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Fuzzy Logic Applications in Traffic and Transportation Engineering
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Fuzzy Logic Applications in Traffic and Transportation Engineering

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Fuzzy Sets, Systems and Decision Making".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 15446

Special Issue Editors

Prof. Dr. Momcilo Dobrodolac

E-Mail Website
Guest Editor
Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, 11000 Belgrade, Serbia
Interests: postal services; transportation science; decision making; optimization algorithms; fuzzy logic
Dr. Stefan Jovcic

E-Mail Website
Guest Editor
Faculty of Transport Engineering, University of Pardubice, Studentská 95, 532 10 Pardubice, Czech Republic
Interests: multi-criteria decision-making; fuzzy logic; operational research; management in logistics; postal traffic; city logistics; last-mile delivery
Dr. Marjana Čubranić-Dobrodolac

E-Mail Website
Guest Editor
Faculty of Transport and Traffic Engineering, University of Belgrade, Vojvode Stepe 305, 11000 Belgrade, Serbia
Interests: traffic psychology and behavior; fuzzy logic; ergonomics; perception; organizational behavior

Special Issue Information

Dear Colleagues,

Traffic and transportation engineering involves the application of scientific principles to the planning, design, and operation of facilities for any mode of transportation and human resource management in industry required to enable the safe, efficient, economical, and environmentally compatible movement of people and goods. Having in mind the complexity of the processes at work in transportation engineering, fuzzy logic is a convenient tool for their modeling. Fuzzy logic is based on reasoning which is approximate rather than precise, which provides various possibilities for application in the transportation field, a domain characterized by constant transformations that often lead to uncertainty and imprecision. A particular advantage of fuzzy systems is the possibility to include multiple goals in calculations and, by adequate optimization algorithms, to reach a high similarity to real-world phenomena. This Special Issue is devoted to examples of fuzzy logic implementation to solve various traffic and transportation engineering problems, in all modes of transportation—road, rail, air, and waterborne transport, the postal and logistics industries, as well as telecommunications.

Prof. Dr. Momcilo Dobrodolac
Dr. Stefan Jovcic
Dr. Marjana Čubranić-Dobrodolac
Guest Editors

Manuscript Submission Information

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Keywords

  • fuzzy applications
  • fuzzy decision making
  • fuzzy and meta-heuristic optimization
  • time series forecasting
  • fuzzy system applications in human–machine interfaces
  • behavior modeling of participants and employees in transportation
  • vehicles
  • machines
  • robots
  • traffic safety
  • road transport
  • rail transport
  • air transport
  • waterborne transport
  • postal traffic
  • logistics
  • telecommunications

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Published Papers (10 papers)

