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28 pages, 1080 KiB  
Systematic Review
A Literature Review on Strategic, Tactical, and Operational Perspectives in EV Charging Station Planning and Scheduling
by Marzieh Sadat Aarabi, Mohammad Khanahmadi and Anjali Awasthi
World Electr. Veh. J. 2025, 16(7), 404; https://doi.org/10.3390/wevj16070404 - 18 Jul 2025
Viewed by 544
Abstract
Before the onset of global warming concerns, the idea of manufacturing electric vehicles on a large scale was not widely considered. However, electric vehicles offer several advantages that have garnered attention. They are environmentally friendly, with simpler drive systems compared to traditional fossil [...] Read more.
Before the onset of global warming concerns, the idea of manufacturing electric vehicles on a large scale was not widely considered. However, electric vehicles offer several advantages that have garnered attention. They are environmentally friendly, with simpler drive systems compared to traditional fossil fuel vehicles. Additionally, electric vehicles are highly efficient, with an efficiency of around 90%, in contrast to fossil fuel vehicles, which have an efficiency of about 30% to 35%. The higher energy efficiency of electric vehicles contributes to lower operational costs, which, alongside regulatory incentives and shifting consumer preferences, has increased their strategic importance for many vehicle manufacturers. In this paper, we present a thematic literature review on electric vehicles charging station location planning and scheduling. A systematic literature review across various data sources in the area yielded ninety five research papers for the final review. The research results were analyzed thematically, and three key directions were identified, namely charging station deployment and placement, optimal allocation and scheduling of EV parking lots, and V2G and smart charging systems as the top three themes. Each theme was further investigated to identify key topics, ongoing works, and future trends. It has been found that optimization methods followed by simulation and multi-criteria decision-making are most commonly used for EV infrastructure planning. A multistakeholder perspective is often adopted in these decisions to minimize costs and address the range anxiety of users. The future trend is towards the integration of renewable energy in smart grids, uncertainty modeling of user demand, and use of artificial intelligence for service quality improvement. Full article
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23 pages, 13862 KiB  
Article
Towards Sustainable Parking: Analyzing the Characteristics of Periodic Off-Street Parking Lots and Their Application in Shared Parking
by Yifei Cai, Xiao Pan, Lei Zhang, Feifei Xu and Shuichao Zhang
Sustainability 2025, 17(3), 833; https://doi.org/10.3390/su17030833 - 21 Jan 2025
Cited by 1 | Viewed by 1220
Abstract
The pollution and congestion caused by the shortage of parking spaces are threatening the sustainable development of cities. Smart parking platforms are one of the major tools to solve the problem by providing the efficient usage of parking resources. However, current platforms can [...] Read more.
The pollution and congestion caused by the shortage of parking spaces are threatening the sustainable development of cities. Smart parking platforms are one of the major tools to solve the problem by providing the efficient usage of parking resources. However, current platforms can only realize limited functions, and shared parking is far from being implemented on a large scale. Since off-street parking provides the majority of potential shared parking spaces, this paper takes periodic off-street parking lots as the starting point for opening the shared parking market. Based on data from the Ningbo Yongcheng parking platform, power spectral density (PSD) and the autocorrelation function (ACF) are used to identify periodic parking lots. A Density-Based Spatial Clustering of Applications with Noise (DBSCAN)-based method is applied to clustering the occupancy time series. Land use, user type, parking duration, and parking patterns are then analyzed to study shared parking supply characteristics. The results show that (1) 31.3% of off-street parking lots are periodic parking lots, and 90.3% of them have regular users exceeding 50%. (2) Periodic parking lots are classified into four types. Most parking lots show convex flat peak, double peak, or triple peak characteristics. (3) The shared parking spaces demonstrate spatial and temporal imbalances. But in a small area, even considering the concentration of land use and the peak period, there are still enough spaces available. The above research is of significance for the large-scale implementation of shared parking, which can promote the sustainable development of a city. Full article
(This article belongs to the Section Sustainable Transportation)
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20 pages, 12465 KiB  
Article
Three-Dimensional (3D) Flood Simulation Aids Informed Decision Making: A Case of a Two-Story Underground Parking Lot in Beijing
by Walaa Elhamamy, Ruidong Li and Guangheng Ni
Buildings 2024, 14(11), 3435; https://doi.org/10.3390/buildings14113435 - 29 Oct 2024
Viewed by 1334
Abstract
Flooding in underground spaces, such as subway stations, underground malls, and garages, has increased due to intensified rainfall, urbanization, and population growth. Traditional 2D simulations often overlook crucial vertical flow variations, especially in steep transitions like stairs and ramps. The current study aims [...] Read more.
