Parking Spot Research Articles

A Novel Approach for Detecting Vehicles Parked in No Parking Zone Using Image Processing

Abstract: The traffic problem in cities is increasing rapidly. It is associated due to several reasons. The Three Biggest tors causing traffic problems are Distort-ed Urbanization, population growth, and increasing private vehicles. The issue of car parking in urban regions has emerged as a significant concern in both developed and developing nations. The escalating parking costs, heavy traffic flow, and insufficient parking spots are some of the common parking-related problems that people encounter on a daily basis. The only solution to this problem is to search for parking spaces for prolonged periods of time. So, detecting vehicles in no parking area is the solution for this issue. This project works on detecting the number plate using OpenCV. By using image processing, the license number plate is captured and analyzed, and give warning to the driver is to move his/her vehicle to no parking region if they don’t the amount will deduct from his/her account by traffic police. This system is specifically assembled for traffic police.

RFID-Based IoT Scanning System for Tracking Parking Slot Application

The increasing demand for parking spaces in various facilities, such as shopping centers, ports, and airports, poses a significant challenge for parking managers. Drivers waste time and fuel searching for available parking slots, resulting in increased air pollution and negative environmental and health impacts. Therefore, a new solution is needed to address these issues and improve parking management efficiency. A parking management system that utilizes RFID technology and allows for the RFID Tag on each car to display user data, user ID, and parking space reservations is needed to improve the efficiency and convenience of parking at various facilities. The proposed system design incorporates various components, including a Camera Sensor, Raspberry PI, ESP8266, UHF RFID reader, and RFID Tag. The RFID technology captures radio waves emitted by the RFID Tag, enabling individual identification through unique codes. Testing revealed high accuracy at close range but decreased effectiveness at longer distances. Internet speed and network latency affected system performance, with faster speeds enabling faster data transmission. The system, developed using Thunkable and Firebase, provides real-time parking space availability information and streamlines vehicle entry and exit processes through RFID technology. This system has the potential to greatly improve the parking experience at busy public facilities by facilitating efficient parking spot finding and enhancing overall convenience for drivers.

Satellite parking: a new method for measuring parking occupancy

Abstract. Parking management plays a critical role in keeping urban spaces accessible and urban managers strive for an optimal balance between not enough and too much parking. Deciding which parking space can be liberated or needs to be extended requires detailed data on parking occupancy trends. In person inspection and in-situ sensors can provide such data but are too costly for city wide deployment. High-resolution satellite imagery is becoming more affordable, has the advantage of instantaneously collecting information from the whole city, is continuously being updated, and available for several years now to allow building a time series. Yet, identifying cars in satellite imagery is not a trivial task. We propose a method for classifying parking spot occupancy based on thresholding the reflectance range. The method requires individual parking spot data to be available and analyses each parking zone individually. We tested the method on a 0.5 metre resolution image (Pleiades satellite) that was specifically ordered for this purpose during a clear spring day in a medium-size city. The method has the advantage of not requiring extensive training data and is non-parametric. To assess accuracy, we collected ground truth data for the exact same moment as the image was ordered. The colour bands (blue, green, and red) performed equally well, while NIR seriously underperformed. We achieved a F1 score of 0.82 for all parking spots in the ground truth. The method is sensitive to tree canopy. When removing the tree obscured spots, the F1 score increased to 0.85. Tree canopy spots were automatically determined and filtered using NDVI.

Parking Management System

Abstract: This research paper aims to a Parking Management System which is an online platform that enables users to reserve a parking spot in advance. The system works by allowing users to search for available parking spots, view prices, and book their preferred spot using a mobile app or a web interface. The system can be integrated with parking management systems, enabling parking providers to better manage their parking spaces and increase their revenue. Additionally, the system can provide realtime data on parking availability, reducing traffic congestion and improving overall parking efficiency. This abstract provides an overview of the Parking Reservation System and highlights its benefits for both parking providers and users.