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21 pages, 3467 KiB  
Article
Location and Size Planning of Charging Parking Lots Based on EV Charging Demand Prediction and Fuzzy Bi-Objective Optimization
by Qiong Bao, Minghao Gao, Jianming Chen and Xu Tan
Mathematics 2024, 12(19), 3143; https://doi.org/10.3390/math12193143 - 8 Oct 2024
Viewed by 1017
Abstract
The market share of electric vehicles (EVs) is growing rapidly. However, given the huge demand for parking and charging of electric vehicles, supporting facilities generally have problems such as insufficient quantity, low utilization efficiency, and mismatch between supply and demand. In this study, [...] Read more.
The market share of electric vehicles (EVs) is growing rapidly. However, given the huge demand for parking and charging of electric vehicles, supporting facilities generally have problems such as insufficient quantity, low utilization efficiency, and mismatch between supply and demand. In this study, based on the actual EV operation data, we propose a driver travel-charging demand prediction method and a fuzzy bi-objective optimization method for location and size planning of charging parking lots (CPLs) based on existing parking facilities, aiming to reduce the charging waiting time of EV users while ensuring the maximal profit of CPL operators. First, the Monte Carlo method is used to construct a driver travel-charging behavior chain and a user spatiotemporal activity transfer model. Then, a user charging decision-making method based on fuzzy logic inference is proposed, which uses the fuzzy membership degree of influencing factors to calculate the charging probability of users at each road node. The travel and charging behavior of large-scale users are then simulated to predict the spatiotemporal distribution of charging demand. Finally, taking the predicted charging demand distribution as an input and the number of CPLs and charging parking spaces as constraints, a bi-objective optimization model for simultaneous location and size planning of CPLs is constructed, and solved using the fuzzy genetic algorithm. The results from a case study indicate that the planning scheme generated from the proposed methods not only reduces the travelling and waiting time of EV users for charging in most of the time, but also controls the upper limit of the number of charging piles to save construction costs and increase the total profit. The research results can provide theoretical support and decision-making reference for the planning of electric vehicle charging facilities and the intelligent management of charging parking lots. Full article
(This article belongs to the Special Issue Fuzzy Logic Applications in Traffic and Transportation Engineering)
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21 pages, 6413 KiB  
Article
An Efficient Tour Construction Heuristic for Generating the Candidate Set of the Traveling Salesman Problem with Large Sizes
by Boldizsár Tüű-Szabó, Péter Földesi and László T. Kóczy
Mathematics 2024, 12(19), 2960; https://doi.org/10.3390/math12192960 - 24 Sep 2024
Viewed by 673
Abstract
In this paper, we address the challenge of creating candidate sets for large-scale Traveling Salesman Problem (TSP) instances, where choosing a subset of edges is crucial for efficiency. Traditional methods for improving tours, such as local searches and heuristics, depend greatly on the [...] Read more.
In this paper, we address the challenge of creating candidate sets for large-scale Traveling Salesman Problem (TSP) instances, where choosing a subset of edges is crucial for efficiency. Traditional methods for improving tours, such as local searches and heuristics, depend greatly on the quality of these candidate sets but often struggle in large-scale situations due to insufficient edge coverage or high time complexity. We present a new heuristic based on fuzzy clustering, designed to produce high-quality candidate sets with nearly linear time complexity. Thoroughly tested on benchmark instances, including VLSI and Euclidean types with up to 316,000 nodes, our method consistently outperforms traditional and current leading techniques for large TSPs. Our heuristic’s tours encompass nearly all edges of optimal or best-known solutions, and its candidate sets are significantly smaller than those produced with the POPMUSIC heuristic. This results in faster execution of subsequent improvement methods, such as Helsgaun’s Lin–Kernighan heuristic and evolutionary algorithms. This substantial enhancement in computation time and solution quality establishes our method as a promising approach for effectively solving large-scale TSP instances. Full article
(This article belongs to the Special Issue Fuzzy Logic Applications in Traffic and Transportation Engineering)
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17 pages, 1507 KiB  
Article
Risk Analysis of the Use of Drones in City Logistics
by Snežana Tadić, Mladen Krstić, Miloš Veljović, Olja Čokorilo and Milica Milovanović
Mathematics 2024, 12(8), 1250; https://doi.org/10.3390/math12081250 - 20 Apr 2024
Cited by 2 | Viewed by 1295
Abstract
Drone delivery in city logistics is gaining attention due to road congestion, environmental threats, etc. However, there are risks associated with using drones which can result in hazardous events, such as conflicts in the air, loss of control, and system failures. It is [...] Read more.
Drone delivery in city logistics is gaining attention due to road congestion, environmental threats, etc. However, there are risks associated with using drones which can result in hazardous events, such as conflicts in the air, loss of control, and system failures. It is crucial to assess the risks involved in using different types of drones and choose the option with the lowest risk. The existence of different criteria important for this decision imposes the need to apply the multi-criteria decision-making (MCDM) method(s). This paper proposes a new hybrid model that combines the fuzzy Factor Relationship (FARE) method for obtaining the criteria weights and the Axial Distance-based Aggregated Measurement (ADAM) method for obtaining the final ranking of the alternatives. A single-rotor microdrone weighing up to 4.4 lb was chosen as the optimal solution, and after that, the most favorable are also the drones of this size (multi-rotor and fixed-wing microdrones). The establishment of a novel hybrid MCDM model, the identified risks, the set of criteria for evaluating the least risky drones, and the framework for prioritizing the drones are the main novelties and contributions of the paper. Full article
