Parking System Research Articles

Potential-based dynamic parking navigation for autonomous vehicles: Near-priority vs. distant-priority

We aim to enhance the parking efficiency for a group of autonomous vehicles in a large parking lot during peak hours. Two parking principles, i.e. the near-priority (NP) and distant-priority (DP) principles, are proposed and quantitatively examined. The NP principle characterizes individual parking behavior, where autonomous vehicles tend to select available parking spaces that are closer in proximity. Conversely, the DP principle is proposed from the perspective of the entire parking system, prioritizing the allocation of more distant parking spaces within a certain range around each entrance. Two time indicators, including the overall parking time and the average parking time, are adopted to evaluate the performance of the two principles. A potential-based cellular automata (CA) model is proposed to formulate the dynamic parking process of vehicles in a two-dimensional space, where vehicle navigation is driven by a so-called potential field. Then, two dynamic navigation algorithms are developed for parking navigation under the NP and DP principles. Furthermore, by conducting a set of comparative simulation experiments, we have obtained some management insights into peak parking management in the era of autonomous driving.

Integration of YOLOv5 Algorithm and OpenCV in Innovative Smart Parking Management Approach

The problem of automatic parking lot identification and vehicle detection in open areas is becoming increasingly important due to the increase in the number of vehicles in Indonesia, particularly in big cities, resulting in difficulties in finding parking spaces during peak hours. In this condition, drivers often have to compete for parking spaces. This research aims to develop a smart parking system that integrates YOLOv5 and OpenCV algorithms. This approach thoroughly combines both algorithms to identify parking spaces and detect vehicles in real time in various parking scenarios. It is carried out in an open area with reference to parking conditions at the BRIN Bandung office. This study collected data from three different parking lot conditions, namely empty, partially occupied, and full. In each condition, the system successfully detected the parking lots and vehicles accurately. The novel contribution of this research is the development of a smart parking system that uses an integrated approach, providing an effective solution to the challenges of parking lot availability and vehicle detection. Using the advantages of both algorithms, we successfully created a system that can identify parking spaces and detect vehicles accurately and efficiently under various parking circumstances. Therefore, this research makes a significant contribution to the development of smart and adaptive parking management technology.

Operation optimization considering multiple uncertainties for the multi-energy system of data center parks based on information gap decision theory

Operation optimization considering multiple uncertainties for the multi-energy system of data center parks based on information gap decision theory

EFEKTIVITAS PEMUNGUTAN PAJAK PARKIR DI KOTA SAMARINDA: TINJAUAN DARI PERSPEKTIF HUKUM DAN KEBIJAKAN

Parking tax is a significant source of Local Revenue (PAD) in Samarinda City, but its implementation faces various challenges. The regulations governing parking tax aim to provide a clear legal framework, yet taxpayer compliance remains low. Weak supervision, limited technology, and low public awareness are the main factors hindering tax collection effectiveness. The use of digital technology in the parking system can enhance taxpayer compliance and reduce revenue leakage. Improving human resource capacity and conducting educational campaigns to raise public awareness are also important. Implementing policies that provide incentives for compliance and strict sanctions for violations is expected to optimize parking tax revenue and improve public services and city infrastructure.

Constraint Optimization Model for Dynamic Parking Space Allocation.

Managing car parking systems is a complex process because multiple constraints must be considered; these include organizational and operational constraints. In this paper, a constraint optimization model for dynamic parking space allocation is introduced. An ad hoc algorithm is proposed, presented, and explained to achieve the goal of our proposed model. This paper makes research contributions by providing an intelligent prioritization mechanism, considering user schedule shifts and parking constraints, and assigning suitable parking slots based on a dynamic distribution. The proposed model is implemented to demonstrate the applicability of our approach. A benchmark is constructed based on well-defined metrics to validate our proposed model and the results achieved.

