Intelligent Parking Management System Research Articles

Research and Design of Intelligent Parking Management System based on the YOLO Algorithm

Given the difficulty in managing parking lots and inefficient utilization of parking spaces at university and college campuses, this paper designs an intelligent campus parking management system with functions such as license plate recognition (LPR), online parking space reservations, campus parking navigation, and mobile app payment through the parking space detection technology based on You Only Look Once (YOLO) algorithm, Internet of Things (IoT) technology, and cloud platform technology. This system obtains information relating to license plates, parking spaces, etc. from sensing nodes with the IoT technology and transmits the collected information through NB-IoT technology to a cloud platform for storage and management to facilitate information exchange between hardware and software. This paper describes the architecture of the intelligent parking management system, parking space detection technology based on the YOLOv4 algorithm, and hardware and software design of the system. The paper proposes an effective solution to parking problems facing colleges and universities. The paper concludes that the intelligent campus parking management system based on the YOLOv4 algorithm can prevent the haphazard parking of vehicles and traffic congestion at open campuses and therefore has important value for application and popularization.

Intelligent Parking Management System by Multi-Agent Approach: The Case of Urban Area of Tunis

Intelligent Parking Management System by Multi-Agent Approach: The Case of Urban Area of Tunis

Optimized real-time parking management framework using deep learning

Today’s modern world has seen massive population growth in the past few decades, causing the automobile industry to expand rapidly. The exponential increase has disrupted the seamless flow of traffic globally and has fashioned significant problems such as traffic congestion and its mismanagement. To tackle these issues, some hardware and data-driven-based solutions have been previously proposed. The hardware-based solutions utilize different types of sensors installed at relevant sites to monitor the status of parking slots which makes them less scalable, complex, costly to install and maintain. In contrast, the data-driven solutions utilize the already available infrastructure of surveillance cameras installed at parking lots, thus overcoming the limitations of sensor-based solutions. However, currently only classification-based approaches are prevalent and adopted to monitor the status of the parking slots which makes the systems less generalized for scalability with slower performance. This paper proposes an intelligent parking management system which employs deep learning to alleviate the limitations in the data driven solutions by leveraging the high performance and fast inference capability of YOLO v5 for vehicles detection instead of parking slot classification. The model was evaluated using the PKLot dataset which is a benchmark for identifying the status of the parking lot with state of the art performance achieved having an accuracy of 99.5%. To augment the performance of the algorithm in real-time, a pretrained model of YOLO v5 on MS COCO dataset was employed to detect and assign vacant parking slots and generate vehicle statistics. The performance of the proposed system was evaluated on our custom dataset with an accuracy of 96.8% achieved and a nearly real-time performance of 45 Fps which makes it more efficient, scalable, and generalized.

Design of a reinforcement learning-based intelligent car transfer planning system for parking lots.

In this study, a car transfer planning system for parking lots was designed based on reinforcement learning. The car transfer planning system for parking lots is an intelligent parking management system that is designed by using reinforcement learning techniques. The system features autonomous decision-making, intelligent path planning and efficient resource utilization. And the problem is solved by constructing a Markov decision process and using a dynamic planning-based reinforcement learning algorithm. The system has the advantage of looking to the future and using reinforcement learning to maximize its expected returns. And this is in contrast to manual transfer planning which relies on traditional thinking. In the context of this paper on parking lots, the states of the two locations form a finite set. The system ultimately seeks to find a strategy that is beneficial to the long-term development of the operation. It aims to prioritize strategies that have positive impacts in the future, rather than those that are focused solely on short-term benefits. To evaluate strategies, as its basis the system relies on the expected return of a state from now to the future. This approach allows for a more comprehensive assessment of the potential outcomes and ensures the selection of strategies that align with long-term goals. Experimental results show that the system has high performance and robustness in the area of car transfer planning for parking lots. By using reinforcement learning techniques, parking lot management systems can make autonomous decisions and plan optimal paths to achieve efficient resource utilization and reduce parking time.