Flooding in underground spaces, such as subway stations, underground malls, and garages, has increased due to intensified rainfall, urbanization, and population growth. Traditional 2D simulations often overlook crucial vertical flow variations, especially in steep transitions like stairs and ramps. The current study aims to investigate the flood dynamics in large underground geometries by taking a parking lot in Beijing, China, as a study case. The model overcomes the limitations of previous simulations by adapting a full 3D mesh-based simulation with reasonable computational cost. Unlike earlier studies, this model employs a high temporal resolution transient inflow at the inlet to the underground space. Simulation scenarios consider different return periods (5, 20, and 100 years) and inlet water depths, providing an analysis of their impact on flood status in the underground structure. The model generates high spatial–temporal results, enabling precise detection of flood-prone locations, evacuation times, and suggested mitigation techniques. The results recommend evacuating from hazard areas before the 10th minute during extreme flood events. Additionally, the study estimates a 40% increase in flood hazards for scenarios with direct connections between levels. Overall, the study highlights the importance of 3D simulations for accurate risk assessment. Full article
(This article belongs to the Section Building Structures)
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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 1801
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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20 pages, 2100 KiB  
Article
Parallel Algorithm on Multicore Processor and Graphics Processing Unit for the Optimization of Electric Vehicle Recharge Scheduling
by Vincent Roberge, Katerina Brooks and Mohammed Tarbouchi
Electronics 2024, 13(9), 1783; https://doi.org/10.3390/electronics13091783 - 5 May 2024
Cited by 1 | Viewed by 2530
Abstract
Electric vehicles (EVs) are becoming more and more popular as they provide significant environmental benefits compared to fossil-fuel vehicles. However, they represent substantial loads on the power grid, and the scheduling of EV charging can be a challenge, especially in large parking lots. [...] Read more.
Electric vehicles (EVs) are becoming more and more popular as they provide significant environmental benefits compared to fossil-fuel vehicles. However, they represent substantial loads on the power grid, and the scheduling of EV charging can be a challenge, especially in large parking lots. This paper presents a metaheuristic-based approach parallelized on multicore processors (CPU) and graphics processing units (GPU) to optimize the scheduling of EV charging in a single smart parking lot. The proposed method uses a particle swarm optimization algorithm that takes as input the arrival time, the departure time, and the power demand of the vehicles and produces an optimized charging schedule for all vehicles in the parking lot, which minimizes the overall charging cost while respecting the chargers’ capacity and the parking lot feeder capacity. The algorithm exploits task-level parallelism for the multicore CPU implementation and data-level parallelism for the GPU implementation. The proposed algorithm is tested in simulation on parking lots containing 20 to 500 EVs. The parallel implementation on CPUs provides a speedup of 7.1x, while the implementation on a GPU provides a speedup of up to 247.6x. The parallel implementation on a GPU is able to optimize the charging schedule for a 20-EV parking lot in 0.87 s and a 500-EV lot in just under 30 s. These runtimes allow for real-time computation when a vehicle arrives at the parking lot or when the electricity cost profile changes. Full article
(This article belongs to the Special Issue Vehicle Technologies for Sustainable Smart Cities and Societies)
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25 pages, 16782 KiB  
Article
Mean Field Game-Based Algorithms for Charging in Solar-Powered Parking Lots and Discharging into Homes a Large Population of Heterogeneous Electric Vehicles
by Samuel M. Muhindo
Energies 2024, 17(9), 2118; https://doi.org/10.3390/en17092118 - 29 Apr 2024
Viewed by 1615
Abstract
An optimal daily scheme is presented to coordinate a large population of heterogeneous battery electric vehicles when charging in daytime work solar-powered parking lots and discharging into homes during evening peak-demand hours. First, we develop a grid-to-vehicle strategy to share the solar energy [...] Read more.