Economic Analysis of On-Street Parking with Urban Delivery

The surge in online shopping has dramatically increased the demand for short-term curb access for package pickups and deliveries, leading to heightened competition for limited curb space. This paper addresses the problem of how the unique parking demand of deliverers, particularly their parking duration for delivery attempts linked to parking space availability, affects the dynamics of urban curb parking systems. We develop continuum models of a curb parking system and perform analytical analyses to understand the dynamics and steady-state properties of the system under the influence of increased urban deliveries. We conduct comparative statics to examine how various curb management measures, such as pricing, parking duration caps, and dedicated delivery bays, influence the equilibrium conditions, followed by comparisons of the theoretical capacity of these measures. We further demonstrate the working mechanism of delivery bays and their role in forestalling specific failures within a hybrid system with both general parkers and deliverers. Finally, we investigate curb management strategies in nonstationary operational contexts and prescribe the optimal strategies therein. Our findings offer valuable insights into the unique properties that deliverers introduce to curb parking dynamics, highlighting the need for a strategic reevaluation of current management practices. We find that pricing strategies for metered parking to general parkers prove to be more efficient and flexible compared with other interventions. Notably, our analysis suggests that when curb parking pricing is optimally calibrated, the necessity for dedicated delivery bays diminishes. Furthermore, we reveal that optimal curb management strategies could diverge in response to surges in demand, depending on whether the increase sources from general parkers or deliverers. To be effective, the sizing of delivery bays must align with the underlying causes of parking scarcity. History: This paper has been accepted for the Transportation Science Special Section on ISTTT25 Conference. Funding: This work was supported by the George Washington University [University Facilitating Fund]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/trsc.2024.0569 .

Spread of parking difficulty in urban environments: A parking network perspective

AbstractSpread of parking difficulty can be regarded as a special cascading failure process of urban parking systems. A comprehensive understanding of this process can be greatly helpful to build a more robust parking system. Parking network, a specified complex network, is proposed to model, simulate, and analyse the failure process of urban parking systems in this paper. This model is applied to the analysis of parking systems in an abstract city grid and the downtown area of Luohu, Shenzhen. The results demonstrate that the parking network can capture subtle variations among various parking cruising behaviours or strategies from a network perspective. To enhance the utility of the parking network, an auxiliary indicator named “Parking Difficulty Index” is introduced to help assess the failure degree of urban parking system, estimate the optimal timing for parking guidance intervention, and evaluate the effectiveness of various guidance strategies in mitigating parking difficulties.

Deep learning and saliency-based parking IoT classification under different weather conditions

The world’s population is growing at an exponential rate, which has created a slew of new issues in our daily lives. Among these challenges is the difficulty of finding available parking spaces. To overcome this obstacle, an effective system for detecting vacant parking spaces is crucial, particularly in densely populated areas. Even though there are numerous parking detecting systems on the market today, they all have their own set of restrictions. There are primarily two types of parking systems available. The first is a hardware-based system that uses hardware to detect whether a space is vacant or occupied, and the second is a smart parking system that uses cameras to classify parking status. Vision-based parking systems are becoming increasingly popular due to benefits such as flexibility and cost efficiency. However, due to challenging weather conditions and various occlusions caused by objects, such systems are challenging to develop. The limitations of a vision-based parking system must be addressed for it to become more accurate. To date, many researchers have attempted to incorporate deep learning-based parking systems with various algorithms but none of them has focused on reducing the complexity of Convolutional Neural Network (CNN) training through unsupervised pre-processing steps. In this study, an attempt is made to reduce the complexity of CNN by integrating salient features as a pre-processing step for normalizing weather conditions. It has been observed that salient features-based pre-processing makes the system more robust in terms of accuracy and time efficiency.

Sunscreen pollution is abated during the COVID-19 “Anthropause” of 2020 in two U.S. National Parks: Cape Lookout National Seashore and Kaloko-Honokōhau National Historical Park

From March to June 2020, governments across the world imposed lockdowns in an attempt to reduce the transmission of COVID-19 during the early phase of the pandemic. This period of time in which human activity slowed worldwide has been coined the “Anthropause”. The goal of this study was to determine if sunscreen pollution abated during the Anthropause and to identify the severity of the pollution when tourism/recreation recovered at two coastal units of the U.S. National Park System: Kaloko-Honokōhau National Historical Park in Hawaiʻi, U.S.A. and Cape Lookout National Seashore in North Carolina, U.S.A. Active ingredients of sunscreen products were measured in water and sand samples at both locations, including oxybenzone, octinoxate, octocrylene, octisalate, homosalate, and relevant breakdown products of some of these ingredients. A risk assessment was conducted on Anthropause and post-Anthropause contaminant levels for both locations to determine if there was a threat reduction during the Anthropause, and whether tourism recovery in the post-Anthropause period served as a threat to coastal wildlife. Both national park units exhibited an almost absolute reduction in the levels of sunscreen contamination during the Anthropause period, a striking commonality considering the geographic expanse separating the parks. Once travel restrictions were lifted, a large influx of tourists ensued at both locations, resulting in a relatively sudden and dangerous increase in the levels of sunscreen chemical pollution. This study supports the argument that unmanaged tourism is a source of coastal sunscreen pollution that poses a threat to the localized continuity of species populations and biodiversity, especially to coral reefs and fisheries.

