Machine Learning for Sustainable Planning and Modelling in Future Smart Transportation System

A special issue of Future Transportation (ISSN 2673-7590).

Deadline for manuscript submissions: 31 December 2024 | Viewed by 2012

Special Issue Editors


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Guest Editor
Computing and Information Science, Anglia Ruskin University, Cambridge CB11PT, UK
Interests: machine learning; internet of thing; smart transportation; cybersecurity
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Computing and Information Science, Anglia Ruskin University, Cambridge CB11PT, UK
Interests: artificial intelligence and machine learning; Internet of Things (IoT)-based systems; AI in biomedical and environmental sciences
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The transportation sector plays a pivotal role in the economic development of society. The planning and management of this sector are significant to the government as well as different companies. Urbanization and economic development have led to traffic congestion, increased travel time, fuel consumption, as well as the emission of greenhouse gases. Although the growing use of electric vehicles (EVs) has the potential to mitigate some of these problems, wide-scale charging infrastructure is yet to be developed to enable their use. To meet many of these challenges, smart as well as sustainable transportation infrastructure is required to enable the best use of the transportation sector and enable economic growth. The objective of this special issue is to employ machine learning (ML)- and artificial intelligence (AI)-based knowledge to better plan and model future smart transportation systems. The data generated from the wide-scale sensor network in the smart city can be efficiently used for developing several applications for smart transportation. We invite manuscripts including review papers that critically examine how ML and technological innovations can the sustainable smart transportation planning. These topics include but are not limited to: 

  1. Prediction, control, and management of pollutants; 
  2. Electric vehicle routing;
  3. Charging infrastructure development for modern electric vehicles; 
  4. Management of traffic flow and route optimization; 
  5. Management of the traffic congestion and reducing travel time; 
  6. Vehicle-to-grid (V2G), vehicle-to-infrastructure (V2I), and vehicle-to-home (V2H) technologies; 
  7. Integrating renewable energy in the transportation sector; 
  8. Vehicle energy management. 

We look forward to receiving your contributions.

You may choose our Joint Special Issue in Sustainability.

Dr. Raj Mani Shukla
Dr. Lakshmi Babu-Saheer
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. Future Transportation is an international peer-reviewed open access quarterly 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 1000 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

  • smart transportation
  • sustainability
  • artificial intelligence

Published Papers (1 paper)

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Research

16 pages, 2415 KiB  
Article
Development of a Signal-Free Intersection Control System for CAVs and Corridor Level Impact Assessment
by Ardeshir Mirbakhsh, Joyoung Lee and Dejan Besenski
Future Transp. 2023, 3(2), 552-567; https://doi.org/10.3390/futuretransp3020032 - 01 May 2023
Cited by 3 | Viewed by 1423
Abstract
Assuming a full market penetration rate of connected and autonomous vehicles (CAVs) would provide an opportunity to remove costly and inefficient traffic lights from intersections, this paper presents a signal-free intersection control system relying on CAVs’ communicability. This method deploys a deep reinforcement [...] Read more.
Assuming a full market penetration rate of connected and autonomous vehicles (CAVs) would provide an opportunity to remove costly and inefficient traffic lights from intersections, this paper presents a signal-free intersection control system relying on CAVs’ communicability. This method deploys a deep reinforcement learning algorithm and pixel reservation logic to avoid potential collisions and minimize the overall delay at the intersection. To facilitate a traffic-oriented assessment of the model, the proposed model’s application is coupled with VISSIM traffic microsimulation software, and its performance is compared with other intersection control systems, including fixed traffic lights, actuated traffic lights, and the Longest Queue First (LQF) control system. The simulation result revealed that the proposed model reduces delay by 50%, 29%, and 23% in moderate, high, and extreme volume regimes, respectively, compared to another signal-free control system. Noticeable improvements are also gained in travel time, fuel consumption, emission, and Surrogate Safety Measures. Full article
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