An optimal daily scheme is presented to coordinate a large population of heterogeneous battery electric vehicles when charging in daytime work solar-powered parking lots and discharging into homes during evening peak-demand hours. First, we develop a grid-to-vehicle strategy to share the solar energy available in a parking lot between vehicles where the statistics of their arrival states of charge are dictated by an aggregator. Then, we develop a vehicle-to-grid strategy so that vehicle owners with a satisfactory level of energy in their batteries could help to decongest the grid when they return by providing backup power to their homes at an aggregate level per vehicle based on a duration proposed by an aggregator. Both strategies, with concepts from Mean Field Games, would be implemented to reduce the standard deviation in the states of charge of batteries at the end of charging/discharging vehicles while maintaining some fairness and decentralization criteria. Realistic numerical results, based on deterministic data while considering the physical constraints of vehicle batteries, show, first, in the case of charging in a parking lot, a strong to slight decrease in the standard deviation in the states of charge at the end, respectively, for the sunniest day, an average day, and the cloudiest day; then, in the case of discharging into the grid, over three days, we observe at the end the same strong decrease in the standard deviation in the states of charge. Full article
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24 pages, 14284 KiB  
Article
Mask2Former with Improved Query for Semantic Segmentation in Remote-Sensing Images
by Shichen Guo, Qi Yang, Shiming Xiang, Shuwen Wang and Xuezhi Wang
Mathematics 2024, 12(5), 765; https://doi.org/10.3390/math12050765 - 4 Mar 2024
Cited by 9 | Viewed by 6481
Abstract
Semantic segmentation of remote sensing (RS) images is vital in various practical applications, including urban construction planning, natural disaster monitoring, and land resources investigation. However, RS images are captured by airplanes or satellites at high altitudes and long distances, resulting in ground objects [...] Read more.
Semantic segmentation of remote sensing (RS) images is vital in various practical applications, including urban construction planning, natural disaster monitoring, and land resources investigation. However, RS images are captured by airplanes or satellites at high altitudes and long distances, resulting in ground objects of the same category being scattered in various corners of the image. Moreover, objects of different sizes appear simultaneously in RS images. For example, some objects occupy a large area in urban scenes, while others only have small regions. Technically, the above two universal situations pose significant challenges to the segmentation with a high quality for RS images. Based on these observations, this paper proposes a Mask2Former with an improved query (IQ2Former) for this task. The fundamental motivation behind the IQ2Former is to enhance the capability of the query of Mask2Former by exploiting the characteristics of RS images well. First, we propose the Query Scenario Module (QSM), which aims to learn and group the queries from feature maps, allowing the selection of distinct scenarios such as the urban and rural areas, building clusters, and parking lots. Second, we design the query position module (QPM), which is developed to assign the image position information to each query without increasing the number of parameters, thereby enhancing the model’s sensitivity to small targets in complex scenarios. Finally, we propose the query attention module (QAM), which is constructed to leverage the characteristics of query attention to extract valuable features from the preceding queries. Being positioned between the duplicated transformer decoder layers, QAM ensures the comprehensive utilization of the supervisory information and the exploitation of those fine-grained details. Architecturally, the QSM, QPM, and QAM as well as an end-to-end model are assembled to achieve high-quality semantic segmentation. In comparison to the classical or state-of-the-art models (FCN, PSPNet, DeepLabV3+, OCRNet, UPerNet, MaskFormer, Mask2Former), IQ2Former has demonstrated exceptional performance across three publicly challenging remote-sensing image datasets, 83.59 mIoU on the Vaihingen dataset, 87.89 mIoU on Potsdam dataset, and 56.31 mIoU on LoveDA dataset. Additionally, overall accuracy, ablation experiment, and visualization segmentation results all indicate IQ2Former validity. Full article
(This article belongs to the Special Issue Advanced Research in Data-Centric AI)
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11 pages, 767 KiB  
Article
Perceptions of Personal Lighting Devices and Associated Behaviors: Shifting Personal Norms and Behavior for Broader Conservation Actions
by Morgan Crump, Brendan Derrick Taff, Elizabeth A. Himschoot, Jennifer Newton, Adam Beeco and Peter Newman
Sustainability 2024, 16(5), 1871; https://doi.org/10.3390/su16051871 - 24 Feb 2024
Cited by 1 | Viewed by 1513
Abstract
Anthropogenic light impacts both wildlife and human well-being, and national parks are some of the only remaining large swaths of land where natural dark skies remain. Over the past two decades, a significant amount of science has contributed both to our understanding of [...] Read more.