Self-Driving Car

Abstract: The evolution of Internet of Things has served up the catalyst in the field of technology. Automobile manufacturers such as Ford, Audi, Hyundai, Tesla, and other companies are investing billions of dollars in autonomous vehicle driving research. According to the new information, in the next 30 years, this fast-developing industry will be worth $ 7 trillion. This will create a shift on the way cities are planned, as less parking spots will be needed, and secondly, in a developed city with most of its vehicles being connected and autonomous, traffic optimization will be able to be strongly applied by coordinating movement of the vehicles..

Car Parking Automation and Premises Security System

Abstract: India is a developing nation. With progress at such a rate, there are cars today at every corner, and parking these cars is a significant issue in the country. Car parking automation is important in today's world for several reasons. Effective use of space, With the growth of urban areas and the increase in the number of vehicles, efficient use of parking spaces has become essential. Also, the demand for personal vehicles is on its high. Automated car parking systems provide convenience to drivers by eliminating the need to search for a parking spot. Drivers can simply drop off their cars at the entrance and the system will take care of the rest. Overall, car parking automation is a must in today's world because it provides an efficient, convenient, and safe parking solution that can help improve the quality of life in urban areas while reducing the environmental impact of driving. To overcome this issue numerous parking systems are available. But the problem with these parking systems is they require more space and are expensive. So, our project is dedicated to developing a fully automatic parking system. The other major problem we are facing today is Inefficient Premises Security Systems. A poor Security System can lead to several problems. If your security system is ineffective, it may be easier for burglars or other criminals to enter your home or business and steal your valuables. This can result in significant financial loss and may also put you and your family or employees at risk. Our Premises Security System keeps your home and your surroundings safe, deters crime and is quite helpful in an emergency. We automated it to make it much more secure and safe which will help us in maintaining the safety of the residences.

Development of Portable Wireless Parking Sensor Device

Parking is regarded as one of the most difficult aspects of driving a vehicle since it is a stressful and confusing situation, even for a competent driver. Therefore, there are many parking sensor devices designed to facilitate the user's search for a parking spot. The ultrasonic sensor was used for the construction of the parking sensor gadget because it is more resistant to environmental conditions than other sensors. This project's objective is to create a portable, wireless parking sensor device by utilizing ultrasonic sensor features in SolidWorks, Proteus, and Arduino. The prototype of the SolidWorks 3D portable wireless parking sensor gadget has to be rigorously tested at parking spaces for vehicles several times in order to depict the actual environment accurately. To facilitate a seamless vehicle detecting procedure, it was necessary that the prototype be strong and durable. After implementing 2 different types of ad-hoc networks, the outcomes showed that the nRF24L01 module normally offers two types of alternatives, either in mesh routed form or Point-to-Point link (PtP). However, the latter is most recommended to gain higher performance and more configurable.

Estimating the Measurement Uncertainty of the Number of Vehicles in a Car Park Using an Indirect Method

The main problem with counting vehicles in rest areas in Europe and America is the overflowing of parking lots in the rest areas. Thus it is impossible to count parked vehicles with traditional, direct methods, which use cameras and Lidar (light detection and ranging) to detect the presence of vehicles in individual parking spots. The solution to this problem may be an indirect method which uses cameras to count the vehicles entering and leaving the rest area and which sorts the vehicles into categories. This article introduces a method for determining car park occupancy in rest areas using indirect measurement and evaluates the uncertainty of this method for determining the occupancy. This indirect method counts the vehicles entering and leaving the car park and sorts the vehicles into categories. The difference between the number of vehicles that entered and the number of vehicles that left in a given time gives the number of vehicles occupying the car park, i.e., the parking space demand for a given time. This demand will vary over time. In order to register the vehicles entering and leaving, mains-free supply video cameras were installed next to the entrance and exit. The counting and categorizing could be conducted organoleptically, semi-automatically, or using an image computer analysis using artificial intelligence networks. Because the difference between the number of vehicles entering and leaving is calculated over a long period, a relative error (regarding car park capacity) might be grave even when the counting errors are minor. The authors will show how the certainty of this indirect counting method can be improved.