Design of Intelligent Parking Management System Based on ARM and Wireless Sensor Network

Motor vehicles are changing the way people live, but they are also putting a huge strain on urban traffic. In the majority of major cities, parking has become the number one problem for car owners to get around. The management efficiency of car parks directly affects the traffic of the whole city. In order to improve the management efficiency of the car park, this paper designs an intelligent parking management system based on ARM and ZigBee wireless sensor network. Firstly, according to the internal environment and economic cost of the car park, ultrasonic sensors are used to monitor whether the parking space is empty or not. The information collected by the ultrasonic sensors is transmitted to the ARM host controller through the ZigBee wireless sensor network, and the ARM host controller determines whether there are free parking spaces based on the collected information. Secondly, Faster R-CNN, a deep learning algorithm, is selected as the license plate recognition model, and the Faster R-CNNN is improved by the residual module. Finally, in order to extend the lifetime of the ZigBee wireless network, the ZigBee routing algorithm is investigated, and an improved routing algorithm based on energy averaging is proposed. The effectiveness of the improved routing algorithm is demonstrated by a simulation analysis through NS2. The test results show that the designed intelligent parking management system is able to complete the functions of parking space detection and license plate recognition normally, thus effectively improving the efficiency of the car park and providing great convenience to motorists.

An intelligent parking management system using RFID technology based on user preferences

An intelligent parking management system using RFID technology based on user preferences

Detection of vacant slots in parking area through machine learning techniques using optimized ensemble classification model

Due to insufficiency of parking space, people face many problems in finding a vacant slot to park their vehicles in the parking area. This problem is giving rise to many other problems such as traffic congestion, wastage of fuel, money and time. Therefore, there is a need to develop an intelligent parking management system for better utilization of the resources. The main objective of the paper is to design an efficient parking system to search for the vacant slots in the parking area. In this paper, experiments have been conducted on standard dataset “PKLot” which consists of 695,899 images of two different parking lots. These images were captured from three different camera views under different climatic conditions like rainy, sunny and cloudy. Various machine learning (ML) techniques like Artificial Neural Network (ANN), K-Nearest Neighbor (KNN), Naïve Bayes Classifier (NBC) and Support Vector Machine (SVM) with different parameters have been applied on the dataset. Further, an ensemble model for classification of occupied and vacant slots in the parking area has been developed which improves the performance of the system as compared with other state-of-the-art systems.

Cloud Intelligent Parking Management System Based on Internet of Things Technology

In recent years, with the rapid development of the national economy, the penetration rate of domestic private cars has risen rapidly. There are too many cars with fewer parking spaces, so many people choose to park their cars on roads. It has caused traffic jams and brought security risks, finally it puts a huge pressure on vehicle management. It requires more parking lots and more effective and convenient parking management and operation methods to improve the service level of parking lots [6]. It is necessary to design an intelligent parking system based on the Internet of Things technology and cloud platform to achieve the highest utilization of space resources and the largest allocation rate of personnel deployment. The intelligent parking lot management system of the Internet of Things is designed and developed to meet the goals of enterprise informatization management and efficient operation and implementation. The web platform conducts the joint operation of users and administrators to realize online reservation, parking at any time, and online payment for car pickup at any time.

Data-Driven Robust Optimal Allocation of Shared Parking Spaces Strategy Considering Uncertainty of Public Users’ and Owners’ Arrival and Departure: An Agent-Based Approach

To alleviate the problem between parking demand and supply, as well as improving urban traffic environment, shared parking has attracted great interest among researchers, policymakers, and entrepreneurs. Naturally, it is a prerequisite of sharing private parking spaces with public users (P-users) that all of the owners (O-users) providing parking spaces have space to park whenever they come back, with a unified management of all parking resources. However, it remains a challenge both in theory and practice. To solve this problem, firstly, we introduced a management framework of shared parking resource in terms of time and spatial dimension. Under this framework, to control the access to parking spaces of P-users, four phases (preparatory phase, open phase, releasing phase, and reconstructive phase) are divided in time dimension, and two types of parking spaces (the prestored parking spaces, and the shared parking spaces) are classified in spatial dimension. Then, based on the proposed management framework, an intelligent parking management system (IPMS) was developed to simulate the operation of shared parking considering the uncertainties of P-users’ and O-users’ arrival and departure. Furthermore, detailed sensitivity analysis, based on real-world data and simulations, evaluated the proposed framework and the developed IPMS in a case study concerning parking lots in Beijing, China. The results show that the IPMS can not only realize that there will always be enough available parking spaces satisfying O-users’ parking demand, but also bring about vast improvements in both utilization and turnover rate of parking spaces, comparing with the non-shared management strategy.

