Special Issue "Advances in Public Transport Platform for the Development of Sustainability Cities"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 30 November 2020.

Special Issue Editors

Prof. Dr. Juan M. Corchado
Website
Guest Editor
IoT European Digital Innovation Hub, Full Professor at the University of Salamanca, Visiting Professor at the Osaka Institute of Technology, Visiting Professor at the Universiti Malaysia Kelantan, President of the IEEE SMC (Spanish Chapter), Director of BISITE - Bioinformatics Intelligent Systems and Educational, Technology Research Group, Salamanca, Spain
Interests: artificial intelligence; machine learning; edge computing; distributed computing; blockchain; consensus model; smart cities; smart grid
Special Issues and Collections in MDPI journals
Dr. Josep L. Larriba-Pey
Website
Guest Editor
Data Maagement Group, Polytechnic University of Catalonia, Spain
Interests: computer science; decision sciences; social sciences; chemical engineering
Dr. Pablo Chamoso
Website SciProfiles
Guest Editor
1. Department of Computing and Automation, Faculty of Sciences, University of Salamanca. Calle Espejo sn (Edificio Multiusos I+D+i), 37007, Salamanca, Spain.
2. BISITE Research Group, University of Salamanca. Calle Espejo sn (Edificio Multiusos I+D+i), 37007, Salamanca, Spain.
3. IoT Digital Innovation Hub, Edificio Parque Científico Módulo 305, Paseo de Belén 11 Campus Miguel Delibes 47011 Valladolid (Spain).
Interests: Machine Learning, Internet of Things, Distributed Systems, Software Applications
Special Issues and Collections in MDPI journals
Prof. Dr. Fernando De la Prieta
Website
Guest Editor
BISITE Research Group, University of Salamanca. Calle Espejo sn, 24.2. 37007 Salamanca, Spain
Interests: artificial intelligence; multiagent systems; cloud computing and distributed systems; technology enhanced
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Modern societies demand a high and varied mobility, which in turn requires a complex transport system adapted to social needs that guarantees the movement of people and goods in an economically efficient and safe way, but all subject to a new environmental rationality and the new logic of the paradigm of sustainability. From this perspective, an efficient and flexible transport system that provides intelligent and sustainable mobility patterns is essential to our economy and our quality of life. The current transport system poses growing and significant challenges for the environment, human health, and sustainability, while current mobility schemes have focused much more on the private vehicle that has conditioned both the lifestyles of citizens and cities, as well as urban and territorial sustainability. 

Transport has a very considerable weight in the framework of sustainable development due to environmental pressures, associated social and economic effects, and interrelations with other sectors. The continuous growth that this sector has experienced over the last few years and its foreseeable increase, even considering the change of trend due to the current situation of generalized crisis, make the challenge of sustainable transport a strategic priority at local, national, European, and global levels. 

This Special Issue will pay attention to all those research approaches focused on the relationship between evolution in the area of transport with a high incidence in the environment from the perspective of efficiency, which has become one of the neuralgic centers of sustainability. It is about producing, consuming, and moving people and goods better, with fewer resources and less environmental impact. 

The topics of interest for this issue include but are not limited to: 

•    Public transport;

•    Traffic management;

•    Smart cities;

•    Location-based systems;

•    Expert systems;

•    Routing algorithms;

•    Recommender systems;

•    Path planning and path finding;

•    Users’ profile analysis;

•    Distributed systems and platforms;

•    Smart city modeling and simulation;

•    Smart mobility and transportation;

•    Intelligent vehicles;

•    Smart traffic system operations;

•    Smart integrated grids;

•    Intelligent infrastructure;

•    Sensors and actuators;

•    Data visualization;

•    Cybersecurity;

•    Blockchain.