A heuristic solution framework for the resource-constrained multi-aircraft scheduling problem with transfer of resources and aircraft

Efficient and feasible flight deck operation scheduling plan is of great significance for improving the sortie rate of carrier aircraft. Oxygen filling, fueling, and other operations of each carrier aircraft are executed in the pre-flight preparation stage. Different personnel, support equipments, and supply resources, are required while different operations are being executed. To date, most approaches proposed in the literature are based on the unrealistic assumption that the transfer process of carrier aircraft can be ignored. To close this gap, the resource-constrained multi-aircraft scheduling problem on the flight deck is examined in this study. The main contributions of the study are as follows. First, by considering the transfer process of aircraft on the flight deck operations, the model formulation of resource-constrained multi-aircraft scheduling problem is established. Second, the parallel and serial scheduling framework are proposed, where parking spot priority rules and resource allocation rules are presented to select the most suitable resources. Third, a modified genetic programming algorithm is presented for obtaining efficient activity priority rules. Fourth, the well-performed scheduling framework, priority rules, and allocation rules are selected by conducting computational experiments. Furthermore, experiment results show that the parallel scheduling framework outperforms the serial framework in most experiments (average outperformance is 10.19%), and the parking spot priority rules slightly affect the serial scheduling framework.

Victimization and Fear in National Parks: That’s My Parking Spot!

ABSTRACT Recently, national parks have experienced record-breaking crowds. However, little is known about victimization, fear, or precautionary behaviors within these spaces. Based on a survey of 1,500 park visitors, the most common forms of victimization were verbal assault and theft. Park visitors experiencing victimization had increased odds of being fearful, considering crime, and staying longer in parks. Similarly, those reporting higher levels of fear of crime were more likely to take safety precautions, consider crime, have experienced victimization in a national park, and spend less time in the park. Policy implications as it relates to crime and national parks are discussed.

Smart Parking System for Institute

As the number of vehicles on roads continues to rise, businesses are more likely to encounter a range of issues. To address such challenges, the "Smart Parking System" has been developed as an intelligent and automatic solution for parking vehicles. This system is designed to alleviate problems faced by urban areas on their roads. However, precisely tracking the availability of parking spots across different locations and times remains a significant difficulty. Nonetheless, the Smart Parking System enables parking attendants to easily locate empty parking spaces. Moreover, implementing this smart parking system can help minimize energy consumption and pollution levels in cities, ultimately contributing toward the country's economic growth.

IoT Based Smart Parking System with Web Application using NodeMCU

Abstract: Parking management has grown to be a significant issue with the rise in vehicle traffic in urban regions. The conventional parking method causes traffic congestion and environmental pollution in addition to being time-consuming. These issues are resolved by the IoT-based smart parking system. It gives drivers and parking administrators access to real-time parking information through sensors and communication networks. To forecast parking availability and maximize parking spot use, the system uses data provided by the IR sensor. Additionally, it provides functions like web booking and payment. By decreasing the amount of time and effort needed to locate a parking space, the smart parking system improves the user experience. Additionally, it aids in lowering fuel consumption, carbon emissions, and traffic congestion, making it an ecologically friendly choice

Autonomous vehicles and street design: Exploring the role of medians in enhancing pedestrian street crossing safety using a virtual reality experiment

As traffic lanes and on-street parking spots can potentially be downsized with the introduction of autonomous vehicles (AVs), the possibility of additional spare road space becoming available arises in future urban streets. While discussions on converting the leftover space into pedestrian-friendly alternatives exist, allocating that limited space to which alternative is foreseen to be another practical issue shared in both urban and transportation planning. However, evidence-based guidance on the issue provided from the actual verification on whether or to what extent the proposed alternatives may have an effect seems to be absent. Therefore, with an emphasis on pedestrian safety, this study focused on the “median strip” alternative as a first example and, through a VR simulation experiment aimed at empirically examining its suggested role on enhancing street crossing safety and further exploring its possible influence on pedestrians’ trust toward autonomous driving. With 99 participants, perceived safety (individual assessments of safety), performance-based safety (crossing success/abandonment and collision occurrence), and trust were either questioned or recorded for nine scenarios with varying crossing conditions. A combination of multilevel models and cross-tabulation results indicate that medians seem especially significant in ensuring the performance-based safety results of pedestrians even when AVs are driving at high speeds or with smaller gaps, thus suggesting it a win–win option for both. Insights and implications on the role and management of medians in future streets are further provided.