Limitations of existing park quality instruments and suggestions for future research

Public parks are critical urban infrastructures offering health, environmental, social, and cultural benefits to people. However, the idea of park quality has lacked a clear operational definition and normative standard for measurement. We provide critical insights into existing park quality instruments and advocate for an alternative approach. First, due to the significant diversity in parks, inherent ambiguity and subjectivity in the idea of quality, and previous instruments’ inconsistent operationalizations of park quality, we recommend that future research shift its focus from creating instruments for universal application and standardized measurement to developing an inventory or list of park quality indicators that researchers and practitioners can selectively choose for their unique park contexts. Second, through our multidisciplinary examination, we identify five limitations in existing park quality instruments: (1) lack of attention to the histories of marginalized communities, (2) overemphasis on physical activities and public health, (3) lack of attention to ecological function and biodiversity, (4) lack of subjective measurements, and (5) insufficient consideration of multiple parks or a park system. Overall, a more flexible and site-specific approach to park quality measurement and the adoption of new indicators of park quality are expected to accomplish a more comprehensive and fairer assessment of park quality, contributing to park equity research and practice.

A smart parking system combining IoT and AI to address improper parking

The world is entering a new era of intelligent parking, with researchers exploring innovative solutions to enhance the parking experience. These solutions aim to simplify parking challenges for drivers, reducing stress caused by traffic congestion and the search for available spaces. This study presents an intelligent parking system driven by artificial intelligence (AI). It addresses inefficient and improper parking, providing drivers with detailed information about available spaces and improving their management. This approach empowers drivers with insights into parking availability, reducing time and fuel consumption. The system streamlines parking operations, ensures accurate spot availability information, and enhances overall efficiency and user satisfaction. The effectiveness of this proposed system is evidenced by a range of outcomes, including significant reductions in the time spent searching for parking and decreased fuel consumption along comparable travel routes.

IR Sensor based Smart Parking System

Nowadays congestion of traffic level increased with the increase in population. As the population increases, the utilization of vehicles also increases. It's becoming a difficult task to find a slot to park the vehicle. To overcome this problem, a smart parking system is introduced. Previously, there were some approaches to this system where Bluetooth and GPS tracker were used to find the empty slots, and different sensors were used for indoor and outdoor parking. In some approaches there was no security for the user’s details. Whereas in the proposed system, every slot has a number which makes it easier for the user to find out the empty slot. IR sensors are used to detect the vehicle and the empty slot is displayed on LCD as well as cloud server where the user’s details are secured. Smart parking system is an IoT based system which includes Raspberry pi, LED display, Cloud Server, Monitor and IR Sensors that are available in each parking slot. The proposed system leverages the advantages of IR sensor technology to accurately detect the presence of vehicles in parking spaces, provides real-time information to the users, and improves overall parking efficiency. The paper discusses the system architecture, sensor deployment strategies, and implementation, thereby showcasing the potential benefits of IR sensor-based smart parking systems. Index Terms: camera, cloud, parking, Raspberry Pi, sensors, vehicles

Design of Mathematical Model and Implementation of IoT Enabled Smart Secure Parking System

Design of Mathematical Model and Implementation of IoT Enabled Smart Secure Parking System

IOT - Enabled Digital Vehicle Parking Systems using Machine Learning

Abstract: In large cities, parking availability is a major problem. Car owners are confused by crowded reserved parking spaces during rush hour. To overcome this obstacle, modernizing the parking system is crucial. This research will conduct an in-depth and thorough literature review of past studies and project implementations to identify best practices and gaps in the existing research. The goal is to analyze previous work comprehensively, highlighting successful approaches and areas where further investigation is needed.In this study aims to perform a detailed and comprehensive examinations of previous research and research executions to precise effective strategies and deficiencies in the current body of research.The objective is to thoroughly evaluate prior efforts,emphasizing successful methodologies and areas requiring additional investigation.A prototype of the digital vehicle Parking System is implemented via an Android application leveraging Firebase and IoT based on AI . This makes it easy for drivers to find parking spaces with assigned spaces.