(This article belongs to the Special Issue Fuzzy Logic Applications in Traffic and Transportation Engineering)
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19 pages, 4979 KiB  
Article
Transferability of Multi-Objective Neuro-Fuzzy Motion Controllers: Towards Cautious and Courageous Motion Behaviors in Rugged Terrains
by Adham Salih, Joseph Gabbay and Amiram Moshaiov
Mathematics 2024, 12(7), 992; https://doi.org/10.3390/math12070992 - 27 Mar 2024
Viewed by 737
Abstract
This study is motivated by the need to develop generic neuro-fuzzy motion controllers for autonomous vehicles that may traverse rugged terrains. Three types of target problems are investigated. These problems differ in terms of the expected motion behavior, including cautious, intermediate, and courageous [...] Read more.
This study is motivated by the need to develop generic neuro-fuzzy motion controllers for autonomous vehicles that may traverse rugged terrains. Three types of target problems are investigated. These problems differ in terms of the expected motion behavior, including cautious, intermediate, and courageous behaviors. The target problems are defined as evolutionary multi-objective problems aiming to evolve near optimal neuro-fuzzy controllers that can operate in a variety of scenarios. To enhance the evolution, sequential transfer optimization is considered, where each of the source problems is defined and solved as a bi-objective problem. The performed experimental study demonstrates the ability of the proposed search approach to find neuro-fuzzy controllers that produce the required motion behaviors when operating in various environments with different motion difficulties. Moreover, the results of this study substantiate the hypothesis that solutions with performances near the edges of the obtained approximated bi-objective Pareto fronts of the source problems provide better transferability as compared with those that are associated with performances near the center of the obtained fronts. Full article
(This article belongs to the Special Issue Fuzzy Logic Applications in Traffic and Transportation Engineering)
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20 pages, 2673 KiB  
Article
A Novel Data-Envelopment Analysis Interval-Valued Fuzzy-Rough-Number Multi-Criteria Decision-Making (DEA-IFRN MCDM) Model for Determining the Efficiency of Road Sections Based on Headway Analysis
by Dejan Andjelković, Gordan Stojić, Nikola Nikolić, Dillip Kumar Das, Marko Subotić and Željko Stević
Mathematics 2024, 12(7), 976; https://doi.org/10.3390/math12070976 - 25 Mar 2024
Cited by 2 | Viewed by 970
Abstract
The capacity of transport infrastructure is one of the very important tasks in transport engineering, which depends mostly on the geometric characteristics of road and headway analysis. In this paper, we have considered 14 road sections and determined their efficiency based on headway [...] Read more.
The capacity of transport infrastructure is one of the very important tasks in transport engineering, which depends mostly on the geometric characteristics of road and headway analysis. In this paper, we have considered 14 road sections and determined their efficiency based on headway analysis. We have developed a novel interval fuzzy-rough-number decision-making model consisting of DEA (data envelopment analysis), IFRN SWARA (interval-valued fuzzy-rough-number stepwise weight-assessment-ratio analysis), and IFRN WASPAS (interval-valued fuzzy-rough-number weighted-aggregate sum–product assessment) methods. The main contribution of this study is a new extension of WASPAS method with interval fuzzy rough numbers. Firstly, the DEA model was applied to determine the efficiency of 14 road sections according to seven input–output parameters. Seven out of the fourteen alternatives showed full efficiency and were implemented further in the model. After that, the IFRN SWARA method was used for the calculation of the final weights, while IFRN WASPAS was applied for ranking seven of the road sections. The results show that two sections are very similar and have almost equal efficiency, while the other results are very stable. According to the results obtained, the best-ranked is a measuring segment of the Ivanjska–Šargovac section, with a road gradient = −5.5%, which has low deviating values of headways according to the measurement classes from PC-PC to AT-PC, which shows balanced and continuous traffic flow. Finally, verification tests such as changing the criteria weights, comparative analysis, changing the λ parameter, and reverse rank analysis have been performed. Full article
(This article belongs to the Special Issue Fuzzy Logic Applications in Traffic and Transportation Engineering)
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21 pages, 1073 KiB  
Article
Analysing the Hidden Relationship between Long-Distance Transport and Information and Communication Technology Use through a Fuzzy Clustering Eco-Extended Apostle Model
by Panayotis Christidis, Juan Carlos Martín and Concepción Román
Mathematics 2024, 12(6), 791; https://doi.org/10.3390/math12060791 - 7 Mar 2024
Viewed by 1020
Abstract
The study analyses the hidden relationship between transport and ICT use for an extensive sample of 26,500 EU citizens. To that aim, a fuzzy clustering Eco-extended apostle model is applied to both latent variables: interurban transport trips and ICT use. The interurban long-distance [...] Read more.
