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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "G1: Smart Cities and Urban Management".

Deadline for manuscript submissions: closed (5 March 2025) | Viewed by 9235

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Dr. Marcin Kłos

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Department of Transport Systems, Traffic Engineering and Logistics, Faculty of Transport and Aviation Engineering, Silesian University of Technology, Krasińskiego 8 Street, 40-019 Katowice, Poland
Interests: civil engineering; GIS analysis; sustainable transport; mobility; QGIS; transportation; urban planning; travel behavior; traffic safety; transport planning and safety management
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Prof. Dr. Grzegorz Sierpiński

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Department Transport Systems, Traffic Engineering and Logistics, Faculty of Transport and Aviation Engineering, Silesian University of Technology, Krasińskiego Str. 8, 40-019 Katowice, Poland
Interests: sustainable transport; electromobility; travel behavior; environmentally friendly transport solutions; traffic engineering; traffic flow measurement; analysis and prognosis; transport systems modeling; optimization of transport networks
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Special Issue Information

Dear Colleagues,

This Special Issue of Energies, “Optimization of Intelligent Transport Systems Planning Energy Efficiency and Environmental Responsibility,” will consist of manuscripts describing problems and challenges for transport systems.

The modern approach to city planning generates new expectations for mobility. The geographic space is a kind of limited resource. Currently, dynamical changes in land-use are being observed. During that process, administrative units do not always prepare land-use planning while considering sustainable development. Vehicle numbers are increasing, as are the number of trips being made. This results from changes in people’s lifestyles, the habits created, and the increased convenience associated with personal transport. This development of individual transport, which contributes to the deterioration of road conditions (congestion), is harming the environment due to air and noise pollution and energy consumption and is causing the deterioration of residents’ health (due to increased use of personal transport).

To plan a modern transport system, it is necessary to plan it for citizens and design it around environmental friendliness and high accessibility. Transport systems should make optimal use of the available resources. Cities have limited space to build new roads and railways. The answer to the problem identified is the introduction of sustainable planning. One approach could be intelligent transport systems (supporting the development of public transport by prioritizing them). It is essential to take a holistic approach to the area to increase journeys made by public transport or eco-friendly mobility.

We invite all scientists and practitioners to submit articles related to modern solutions used for transport system planning. Ensuring the appropriate quality of its functioning is a big challenge facing smart cities. It requires a multicriteria approach, taking into account the principles of sustainable development. We hope that this Special Issue of Energies will be an opportunity to present the research results and exchange experiences.

Both original research and review works are welcome for submission. Research topics of interest include, but are not limited to, models and methods concerning:

Public transport optimization;
Introduction of electro-mobility infrastructure;
Spatial planning of electro-mobility infrastructure;
Transport development;
Sustainable mobility shaping and planning;
Information technologies in a public transport system;
Planning of intelligent transport systems;
Transit-oriented development strategies in urban areas;
Energy networks in smart cities;
Conventional, hybrid and electric drive systems;
Various communication environment and innovative new mobility service;
Safety in transport systems;
Autonomous vehicles and their impact for transport system;
The implementation of the MaaS integrating public transport systems.

Dr. Marcin Kłos
Dr. Grzegorz Sierpiński
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. Energies 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 2600 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
transport systems
energy efficiency
spatial analysis
environmental responsibility
public transport
sustainable urban mobility
sustainable development
smart city
spatio-temporal analysis
urban planning

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Related Special Issue

The Role of Sustainable Transport Development in Urban Areas: Energy Efficiency and Infrastructure Optimization in Energies

Published Papers (8 papers)

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Research

30 pages, 4993 KiB

Open AccessArticle

Deep Learning vs. Gradient Boosting: Optimizing Transport Energy Forecasts in Thailand Through LSTM and XGBoost

by Thanapong Champahom, Chinnakrit Banyong, Thananya Janhuaton, Chamroeun Se, Fareeda Watcharamaisakul, Vatanavongs Ratanavaraha and Sajjakaj Jomnonkwao