Detection of car parking space by using Hybrid Deep DenseNet Optimization algorithm

AbstractInternet of Things (IoT) and related applications have revolutionized most of our societal activities, enhancing the quality of human life. This study presents an IoT‐based model that enables optimized parking space utilization. The paper implements a Hybrid Deep DenseNet Optimization (HDDNO) algorithm for predicting parking spot availability involving Machine Learning (ML) and deep learning techniques. The HDDNO‐based ML model uses secondary data from the National Research Council Park (CNRPark) in Pisa, Italy. Different regression algorithms are employed to forecast parking lot availability for a given time as part of the prediction process. The DenseNet technique has generated promising results, whereas the HDDNO model yielded better accuracy. The use of five optimizers, namely, Adaptive Moment Estimation (Adam), Root Mean Squared Propagation (RMSprop), Adaptive Gradient (AdaGrad), AdaDelta, and Stochastic Gradient Descent (SGD), have played significant roles in minimizing the loss of the model. The part of Adam has enabled the HDDNO model to generate predictions with high accuracy 99.19% and low loss 0.0306%. This proposed methodology would significantly improve environmental safety and act as an initiative toward developing smart cities.

Implementation of Agent Based Smart Parking System using IoT

Due to the increasing number of automobiles on the roads worldwide, parking space problems have arisen in many areas, causing people to spend a considerable amount of time searching for a place to park. This study proposes a smart mobile parking booking system utilizing an agent-based model. The algorithm considers the driver's location, speed, desired destination, preferred parking charge, and arrival time, to determine the most suitable and available parking spot for them. The agent-oriented approach is utilized to represent the system, with each agent responsible for addressing a particular issue

Comprehensive Review of Recent Advancements in Battery Technology, Propulsion, Power Interfaces, and Vehicle Network Systems for Intelligent Autonomous and Connected Electric Vehicles

Numerous recent innovations have been achieved with the goal of enhancing electric vehicles and the parts that go into them, particularly in the areas of managing energy, battery design and optimization, and autonomous driving. This promotes a more effective and sustainable eco-system and helps to build the next generation of electric car technology. This study offers insights into the most recent research and advancements in electric vehicles (EVs), as well as new, innovative, and promising technologies based on scientific data and facts associated with e-mobility from a technological standpoint, which may be achievable by 2030. Appropriate modeling and design strategies, including digital twins with connected Internet of Things (IoT), are discussed in this study. Vehicles with autonomous features have the potential to increase safety on roads, increase driving economy, and provide drivers more time to focus on other duties thanks to the Internet of Things idea. The enabling technology that entails a car moving out of a parking spot, traveling along a long highway, and then parking at the destination is also covered in this article. The development of autonomous vehicles depends on the data obtained for deployment in actual road conditions. There are also research gaps and proposals for autonomous, intelligent vehicles. One of the many social concerns that are described is the cause of an accident with an autonomous car. A smart device that can spot strange driving behavior and prevent accidents is briefly discussed. In addition, all EV-related fields are covered, including the likely technical challenges and knowledge gaps in each one, from in-depth battery material sciences through power electronics and powertrain engineering to market assessments and environmental assessments.

Designing intelligent public parking locations for autonomous vehicles

Looking for parking spaces in crowded areas can be a stressful and time-consuming challenge. With the arrival of technologies like autonomous vehicles (AVs), users can park far away from their destinations. AVs can move from the city center, which has high congestion, into a parking spot outside the area, and thus have more flexibility in choosing the parking location. This study aims to provide a rent bid for the daytime parking of AVs that considers urban land use to evaluate parking strategies possibly chosen by AV users. We determine an actual parking demand function by integrating individual preferences into a p-median problem that controls user optimality. Combining all these together, a novel dynamic optimization formulation is proposed to design the location of parking facilities for AVs that examines the driver's parking preference including rent bid, waiting time for searching parking lots, and travel costs. A Lagrangian relaxation (LR) algorithm is presented to solve the stochastic parking location problem that integrates a reliability strategy to balance demand and supply for parking spaces. The average gap between the exact and the LR solution is about 6% which is very reasonable. We provide a detailed case study of our model with real data generated from daily household travel in New York City. The results show that the average parking price is reduced by 34%, and the average empty trips by AVs decrease by 22% using the proposed public parking strategy.