The study analyses the hidden relationship between transport and ICT use for an extensive sample of 26,500 EU citizens. To that aim, a fuzzy clustering Eco-extended apostle model is applied to both latent variables: interurban transport trips and ICT use. The interurban long-distance trip (LDT) latent variable is measured by four different indicators (long- and medium-distance trips for work and leisure in the past twelve months), and the ICT use is based on a ten-item scale that provides information on different transport modes. The fuzzy Eco-extended apostle model is compared with the classical apostle model, translating the satisfaction and loyalty dimensions to our case. The fuzzy clustering model shows that most EU citizens are similar to the representative citizen who moved and used ICT at very low rates (56.5 and 50.4 per cent, respectively). The classical apostle model shows that the quadrants low LDT–high ICT and low LDT–low ICT are more represented by 38.5 and 35.2 per cent, respectively. However, the Eco-extended apostle model reinforces the results of the quadrant of low LDT–low ICT (40.22%) but softens those obtained in the quadrant of low LDT–high ICT (21.01%). Interesting insights of the effects of gender, age, education, and employment status are discussed. Full article
(This article belongs to the Special Issue Fuzzy Logic Applications in Traffic and Transportation Engineering)
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22 pages, 4582 KiB  
Article
Strategic Warehouse Location Selection in Business Logistics: A Novel Approach Using IMF SWARA–MARCOS—A Case Study of a Serbian Logistics Service Provider
by Vukašin Pajić, Milan Andrejić, Marijana Jolović and Milorad Kilibarda
Mathematics 2024, 12(5), 776; https://doi.org/10.3390/math12050776 - 5 Mar 2024
Cited by 5 | Viewed by 3998
Abstract
Business logistics encompasses the intricate planning, seamless implementation, and precise control of the efficient and effective movement and storage of goods, services, and associated information from their origin to their final consumption point. The strategic placement of facilities is intricately intertwined with business [...] Read more.
Business logistics encompasses the intricate planning, seamless implementation, and precise control of the efficient and effective movement and storage of goods, services, and associated information from their origin to their final consumption point. The strategic placement of facilities is intricately intertwined with business logistics, exerting a direct influence on the efficiency and cost-effectiveness of supply chain operations. In the realm of business logistics, decisions regarding the location of facilities, including warehouses, distribution centers, and manufacturing plants, assume a pivotal role in shaping the overarching logistics strategy. Warehouses, serving as pivotal nodes in the supply chain network, establish crucial links at both local and global markets. They serve as the nexus connecting suppliers and customers across the entire supply chain, thus constituting indispensable elements that significantly impact the overall performance of the supply chain. The optimal location of warehouses is paramount for efficient supply chains, ensuring minimized costs and bigger profits. The decision on warehouse location exerts a profound influence on investment costs, operational expenses, and the distribution strategy of a company, thereby playing a substantial role in elevating customer service levels. Hence, the primary objective of this paper is to propose a novel methodology grounded in the application of the Improved Fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA)-Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) methods for determining warehouse locations tailored to a logistics service provider (LSP) operating in the Serbian market. Through the definition of seven evaluation criteria based on a comprehensive literature review and expert insights, this study aims to assess five potential locations. The findings suggest that the proposed model offers great decision support for effectively addressing challenges akin to the one presented in this study. Full article
(This article belongs to the Special Issue Fuzzy Logic Applications in Traffic and Transportation Engineering)
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20 pages, 4580 KiB  
Article
Fuzzy Logic Model for Assessing Accident Proneness Based on Passenger Vehicle Speed in Real and Virtual Traffic Conditions
by Nenad Marković, Tijana Ivanišević, Svetlana Čičević and Aleksandar Trifunović
Mathematics 2024, 12(3), 421; https://doi.org/10.3390/math12030421 - 28 Jan 2024
Viewed by 1301
Abstract
Inappropriate or unsafe speed is one of the main factors that affects the number of road crashes as well as the severity of the consequences. Research shows that speed is an influential factor in the occurrence of road crashes in more than 30% [...] Read more.
Inappropriate or unsafe speed is one of the main factors that affects the number of road crashes as well as the severity of the consequences. Research shows that speed is an influential factor in the occurrence of road crashes in more than 30% of road crashes with fatal outcomes and in over 12% of all road crashes. With an increase in speed, the risk of road crashes increases as well as the severity of the consequences. The perception of the vehicle speed in the traffic lane is one of the basic prerequisites for the safe functioning of traffic, that is, for the successful and timely interaction of all road users. Therefore, the challenge of this paper is to examine how the assessment of the speed of a passenger vehicle in different environments affects the prediction of the respondent’s participation in road crashes. Bearing the above in mind, an experimental study was carried out, in real traffic conditions (RTC) as well as in a virtual environment using a driving simulator (DS), at different passenger vehicle speeds (30, 50 and 70 km/h), and at different perspectives of observing the oncoming vehicle (observing the vehicle from the front, from the back, from the side and from the driver’s seat) by the respondents. The respondents had the task of evaluating the passenger vehicle speed, in all tested conditions and at all tested speeds. Standard statistical models and fuzzy logic were used to analyze the obtained results. The results show statistically significant differences for all tested situations and all tested speeds as well as statistically significant differences depending on the gender of the respondents, the driver’s license category, the driver’s experience, frequency of driving and depending on whether respondents wear glasses. Bearing in mind the results of the developed model, by applying fuzzy logic, it can be concluded that the proposed model can be used to assess the propensity of respondents to participate in road crashes, based on perception of vehicle speeds in two tested environments. Full article