Energies 2025, 18(7), 1685; https://doi.org/10.3390/en18071685 - 27 Mar 2025

Viewed by 448

Abstract

Thailand’s transport sector faces critical challenges in energy management amid rapid economic growth, with transport accounting for approximately 30% of total energy consumption. This study addresses research gaps in transport energy forecasting by comparing Long Short-Term Memory (LSTM) neural networks and XGBoost models for predicting transport energy consumption in Thailand. Utilizing a comprehensive dataset spanning 1993–2022 that includes vehicle registration data by size category, vehicle kilometers traveled, and macroeconomic indicators, this research evaluates both modeling approaches through multiple performance metrics. The results demonstrate that XGBoost consistently outperforms LSTM, achieving an R-squared value of 0.9508 for test data compared to LSTM’s 0.2005. Feature importance analysis reveals that medium vehicles contribute 36.6% to energy consumption predictions, followed by truck VKT (20.5%), with economic and demographic factors accounting for a combined 15.2%. This research contributes to both methodological understanding and practical application by establishing XGBoost’s superior performance for transport energy forecasting, quantifying the differential impact of various vehicle categories on energy consumption, and demonstrating the value of integrating vehicle registration and usage data in predictive models. The findings provide evidence-based guidance for prioritizing policy interventions in Thailand’s transport sector to enhance energy efficiency and sustainability. Full article

(This article belongs to the Special Issue Optimization of Intelligent Transport Systems Planning Energy Efficiency and Environmental Responsibility)

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48 pages, 5009 KiB

Open AccessArticle

Combined Rough Sets and Rule-Based Expert System to Support Environmentally Oriented Sandwich Pallet Loading Problem

by Piotr Sawicki, Hanna Sawicka, Marek Karkula and Krzysztof Zajda

Energies 2025, 18(2), 268; https://doi.org/10.3390/en18020268 - 9 Jan 2025

Viewed by 784

Abstract

A sandwich pallet loading problem represents a significant challenge in the logistics of fast-moving consumer goods (FMCG), requiring optimisation of load units (LUs) arrangements to minimise their number in transportation and warehousing processes, leading to an environmental responsibility of organisations. This study introduces an innovative approach combining Dominance-Based Rough Set Theory (DRST) with a rule-based expert system to improve the efficiency of the pallet loading and to provide sustainable development. Key criteria and attributes for the LU assessment, such as weight, height, and fragility, are defined. DRST is utilised to classify these units, leveraging its capability to handle imprecise and vague information. The rule-based system ensures an optimal arrangement of LUs by considering critical control parameters, thereby reducing LU numbers and mitigating the environmental impact of logistics operations, as measured by energy consumption. The proposed approach is validated using real-world data from the FMCG distribution company. Results demonstrate that integrating DRST with an expert system improves decision-making consistency and significantly reduces the number of LUs. This study shows a way to increase the level of environmental responsibility of the organisation by cutting energy consumption and delivering economic and social benefits through fewer shipments. For example, the approach reduces energy consumption for a customer order delivery by 40%, from 0.60 to 0.36 (kWh/pskm). Full article

(This article belongs to the Special Issue Optimization of Intelligent Transport Systems Planning Energy Efficiency and Environmental Responsibility)

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11 pages, 10508 KiB

Open AccessArticle

The Impact of Mechanical Failure of 18650 Batteries on the Safety of Electric Transport Operations

by Henryk Bąkowski, Iga Przytuła, Wioletta Cebulska, Damian Hadryś and Janusz Ćwiek

Energies 2024, 17(23), 5980; https://doi.org/10.3390/en17235980 - 28 Nov 2024

Viewed by 1230

Abstract

The safety of 18650 lithium-ion batteries is critical for the reliability and durability of electric vehicles, especially as interest in sustainable transportation grows. Battery failures, such as fires or explosions, pose significant risks to both users and manufacturers, highlighting the need for advanced power systems. This study used finite element method (FEM) simulations and crash tests to evaluate battery safety in accident scenarios. The results showed that mechanical damage, especially from collisions, can cause internal short circuits, increasing the risk of thermal runaway, especially when combined with high temperatures during normal operation or charging. This can be caused by mechanical damage to the battery causing a change in the distance inside the battery, causing it to short circuit. The results highlight the importance of designing battery systems that prevent internal short circuits, especially under extreme conditions, and the need for continuous monitoring of battery parameters to detect early signs of failure. In the context of improving battery safety, the battery not only saves lives, but also extends vehicle life, reduces electronic waste, and increases energy efficiency, which is consistent with global efforts to minimize the environmental impact of technology and promote safer transportation. Full article