Modelling and comparing two modes of sharing parking spots at residential area: Real‐time and fixed‐time allocation

AbstractThis research aims to improve the utilization efficiency of parking facilities in residential areas. The real‐time and fixed‐time shared parking spot allocation models based on a time window constraint are proposed, respectively. The real‐time model adopts the dynamic response service mechanism, introducing a multi‐objective decision weighting method to construct the weighted evaluation function. Then, the 0–1 planning model with user optimization is established, utilizing branch‐bound algorithm for a solution. The fixed‐time model adopts the periodic service mechanism, where a rejection penalty factor is introduced to add penalty cost. Then, the 0–1 programming model with system optimization is constructed, where genetic annealing algorithm solves the large‐scale calculation problem. The results from this case study illustrate the fixed‐time allocation mode has more balanced utilization of parking facilities, whereas over‐utilization of preferred parking lots occurs in the real‐time model; additionally, when supply and demand are in balance, the fixed‐time model can obtain higher system revenues, reduce effective rejection rate by 9.43%, and increase resource utilization efficiency by 5.28%. In conclusion, the real‐time allocation mode reflects the advantage of a user's optimal allocation mode when supply is greater than demand; conversely, the fixed‐time allocation mode has the advantage of optimum system resources utilization efficiency.

Parking Spot Occupancy Classification Using Deep Learning

In today’s world, where a car is present in almost every family, the parking problem plays an extremely important role. Parking is one of the most important factors in modern transport infrastructure, because it allows to save the time of both drivers and passengers, to increase the level of comfort and safety of road trips. In Ukraine, this problem is especially relevant, since nowadays it is going through the process of improving its parking infrastructure.The paper examines the problem of parking in large cities, proposes a system for recognizing occupancy of parking spots using computer vision. Such system would use camera feed to track the occupancy of each parking space within a slot. Its benefits would include ease of scalability, saving time of drivers and passengers, automation of parking payment and detection of unpaid parkings. In addition, it makes it possible to easily collect statistics about the busyness of various areas throughout the day or week.The paper also describes the algorithm of classifying the parking spot, as well as a possible architecture that the system may have.Possible problems in training a computer vision model for building the proposed system are considered. Firstly, the available parking datasets are lacking images collected in snow conditions or during nighttime. The hypothesized solution is to use vehicle detection datasets, the number of which that are publicly available is considerably bigger. Another problem is that classification accuracy drops drastically when using different images in train and test dataset. The hypothesized solution here is to apply incremental learning to improve the model as it is being used in a real-life scenario.

Evolutionary algorithm for vehicle routing for shared e-bicycle battery replacement and recycling

Shared electric bicycles (e-bicycles) are becoming an increasingly popular model of sharing economy that provides the public with a convenient and labor-saving transport alternative. Efficient battery replacement is critical to maintain the operational capability of e-bicycles, but is quite difficult as there are often a large number of e-bicycles that are widely dispersed. In this paper, we study a problem of scheduling multiple vehicles to deliver fully-charged batteries to and take back low-power batteries from shared e-bicycles scattered in numerous parking spots, while the low-power batteries are recharged in battery depots for potential re-utilization. The aim of this problem is to minimize the completion time of all battery replacement tasks so as to keep a high operational efficiency of the system. The problem differs from existing vehicle routing problems in two main special features: (1) equivalent exchange of fully-charged batteries and low-power batteries; (2) recycling of batteries. To efficiently solve this special problem, we propose an evolutionary algorithm using variable local-search-based mutation to balance global exploration and local exploitation and employing enhanced local search around each newly found best known solution to improve accuracy. Experiments on test instances and real-world instances demonstrate the competitive performance of the proposed method.