Research on Intelligent Parking Management System of Urban Roadside

Static traffic, as supplementary dynamic traffic, plays an equally important role in the development of modern city transportation. Because the urban land resources are very limited, the parking problem has been the focus of the city management department, while the traditional off-road parking has been unable to meet the requirements of the development of the city parking. This paper will introduce a roadside parking way, the front end detection device to video as pile, combing the basic business processes of roadside parking, and build a complete cloud platform to deploy the network topology, and then realize the communication between front-end video detector and cloud platform according to the specific business needs, and ultimately to achieve the real unattended of parking, timing and charging.

The Intelligent Parking System Based on ZigBee Technology Research and Design

With the development of economy, people living standard rise, the necessary traffic tools in the private cars as showing a strong growth trend, the resulting traffic problems become more and more serious, mainly urban area parking management technology still is not high, generally lead to the parking management difficult problem is also growing. So in order to improve the management of the parking lot, improve the efficiency of parking, parking management system, the author of this paper in the entrance guard recognition and parking monitoring problems put forward a design scheme of intelligent parking management system, the scheme comprehensive utilization of the Internet of things (RFID) and Zigbee wireless sensor technology, the system has simple structure, low cost, and expected results have been achieved in the lab, can make the car into the designated parking space.

Intelligent Parking Management System (PMS) based on Video Analytics

Intelligent Parking Management System (PMS) based on Video Analytics

Parking problems in Abu Dhabi, UAE toward an intelligent parking management system “ADIP: Abu Dhabi Intelligent Parking”

Car parking is a serious problem in Gulf Cooperation Council (GCC) countries in general and in United Arab Emirates (UAE) in particular. This problem has been associated with the exceptional growth in the number of cars, buses, trucks, and other modes of transportation over the past few decades. In Abu Dhabi (the capital city of UAE), finding a parking at some locations is a real challenge due to the lack of available parking slots in the city. In 2009, in order to organize the randomness in parking management in Abu Dhabi, Abu Dhabi City started implementing a new paid parking system inside the city, named MAWAQIF. This new system helps in reducing the parking problem in congested areas, yet has transferred the problem to less crowded areas in the city. Furthermore, the number of parking lots provided in the controlled areas isn’t enough to satisfy the demand in these areas. This article concentrates on this direction and focuses on two aspects. First, a survey was prepared and distributed to 500 participants as a part of a project, in order to identify the scale of the parking problem in Abu Dhabi. Then, a technical framework for developing an intelligent mobile application for improving the indoor parking management system in Abu Dhabi was developed. Results indicate that the proposed mobile application will help in reducing the time wasted in searching for parking and will increase the efficiency of the parking system in Abu Dhabi.

On Research IoT-based Intelligent Parking Management System and Its Design

With the rapid economic development and constant social advancement in our country, people's production and lifestyle are undergoing profound changes, consequently resulting in traffic jams and increasingly severe challenges on the limited parking resources. How to enhance the utilization of parking places has been an important problem influencing city image and the harmonious economic and social development. This paper introduces a Internet of Things (IoT)-based intelligent parking management system, innovatively proposes a non-source RFID card that utilizes label and sensor binding to actualize vehicle identification and to accomplish functions of vehicle entrance & exit authentication, automatic charging, and parking lot certification, eventually further enhancing the utilization, traffic efficiency and service level of parking places.

Transportation Planning Aspects of a Smart City–Case Study of GIFT City, Gujarat

Gujarat International Finance Tec-City Company Limited (GIFTCL) is developing a financial Central Business District (CBD) namely GIFT City between Ahmedabad and Gandhinagar as a global financial and IT services hub, a first of its kind in India. GIFT City is being developed as a high quality commercial zone along with an ideal blend of residential and social facilities that optimise land and real estate values with global connectivity and generation next infrastructure. GIFT City transport master plan aims at a transit oriented development based on walk to work approach, pedestrian friendly infrastructure with zero fatal accidents, easy and fast mobility with minimum conflicts and efficient public transport systems which reduce the per capita energy basket. In accordance with the GIFT City transport vision, the transport infrastructure has been planned to cater to the daily demand as well as that of the peak hour and Multi Level Parking (MLP) lots have been proposed at suitable locations in the GIFT city. To enhance the mobility and safety in GIFT city, various smart transport applications like advanced traveller information system, security and surveillance system, intelligent parking management system, parking guiding system, automatic vehicle location and tracking, real time travel response etc are planned. GIFT City transport master plan addresses the needs of all users of GIFT City, thereby it can be called as “User-Centred Smart Transport System” and its makes it possible for all GIFT City users to enjoy a world class life style in this vibrant global city. GIFT City smart transport planning parameters and design details are elaborated in this paper.

