves as a criterion for sensor placement. This article presents the development of a simulated annealing heuristic to address the selection problem. The selected sensors are then applied to construct a Luenberger observer, a mathematical construct used in control theory to accurately estimate the internal state of a dynamic system based on its inputs and outputs. Numerical simulations are carried out to demonstrate the effectiveness of this method, and a performance analysis using a digital twin of a transport network, designed using the Aimsun Next software, are also carried out to assess traffic flow and associated pollutant emissions. In particular, we examine a traffic network comprising 21 roads. We address the sensor selection problem by identifying an optimal set of six sensors, which facilitates the design of a Luenberger observer. This observer enables the reconstruction of traffic flow across the network with minimal estimation error. Furthermore, by integrating this observer with data from the Aimsun Next software, we assess the pollutant emissions related to traffic flow. The results indicate a high accuracy in estimating pollutant levels. Full article
(This article belongs to the Special Issue Research on Sustainable Transportation and Urban Traffic—2nd Edition)
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17 pages, 2586 KiB  
Article
Understanding the Determinants of Lane Inefficiency at Fully Actuated Intersections: An Empirical Analysis
by Nihat Can Karabulut, Murat Ozen and Oruc Altintasi
Sustainability 2024, 16(2), 722; https://doi.org/10.3390/su16020722 - 14 Jan 2024
Viewed by 855
Abstract
As urban traffic challenges intensify, the growing interest for fully actuated control systems in intersection management is on the rise due to their capacity to adapt to dynamic traffic demands. These systems play a crucial role in sustainable traffic solutions, significantly reducing delays [...] Read more.
As urban traffic challenges intensify, the growing interest for fully actuated control systems in intersection management is on the rise due to their capacity to adapt to dynamic traffic demands. These systems play a crucial role in sustainable traffic solutions, significantly reducing delays and emissions and enhancing overall system efficiency. The optimal performance of these systems relies on effectively facilitating vehicle discharge at the saturation flow rate throughout the green period. This study introduces a new parameter, lane inefficiency, evaluating vehicle discharge effectiveness by comparing saturation flow rate with instantaneous discharge for each green period. It provides a comprehensive assessment of green utilization for specific lanes. This study also explores the impact of signal control system parameters and traffic flow characteristics on lane inefficiency using principal component analysis (PCA) and multiple linear regression models. This approach holistically evaluates how both signal control system and traffic flow parameters collectively influence efficient green period utilization. The findings emphasize the impact of critical factors on lane inefficiency, including green time, the proportion of total unused green time to green time, total unused green time, the percentage of heavy vehicles in departing traffic, the ratio of effective green time to cycle time, the total time headways of the first four vehicles, and queue length. Decision makers need to pay due attention to these parameters to enhance intersection performance and foster a more sustainable urban transportation network. Full article
(This article belongs to the Special Issue Research on Sustainable Transportation and Urban Traffic—2nd Edition)
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