Anthropogenic light impacts both wildlife and human well-being, and national parks are some of the only remaining large swaths of land where natural dark skies remain. Over the past two decades, a significant amount of science has contributed both to our understanding of these impacts and to engineering advances to reduce negative lighting effects. This has resulted in changes to lighting infrastructure in some national parks, and growth in Dark Sky Certification for many protected areas globally. To date, changing infrastructure, such as street and parking lot lighting, to less intrusive hues and intensities or removing lights altogether have been some of the sustainable changes made in these areas. This study advances our understanding of lighting issues by examining national park visitors’ perceptions of personal lighting use (e.g., headlamps). Specifically, this study explores camper and mountaineer perceptions of personal lighting devices and their impact on social and ecological systems in Grand Teton National Park, USA. During peak visitation in the summer of 2023, 17 mountaineer interviews and 16 general camper interviews took place in the park at night. Results indicate that campers and mountaineers are largely unaware of anthropogenic light impacts on wildlife and humans. However, once informed, they are willing to change their behaviors and reduce the use of personal lighting devices and use more wildlife-friendly lighting with amber or red settings (which, to date, are just emerging and available for general consumers by several companies). These results provide insights for developing educational strategies and personal lighting engineering designs that will ultimately lead to more sustainable normative shifts capable of reducing anthropogenic lighting impacts in parks and beyond. Full article
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14 pages, 828 KiB  
Article
A Quantum-Inspired Ant Colony Optimization Algorithm for Parking Lot Rental to Shared E-Scooter Services
by Antonella Nardin and Fabio D’Andreagiovanni
Algorithms 2024, 17(2), 80; https://doi.org/10.3390/a17020080 - 14 Feb 2024
Cited by 4 | Viewed by 2379
Abstract
Electric scooter sharing mobility services have recently spread in major cities all around the world. However, the bad parking behavior of users has become a major source of issues, provoking accidents and compromising urban decorum of public areas. Reducing wild parking habits can [...] Read more.
Electric scooter sharing mobility services have recently spread in major cities all around the world. However, the bad parking behavior of users has become a major source of issues, provoking accidents and compromising urban decorum of public areas. Reducing wild parking habits can be pursued by setting reserved parking spaces. In this work, we consider the problem faced by a municipality that hosts e-scooter sharing services and must choose which locations in its territory may be rented as reserved parking lots to sharing companies, with the aim of maximizing a return on renting and while taking into account spatial consideration and parking needs of local residents. Since this problem may result difficult to solve even for a state-of-the-art optimization software, we propose a hybrid metaheuristic solution algorithm combining a quantum-inspired ant colony optimization algorithm with an exact large neighborhood search. Results of computational tests considering realistic instances referring to the Italian capital city of Rome show the superior performance of the proposed hybrid metaheuristic. Full article
(This article belongs to the Section Algorithms for Multidisciplinary Applications)
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16 pages, 3117 KiB  
Article
Safety in Public Open Green Spaces in Fortaleza, Brazil: A Data Analysis
by Bárbara Mylena Delgado da Silva, Eszter Karlócainé Bakay and Mariana Batista de Morais
Sustainability 2024, 16(2), 539; https://doi.org/10.3390/su16020539 - 8 Jan 2024
Cited by 3 | Viewed by 3326
Abstract
Latin America is as heterogeneous as its cities. To understand Latin American cities, it is necessary to have a clear vision of how they are organized, not only physically but according to their social, cultural, and economic contexts (which are associated). Historically, it [...] Read more.