Prof. Dr. Juan Manuel Corchado Rodríguez
Dr. Josep L. Larriba-Pey
Dr. Pablo Chamoso Santos
Dr. Fernando De la Prieta Pintado
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. Electronics is an international peer-reviewed open access monthly 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 1500 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

  • Traffic management
  • Smart cities
  • Recommender systems
  • Intelligent infrastructure

Published Papers (3 papers)

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Research

Open AccessFeature PaperArticle
Exploratory Data Analysis and Data Envelopment Analysis of Urban Rail Transit
Electronics 2020, 9(8), 1270; https://doi.org/10.3390/electronics9081270 - 07 Aug 2020
Abstract
This paper deals with the efficiency and sustainability of urban rail transit (URT) using exploratory data analytics (EDA) and data envelopment analysis (DEA). The first stage of the proposed methodology is EDA with already available indicators (e.g., the number of stations and passengers), [...] Read more.
This paper deals with the efficiency and sustainability of urban rail transit (URT) using exploratory data analytics (EDA) and data envelopment analysis (DEA). The first stage of the proposed methodology is EDA with already available indicators (e.g., the number of stations and passengers), and suggested indicators (e.g., weekly frequencies, link occupancy rates, and CO2 footprint per journey) to directly characterize the efficiency and sustainability of this transport mode. The second stage is to assess the efficiency of URT with two original models, based on a thorough selection of input and output variables, which is one of the key contributions of EDA to this methodology. The first model compares URT against other urban transport modes, applicable to route personalization, and the second scores the efficiency of URT lines. The main outcome of this paper is the proposed methodology, which has been experimentally validated using open data from the Transport for London (TfL) URT network and additional sources. Full article
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Open AccessFeature PaperArticle
A Generic Data-Driven Recommendation System for Large-Scale Regular and Ride-Hailing Taxi Services
Electronics 2020, 9(4), 648; https://doi.org/10.3390/electronics9040648 - 15 Apr 2020
Cited by 3
Abstract
Modern taxi services are usually classified into two major categories: traditional taxicabs and ride-hailing services. For both services, it is required to design highly efficient recommendation systems to satisfy passengers’ quality of experience and drivers’ benefits. Customers desire to minimize their waiting time [...] Read more.
Modern taxi services are usually classified into two major categories: traditional taxicabs and ride-hailing services. For both services, it is required to design highly efficient recommendation systems to satisfy passengers’ quality of experience and drivers’ benefits. Customers desire to minimize their waiting time before rides, while drivers aim to speed up their customer hunting. In this paper, we propose to leverage taxi service efficiency by designing a generic and smart recommendation system that exploits the benefits of Vehicular Social Networks (VSNs). Aiming at optimizing three key performance metrics, number of pick-ups, customer waiting time, and vacant traveled distance for both taxi services, the proposed recommendation system starts by efficiently estimating the future customer demands in different clusters of the area of interest. Then, it proposes an optimal taxi-to-region matching according to the location of each taxi and the future requested demand of each region. Finally, an optimized geo-routing algorithm is developed to minimize the navigation time spent by drivers. Our simulation model is applied to the borough of Manhattan and is validated with realistic data. Selected results show that significant performance gains are achieved thanks to the additional cooperation among taxi drivers enabled by VSN, as compared to traditional cases. Full article
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Open AccessArticle
Optimization of Public Transport Services to Minimize Passengers’ Waiting Times and Maximize Vehicles’ Occupancy Ratios
Electronics 2020, 9(2), 360; https://doi.org/10.3390/electronics9020360 - 20 Feb 2020
Cited by 1
Abstract
Determining the best timetable for vehicles in a public transportation (PT) network is a complex problem, especially because it is just necessary to consider the requirements and satisfaction of passengers as the requirements of transportation companies. In this paper, a model of the [...] Read more.
Determining the best timetable for vehicles in a public transportation (PT) network is a complex problem, especially because it is just necessary to consider the requirements and satisfaction of passengers as the requirements of transportation companies. In this paper, a model of the PT timetabling problem which takes into consideration the passenger waiting time (PWT) at a station and the vehicle occupancy ratio (VOR) is proposed. The solution aims to minimize PWT and maximize VOR. Due to the large search space of the problem, we use a multiobjective particle swarm optimization (MOPSO) algorithm to arrive at the solution of the problem. The results of the proposed method are compared with similar results from the existing literature. Full article
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