Design of Intelligent Parking Management System Based on License Plate Recognition

License Plate Recognition (LPR) which has been extensively studied recently is becoming one important part of Intelligent Transportation Systems (ITS). It is not only applied to public security monitoring, but also applied to a red light shot, speeding violation paparazzi, parking system and so on. The present paper introduces an intelligent parking management system based on LPR, recognizing license plate automatically at the parking lot access and realizing vehicle information integrated management conveniently. The software part is developed with VC++, QT and Microsoft Office Access Database. In the system, LPR is carried out through video streaming frame by frame to choose the best result with a high speed. After accurate LPR, the vehicle information, such as LP number, LP color, car type and access time, will be stored in system database. In addition, the system interface is designed very friendly and simple for administrators to operate, which can largely improve the whole performance of LPR system. Experimental results show that this parking management system can achieve high correct rate at 95%, and can be applied to real-time implementation

Intelligent Parking Management System Based on Image Processing

This paper aims to present an intelligent system for parking space detection based on image processing technique. The proposed system captures and processes the rounded image drawn at parking lot and produces the information of the empty car parking spaces. In this work, a camera is used as a sensor to take photos to show the occupancy of car parks. The reason why a camera is used is because with an image it can detect the presence of many cars at once. Also, the camera can be easily moved to detect different car parking lots. By having this image, the particular car parks vacant can be known and then the processed information was used to guide a driver to an available car park rather than wasting time to find one. The proposed system has been developed in both software and hardware platform. An automatic parking system is used to make the whole process of parking cars more efficient and less complex for both drivers and administrators.

Design and Application of Virtual Parking Management Platform Based on LabVIEW

Intelligent parking management development platform based on LabVIEW imitates parking access control system, smart regional guidance system, parking information inquiry system and alarm information inquiry system. The system achieves kinds of functions, such as fast access, time charges, intelligent guidance, security alarm and so on. The development platform for intelligent parking management system can be applied to develop new features for the system. The platform simulates that the parking system combines the Internet of Things technology using the LabVIEW database connectivity tools package. It can develop new functions including urban parking guidance and smart reverse seeking cars in adapt to smart city development.

Parking Management and Modeling of Car Park Patron Behavior in Underground Facilities

Underground parking facilities in urban areas or central business districts have incorporated many information and communications technologies to provide better service, to achieve customer satisfaction, and to improve parking management. But the diversity of the off-street parking supply in terms of parking access and revenue control systems, the information offered, costs, and benefits suggests that the efficiencies of certain improvements in parking facility operations and the ultimate profitability obtained as a result of the corresponding investment made by the parking operator need to be compared. The present investigation focuses on the operations of and the behavior of parking patrons in underground parking facilities, a common type of facility in Barcelona, Spain. To model patron behavior, commonly known desegregated models based on the random utility theory were adapted to facilitate an understanding of how parking patrons decide to use a particular garage level and determine their preferences for a particular garage level. The decisions made depend on the accuracy and the convenience of the information offered. The study finds that an intelligent parking management system that tells a customer the exact locations of the available spaces is of great benefit to patrons and in the long run is a cost-effective alternative to operators because the operator can achieve financial profitability with small increases in the parking rate, and in competitive environments patrons will prefer facilities with these systems over others. The conclusions presented in this paper will be particularly useful to planners, developers, and managers.

Parking Management and Modeling of Car Park Patron Behavior in Underground Facilities

Underground parking facilities in urban areas or central business districts have incorporated many information and communications technologies to provide better service, to achieve customer satisfaction, and to improve parking management. But the diversity of the off-street parking supply in terms of parking access and revenue control systems, the information offered, costs, and benefits suggests that the efficiencies of certain improvements in parking facility operations and the ultimate profitability obtained as a result of the corresponding investment made by the parking operator need to be compared. The present investigation focuses on the operations of and the behavior of parking patrons in underground parking facilities, a common type of facility in Barcelona, Spain. To model patron behavior, commonly known desegregated models based on the random utility theory were adapted to facilitate an understanding of how parking patrons decide to use a particular garage level and determine their preferences for a particular garage level. The decisions made depend on the accuracy and the convenience of the information offered. The study finds that an intelligent parking management system that tells a customer the exact locations of the available spaces is of great benefit to patrons and in the long run is a cost-effective alternative to operators because the operator can achieve financial profitability with small increases in the parking rate, and in competitive environments patrons will prefer facilities with these systems over others. The conclusions presented in this paper will be particularly useful to planners, developers, and managers.