(This article belongs to the Special Issue Optimization of Intelligent Transport Systems Planning Energy Efficiency and Environmental Responsibility)

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15 pages, 7847 KiB

Open AccessFeature PaperArticle

High-Capacity Energy Storage Devices Designed for Use in Railway Applications

by Krystian Woźniak, Beata Kurc, Łukasz Rymaniak, Natalia Szymlet, Piotr Pielecha and Jakub Sobczak

Energies 2024, 17(23), 5904; https://doi.org/10.3390/en17235904 - 25 Nov 2024

Viewed by 753

Abstract

This paper investigates the application of high-capacity supercapacitors in railway systems, with a particular focus on their role in energy recovery during braking processes. The study highlights the potential for significant energy savings by capturing and storing energy generated through electrodynamic braking. Experimental measurements conducted on a diesel–electric multiple unit revealed that approximately 28.3% to 30.5% of the energy could be recovered from the traction network, regardless of the type of drive used—whether electric or diesel. This research also explores the integration of starch-based carbon as an electrode material in supercapacitors, offering an innovative, sustainable alternative to traditional graphite or graphene electrodes. The carbon material was obtained through a simple carbonization process, with experimental results demonstrating a material capacity of approximately 130 F/g. To quantify the energy recovery, calculations were made regarding the mass and power requirements of the supercapacitors. For the tested vehicle, it was estimated that around 28.7% of the energy could be recovered during the braking process. To store 15 kWh of energy, the total mass of the capacitors required is approximately 245.1 kg. The study emphasizes the importance of increasing voltage levels in railway systems, which can enhance energy transmission and utilization efficiency. Additionally, the paper discusses the necessity of controlled energy discharge, allowing for the flexible management of energy release to meet the varying power demands of trains. By integrating high-voltage supercapacitors and advanced materials like starch-based carbon, this research paves the way for more sustainable and efficient railway systems, contributing to the industry’s goals of reducing emissions and improving operational performance. The findings underscore the crucial role of these capacitors in modernizing railway infrastructure and promoting environmentally responsible transportation solutions. Full article

(This article belongs to the Special Issue Optimization of Intelligent Transport Systems Planning Energy Efficiency and Environmental Responsibility)

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21 pages, 4525 KiB

Open AccessArticle

The Attractiveness of Regional Transport as a Direction for Improving Transport Energy Efficiency

by Wojciech Miechowicz, Marcin Kiciński, Izabela Miechowicz and Agnieszka Merkisz-Guranowska

Energies 2024, 17(19), 4844; https://doi.org/10.3390/en17194844 - 27 Sep 2024

Viewed by 968

Abstract

One of the ways to improve energy efficiency in transportation is through efforts aimed at increasing the usage of public transportation by residents. This, in turn, is closely related to residents’ preferences. One of the most frequently cited factors influencing the attractiveness and quality of public transportation is the frequency of connections. This is important not only for urban transport but also regional transport, which has significantly lower passenger flows. This paper aims to present how the frequency of connections affects the attractiveness of regional transport. An original method for determining the attractiveness of public transport, based on the share of adult, senior, and youth passengers with single tickets and monthly passes, is introduced. The results of research on the structure of passengers and flows to/from the district center are presented. Based on the research results, attractiveness factors are calculated for each town. The statistical analysis clearly indicates there is a strong correlation between the attractiveness of regional transport and the frequency of connections (Rs = 0.807, p = 0.001). Moreover, for every connection increase, the number of adult passengers will increase by an average of 1.5. Assuming that these additional passengers switch from individual to public transportation, the resulting reduction in energy consumption due to an increase of one connection is 0.33–0.69 kWh for each kilometer traveled by these passengers. Full article

(This article belongs to the Special Issue Optimization of Intelligent Transport Systems Planning Energy Efficiency and Environmental Responsibility)