(This article belongs to the Special Issue Fuzzy Logic Applications in Traffic and Transportation Engineering)
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26 pages, 6167 KiB  
Article
Using an Interval Type-2 Fuzzy AROMAN Decision-Making Method to Improve the Sustainability of the Postal Network in Rural Areas
by Ivana Nikolić, Jelena Milutinović, Darko Božanić and Momčilo Dobrodolac
Mathematics 2023, 11(14), 3105; https://doi.org/10.3390/math11143105 - 13 Jul 2023
Cited by 11 | Viewed by 1351
Abstract
One of the crucial pillars of each state’s development strategy relates to service provision in rural areas. An adequate scope of these services is a prerequisite for uniform regional progress. Postal operators play a key role in supporting these development policies, by providing [...] Read more.
One of the crucial pillars of each state’s development strategy relates to service provision in rural areas. An adequate scope of these services is a prerequisite for uniform regional progress. Postal operators play a key role in supporting these development policies, by providing postal, financial and transportation services to each citizen in a state, regardless of place of residence. The postal network represents one of the biggest logistics networks worldwide. However, since it is not financially justified to provide services to all citizens, even to those that live in the most remote areas, the question of how to optimize the postal network is always topical. This problem is very complex because the postal units’ existence in rural areas cannot be considered just from an economic standpoint; many other criteria should be considered. The model proposed in this paper can be considered a decision-making tool designed to support policymakers in planning the postal network. First, we identify the criteria that should be considered in decision-making by an extensive literature review. We then apply the FUCOM method to determine the importance of individual criteria. Finally, we propose an Interval Type-2 Fuzzy AROMAN approach to determine which postal unit should be reorganized. Full article
(This article belongs to the Special Issue Fuzzy Logic Applications in Traffic and Transportation Engineering)
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24 pages, 1901 KiB  
Article
A Decision-Making Model for Professional Drivers Selection: A Hybridized Fuzzy–AROMAN–Fuller Approach
by Marjana Čubranić-Dobrodolac, Stefan Jovčić, Sara Bošković and Darko Babić
Mathematics 2023, 11(13), 2831; https://doi.org/10.3390/math11132831 - 24 Jun 2023
Cited by 9 | Viewed by 1730
Abstract
Professional drivers play a crucial role in many businesses and the lives of people. They are responsible for transferring people and goods between distant points, enabling safe and efficient flows. The road traffic death rate is from 8.3 to 27.5 per 100,000 inhabitants [...] Read more.
Professional drivers play a crucial role in many businesses and the lives of people. They are responsible for transferring people and goods between distant points, enabling safe and efficient flows. The road traffic death rate is from 8.3 to 27.5 per 100,000 inhabitants in the countries globally. Because professional drivers spend a significant amount of time on the road, their appropriate selection may contribute to general traffic safety. In addition, an adequate selection of candidates significantly impacts the financial costs of the employing company. However, the recruitment procedure is a very complex task where multiple criteria should be considered. By its nature, this is a typical multi-criteria decision-making problem. The purpose of this paper is twofold: to contribute to the methodological, as well as to the professional field. Considering the professional, we propose a decision-making tool in the procedure of professional driver selection. There are several methodological contributions. By reviewing the literature, we identified 14 criteria for candidate selection. In the proposed model, by using expert opinion and implementing DEMATEL and Fuller’s pairwise comparisons, we ranked these criteria and determined the seven most important for further calculation procedure. Here, we introduced an original approach for measuring the reliability of obtained answers. Then, to rank the candidates, the fuzzy AROMAN approach is applied for the first time in the literature. The input data were obtained in the form of a survey, where the experts evaluated the importance of criteria and their interrelation. We used MS Excel and MATLAB for data processing. An additional methodological contribution of this study is an advancement of the AROMAN method by the proposal of an algorithm for the calculation of parameter λ used in the final ranking formula. To illustrate the applicability of the proposed model, a case study is provided. Based on the results, we can conclude that the new methodological approaches can be successfully used in the procedure of professional driver selection, as well as in solving other multi-criteria decision-making problems. Full article
(This article belongs to the Special Issue Fuzzy Logic Applications in Traffic and Transportation Engineering)
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