Latin America is as heterogeneous as its cities. To understand Latin American cities, it is necessary to have a clear vision of how they are organized, not only physically but according to their social, cultural, and economic contexts (which are associated). Historically, it has suffered a lot in terms of politics and the security of its cities. Insecurity reflects a structural problem; economic and social inequality are the main actors of spatial segregation, motivating violence and, consequently, the insecurity of urban space. Fortaleza is one of the largest Brazilian cities, and it is possible to fit it into this reality. Many public actions may benefit only one sector of society, showing biased investments and, again, confirming the tremendous economic and social differences in Latin American cities. In this study, questionnaires related to attendance, feelings, maintenance, and safety were made to some of Fortaleza’s residents regarding an urban park called Parque do Cocó, one of the biggest in Latin America. Due to its large area, it is located in different city neighborhoods, allowing for us to see the differences in treatments throughout its extension. This article aims to understand how the public opinions and mentality of a portion of the population are characterized concerning safety in green public spaces in the city. In addition, the insecurity of public green spaces can also be inserted into a problem of environmental injustice in the urban context. This study of Fortaleza’s Cocó Park highlights significant disparities in safety perceptions and maintenance across socioeconomic regions. Findings indicate that areas with higher human development index (HDI) scores experience better park conditions. The research underscores the necessity for comprehensive urban policies that address socioeconomic inequalities, as evidenced by the correlation between crime rates and HDI. Cocó Park emerges as a key factor in sustainable urban development, aligning with Fortaleza’s urban planning goals. The study emphasizes the critical role of urban green spaces in enhancing the quality of life and fostering social cohesion in urban landscapes. Moreover, with the data collected, it will be possible to stress further how urban adequacy relates to social situations in Latin American cities. Full article
(This article belongs to the Special Issue Resilient Cultural Landscapes—Methods, Applications and Patterns)
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18 pages, 6495 KiB  
Article
A Smart Real-Time Parking Control and Monitoring System
by Abdelrahman Osman Elfaki, Wassim Messoudi, Anas Bushnag, Shakour Abuzneid and Tareq Alhmiedat
Sensors 2023, 23(24), 9741; https://doi.org/10.3390/s23249741 - 10 Dec 2023
Cited by 29 | Viewed by 25216
Abstract
Smart parking is an artificial intelligence-based solution to solve the challenges of inefficient utilization of parking slots, wasting time, congestion producing high CO2 emission levels, inflexible payment methods, and protecting parked vehicles from theft and vandalism. Nothing is worse than parking congestion [...] Read more.