Moving Vehicle Number Plate Detection

Abstract: The ability to detect and recognize vehicle license plates is a crucial task in various applications such as traffic management, law enforcement, and parking systems. In this project, we propose a system for moving vehicle license plate detection using image and video processing techniques. The system employs a combination of computer vision algorithms and machine learning models to accurately locate and recognize license plates from moving vehicles in real-time. The input images or video frames are preprocesses to enhance the regions containing license plates and reduce noise. This preprocessing step may include operations such as resizing, grayscale conversion, noise reduction, and contrast enhancement. Next, object detection algorithms such as Haar cascades or deep learning-based techniques like YOLO (You Only Look Once) are utilized to detect candidate regions in the image/frame that potentially contain license plates. After candidate regions are identified, a series of image processing techniques such as morphological operations, contour detection, and character segmentation are employed to isolate and extract the license plate characters. Machine learning models like Support Vector Machines (SVM), Convolutional Neural Networks (CNNs) are then applied to recognize the characters on the license plate.

IOT Based Smart Parking System

Abstract: The problem faced by people in this modern era in urban areas is the problem of parking whether it is in shopping mall, railway station, hospitals, movie theatre, etc. This problem occurs due the increase of number of vehicles in recent times. Furthermore, today’s car parking is insufficient and driver/users waste most of the time in finding a place to park their vehicles. The purpose of this research is to use modern technologies like IoT (Internet of Things) and RFID (Radio-Frequency Identification) which detects the availability of parking slots in the parking lots. Besides, the smart parking system has a web application which displays how many slots are available and alerts the user when status of the slot has changed. Additionally, the user details are added on the database. Hence, the smart parking system will provide a smooth functioning and will take the parking system to new levels

자율주행 발렛 주차 시스템을 위한 계층적 주차 경로 계획

자율주행 발렛 주차 시스템을 위한 계층적 주차 경로 계획

Arduino Based IOT Smart Parking System

Abstract: The idea of "smart cities" was very popular in the beginning. This paper presents an in-depth exploration of an Arduino-based Internet of Things (IoT) Smart Parking System designed to address the growing challenges of urban parking management. Leveraging the capabilities of Arduino microcontrollers and IoT technology, the proposed system offers an intelligent and efficient solution for optimizing parking space utilization. The key components of the system consist of sensor nodes that are positioned thoughtfully in parking spots and send occupancy data in real time to a centralized Arduino microcontroller. After processing this data, the microcontroller sends status updates to a cloud-based platform via wireless communication protocols. The cloud platform is interfaced with an intuitive mobile application that gives drivers instant access to information about parking availability and promotes a smooth parking experience.

Integrated Notification System for Smart Parking Security Using Bot Telegram

Notification system for smart parking system is very important for parking security. The purpose of this research is to create a system used in parking security in the technical faculty of mataram university. The method used in this research is the flow of making a notification system using a telegram bot, namely determining the notification using a telegram bot and then creating a telegram bot that will send notifications to security guards, after the bot has been created, then coding the notification system so that the notification can run according to existing rules. The results showed that the notification system made runs according to predetermined rules as seen from the success of sending notifications to the security guard group. The conclusion is that the use of this notification system is a solution to parking security problems. This notification system can provide accurate information to security officers regarding information on vehicle data mismatches and vehicle license plates so that vehicles in the parking area can be monitored.

Smart Car Parking System and Generation of Piezoelectric Energy

Abstract: In the past few years, parking has become a costly commodity in virtually every major urban region on the earth, and scarcity is a contributing factor to traffic jam and air pollution in urban areas. The most popular method to obtain a parking place is to do it manually, in which the drivers looks for a parking area either through experience or by luck. This method takes time and effort, and it may result in the worst-possible situation of not finding a parking place if vehicle is in a place with a high vehicle density. An effort is made here to park the vehicle as well as to find a parking space for the vehicle with a framework of Smart Parking System(SPS) which is based on the law of conservation of energy in we basically convert the elements from mechanical energy into electrical energy. This document Allow user to Automatically find a free site for parking at low cost without wasting much fuel and time.