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26 pages, 4748 KiB

Open AccessArticle

Reliable Energy Optimization Strategy for Fuel Cell Hybrid Electric Vehicles Considering Fuel Cell and Battery Health

by Cong Ji, Elkhatib Kamal and Reza Ghorbani

Energies 2024, 17(18), 4686; https://doi.org/10.3390/en17184686 - 20 Sep 2024

Cited by 2 | Viewed by 1848

Abstract

To enhance the fuel efficiency of fuel cell hybrid electric vehicles (FCHEVs), we propose a hierarchical energy management strategy (HEMS) to efficiently allocate power to a hybrid system comprising a fuel cell and a battery. Firstly, the upper-layer supervisor employs a fuzzy fault-tolerant control and prediction strategy for the battery and fuel cell management system, ensuring vehicle stability and maintaining a healthy state of charge for both the battery and fuel cell, even during faults. Secondly, in the lower layer, dynamic programming and Pontryagin’s minimum principle are utilized to distribute the necessary power between the fuel cell system and the battery. This layer also incorporates an optimized proportional-integral controller for precise tracking of vehicle subsystem set-points. Finally, we compare the economic and dynamic performance of the vehicle using HEMS with other strategies, such as the equivalent consumption minimization strategy and fuzzy logic control strategy. Simulation results demonstrate that HEMS reduces hydrogen consumption and enhances overall vehicle energy efficiency across all operating conditions, indicating superior economic performance. Additionally, the dynamic performance of the vehicle shows significant improvement. Full article

(This article belongs to the Special Issue Optimization of Intelligent Transport Systems Planning Energy Efficiency and Environmental Responsibility)

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26 pages, 11909 KiB

Open AccessArticle

The Influence of Stops on the Selected Route of the City ITS on the Energy Efficiency of the Public Bus

by Miroslaw Smieszek, Vasyl Mateichyk and Jakub Mosciszewski

Energies 2024, 17(16), 4179; https://doi.org/10.3390/en17164179 - 22 Aug 2024

Cited by 1 | Viewed by 911

Abstract

Public transport is an important part of sustainable economic development, sustainable cities, and communities. Reducing energy consumption in public transport can be achieved through better organisation of the transport system, changes in infrastructure, the use of new energy-efficient means of transport, and other ways to achieve intelligent mobility. The operation of a city bus involves frequent stops. These stops are due to the need to exchange passengers at bus stops and traffic conditions. Each stop and the subsequent acceleration process require additional energy consumption. In this paper, an analysis of bus operation within the Rzeszów ITS on a selected route is carried out to determine the energy consumption in these special modes. First, the number and duration of stops were determined based on data recorded during the bus operation using the tracker. Then, taking into account the idle fuel consumption and the energy consumption required to reach a set speed, the total energy consumption associated with the stops was determined. The results obtained on the selected route indicate a significant share of energy associated with stops at bus stops and outside bus stops in total fuel consumption. These shares are about 26.2% and about 42.5%, respectively. The opportunity to improve the energy efficiency of the city bus on the route due to the reduction of stops at bus stops by introducing on-demand stops as one of the elements of ITS has been evaluated. The number of stops related to traffic conditions can be reduced by further improving traffic management and measures to modify urban infrastructure. Full article

(This article belongs to the Special Issue Optimization of Intelligent Transport Systems Planning Energy Efficiency and Environmental Responsibility)

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20 pages, 5623 KiB

Open AccessArticle

Manifold Learning in Electric Power System Transient Stability Analysis

by Petar Sarajcev and Dino Lovric

Energies 2023, 16(23), 7810; https://doi.org/10.3390/en16237810 - 27 Nov 2023

Viewed by 1166

Abstract

This paper examines the use of manifold learning in the context of electric power system transient stability analysis. Since wide-area monitoring systems (WAMSs) introduced a big data paradigm into the power system operation, manifold learning can be seen as a means of condensing these high-dimensional data into an appropriate low-dimensional representation (i.e., embedding) which preserves as much information as possible. In this paper, we consider several embedding methods (principal component analysis (PCA) and its variants, singular value decomposition, isomap and spectral embedding, locally linear embedding (LLE) and its variants, multidimensional scaling (MDS), and others) and apply them to the dataset derived from the IEEE New England 39-bus power system transient simulations. We found that PCA with a radial basis function kernel is well suited to this type of power system data (where features are instances of three-phase phasor values). We also found that the LLE (including its variants) did not produce a good embedding with this particular kind of data. Furthermore, we found that a support vector machine, trained on top of the embedding produced by several different methods was able to detect power system disturbances from WAMS data. Full article

(This article belongs to the Special Issue Optimization of Intelligent Transport Systems Planning Energy Efficiency and Environmental Responsibility)

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