Smart parking is an artificial intelligence-based solution to solve the challenges of inefficient utilization of parking slots, wasting time, congestion producing high CO2 emission levels, inflexible payment methods, and protecting parked vehicles from theft and vandalism. Nothing is worse than parking congestion caused by drivers looking for open spaces. This is common in large parking lots, underground garages, and multi-story car parks, where visibility is limited and signage can be confusing or difficult to read, so drivers have no idea where available parking spaces are. In this paper, a smart real-time parking management system has been introduced. The developed system can deal with the aforementioned challenges by providing dynamic allocation for parking slots while taking into consideration the overall parking situation, providing a mechanism for booking a specific parking slot by using our Artificial Intelligence (AI)-based application, and providing a mechanism to ensure that the car is parked in its correct place. For the sake of providing cost flexibility, we have provided two technical solutions with cost varying. The first solution is developed based on a motion sensor and the second solution is based on a range-finder sensor. A plate detection and recognition system has been used to detect the vehicle’s license plate by capturing the image using an IoT device. The system will recognize the extracted English alphabet and Hindu-Arabic Numerals. The proposed solution was built and field-tested to prove the applicability of the proposed smart parking solution. We have measured and analyzed keen data such as vehicle plate detection accuracy, vehicle plate recognition accuracy, transmission delay time, and processing delay time. Full article
(This article belongs to the Special Issue Advanced IoT Systems in Smart Cities)
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25 pages, 18022 KiB  
Article
Optimal Electric Vehicle Parking Lot Energy Supply Based on Mixed-Integer Linear Programming
by Damir Jakus, Josip Vasilj and Danijel Jolevski
Energies 2023, 16(23), 7793; https://doi.org/10.3390/en16237793 - 27 Nov 2023
Cited by 2 | Viewed by 1620
Abstract
E-mobility represents an important part of the EU’s green transition and one of the key drivers for reducing CO2 pollution in urban areas. To accelerate the e-mobility sector’s development it is necessary to invest in energy infrastructure and to assure favorable conditions [...] Read more.
E-mobility represents an important part of the EU’s green transition and one of the key drivers for reducing CO2 pollution in urban areas. To accelerate the e-mobility sector’s development it is necessary to invest in energy infrastructure and to assure favorable conditions in terms of competitive electricity prices to make the technology even more attractive. Large peak consumption of parking lots which use different variants of uncoordinated charging strategies increases grid problems and increases electricity supply costs. On the other hand, as observed lately in energy markets, different, mostly uncontrollable, factors can drive electricity prices to extreme levels, making the use of electric vehicles very expensive. In order to reduce exposure to these extreme conditions, it is essential to identify the optimal way to supply parking lots in the long term and to apply an adequate charging strategy that can help to reduce costs for end consumers and bring higher profit for parking lot owners. The significant decline in photovoltaic (PV) and battery storage technology costs makes them an ideal complement for the future supply of parking lots if they are used in an optimal manner in coordination with an adequate charging strategy. This paper addresses the optimal power supply investment problem related to parking lot electricity supply coupled with the application of an optimal EV charging strategy. The proposed optimization model determines optimal investment decisions related to grid supply and contracted peak power, PV plant capacity, battery storage capacity, and operation while optimizing EV charging. The model uses realistic data of EV charging patterns (arrival, departure, energy requirements, etc.) which are derived from commercial platforms. The model is applied using the data and prices from the Croatian market. Full article
(This article belongs to the Special Issue Computational Intelligence in Electrical Systems)
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24 pages, 9608 KiB  
Article
Deploying a Low-Cost Wi-Fi-Based Vehicular Ad Hoc Network in a Shopping Mall Parking Lot: An Empirical Study
by Nurul I. Sarkar, Foysal Ahmed and Sonia Gul
Electronics 2023, 12(22), 4672; https://doi.org/10.3390/electronics12224672 - 16 Nov 2023
Viewed by 1939
Abstract
Vehicular ad hoc networks (VANETs) have the potential to reduce car accidents by facilitating connectivity and warning message exchange between vehicles, both on roads and in parking lots. This research endeavored to accomplish three primary goals: conducting a field measurement in the parking [...] Read more.
Vehicular ad hoc networks (VANETs) have the potential to reduce car accidents by facilitating connectivity and warning message exchange between vehicles, both on roads and in parking lots. This research endeavored to accomplish three primary goals: conducting a field measurement in the parking lot of a large shopping mall in Auckland, developing an OPNET-based simulation model to analyze and validate the system performance, and analyzing the compatibility between five selected radio propagation models (Free-space, Shadowing Path-loss, Egli, Hata, and COST231). These models were selected based on their popularity and relevance to our study. We found that the “Free Space” model outperforms in the scenario in which measurements were conducted from the Level-1 car park to the Roadside. The received signal strengths in the parking lot ranged from −45 dBm to −92 dBm. This research also examines the coverage distance for the successful transmission of warning messages, achieving up to 57 m, 17.5 m, 9.4 m, and 68 m at parking levels 1, 2, 3, and the roadside, respectively. Research findings reveal that a low-cost Wi-Fi-based VANET system can be utilized to prevent car accidents in parking lots. Finally, we provide guidelines for network planners to deploy Wi-Fi-based VANET systems in parking lots. Full article
(This article belongs to the Special Issue Feature Papers in "Networks" Section)
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19 pages, 10551 KiB  
Article
Convolutional Neural Network-Based Approximation of Coverage Path Planning Results for Parking Lots
by Andrius Kriščiūnas, Dalia Čalnerytė, Tautvydas Fyleris, Tadas Jurgutis, Dalius Makackas and Rimantas Barauskas
ISPRS Int. J. Geo-Inf. 2023, 12(8), 313; https://doi.org/10.3390/ijgi12080313 - 30 Jul 2023
Cited by 2 | Viewed by 1696
Abstract
Parking lots have wide variety of shapes because of surrounding environment and the objects inside the parking lot, such as trees, manholes, etc. In the case of paving the parking lot, as much area as possible should be covered by the construction vehicle [...] Read more.
Parking lots have wide variety of shapes because of surrounding environment and the objects inside the parking lot, such as trees, manholes, etc. In the case of paving the parking lot, as much area as possible should be covered by the construction vehicle to reduce the need for manual workforce. Thus, the coverage path planning (CPP) problem is formulated. The CPP of the parking lots is a complex problem with constraints regarding various issues, such as dimensions of the construction vehicle and data processing time and resources. A strategy based on convolutional neural networks (CNNs) for the fast estimation of the CPP’s average track length, standard deviation of track lengths, and number of tracks was suggested in this article. Two datasets of different complexity were generated to analyze the suggested approach. The first case represented a simple case with a working polygon constructed out of several rectangles with applied shear and rotation transformations. The second case represented a complex geometry generated out of rectangles and ellipses, narrow construction area, and obstacles. The results were compared with the linear regression models, with the area of the working polygon as an input. For both generated datasets, the strategy to use an approximator to estimate outcomes led to more accurate results compared to the respective linear regression models. The suggested approach enables us to have rough estimates of a large number of geometries in a short period of time and organize the working process, for example, planning construction time and price, choosing the best decomposition of the working polygon, etc. Full article
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22 pages, 50057 KiB  
Article
Assessment of Walkability of Large Parking Lots on University Campuses Using Walking Infrastructure and User Behavior as an Assessment Method for Promoting Sustainability
by Nawaf Alhajaj
Sustainability 2023, 15(9), 7203; https://doi.org/10.3390/su15097203 - 26 Apr 2023
Cited by 4 | Viewed by 4267
Abstract
Car-dominated university campuses allocate large areas of land for parking lots, which are major hubs for users to start and end their daily walking trips. However, studies on the walkability of large parking lots are limited, and there is a study gap in [...] Read more.
Car-dominated university campuses allocate large areas of land for parking lots, which are major hubs for users to start and end their daily walking trips. However, studies on the walkability of large parking lots are limited, and there is a study gap in the assessment of existing constructed walking infrastructures and their usage and effectiveness in facilitating walking. In this study, a method is developed that can assess both the walking infrastructure and its usage, then applied in five large campus parking lots based on observational strategies. The results indicate that the orientation of a walking path perpendicular to a destination (which provides short-distance walks), availability of proper access to walking paths and designated crossing areas that connect between walking paths, proper implementation of effective traffic calming strategies, and presence of a single entrance and exit for vehicles all play important roles in promoting the use of existing walking infrastructure and creating pedestrian-friendly parking lots. Additionally, this study method extends the walkability assessment of built environments, particularly in large parking lots. This study promotes the creation of sustainable university campuses, thereby enhancing the quality of life of students and staff who use the facilities. Full article
(This article belongs to the Section Sustainable Transportation)
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