Parking Information Research Articles

Analysis of user behavior in urban parking under different level of information scenarios provided by smart devices or connected cars

Due to the issues of land redevelopment and changes of use within urban areas, many cities must adopt measures to reorganise and optimise parking space. This paper proposes a methodology to study one of them by implementing parking information systems (PIS). This solution offers users a competitive advantage by allowing them to know about the free parking spaces at the moment of decision-making. To achieve this goal, microscopic simulations are conducted to analyse the effects of various scenarios involving the implementation of PIS. The data used in these simulations is obtained from the Santander area in Spain. For the evaluation of results, a methodology has been developed that combines the evaluation of social factors for citizens and operational impacts for decision-makers. The results show significant improvements with increasing user information rate, e.g., the number of unsuccessful parking attempts before finding a final parking space is reduced by 55%, and 37% less particulate pollutants are emitted into the atmosphere.

Parking Survey Design Using Gamification

We present a survey methodology to collect parking behavior data. The survey is a game that exposes respondents to hypothetical parking scenarios including parking information and the possibility of illegal parking. We use incentive mechanisms from the gamification literature. The survey overcomes choice set deficiencies of conventional revealed and stated preference surveys (i.e., large or unavailable choice sets). We record detailed travel and parking decisions and use the data to develop choice models. The Mixed logit model demonstrates significance of parking preference heterogeneity. Respondents are more likely to park legally when provided full information about parking spot status.

Ordinal Regression Model of Parking Search Time

Parking search reduces the quality of parking service, as well as traffic network level of service, due to additionally generated traffic. Parking search also entails other negative effects, primarily ecological, social and economic. Even though the importance of this problem has been noted in the past, there is an impression that this issue has not been sufficiently researched and should be additionally analysed in order to properly understand this phenomenon. Therefore, the aim of this paper is to study the factors affecting parking search time that can be influenced through a set of parking management measures. In this paper, an ordinal regression model was developed to estimate these parameters and it was fitted using empirical data collected by interviewing drivers. Main model results show that parking occupancy has the highest impact upon the value of parking search time, indicating the significance of defining proper policies and measures aimed at reaching targeted parking occupancy. Parking frequency is the second parameter observed to be significant, demonstrating the importance of implementing proper parking information systems.

Design of Parking Information System in Langsa City General Hospital, Aceh

This study designed and built a parking information system at the Langsa City General Hospital with the aim of facilitating the management of incoming and outgoing vehicle data at the Langsa City General Hospital parking lot in Aceh. With the rapid advancement of technology, previous data management was still done manually, so it was not effective and efficient, and officers found it very difficult to know the data of incoming and outgoing vehicles. Researchers designed a computer-based information system to facilitate the management of the parking system. Methods of data collection using descriptive qualitative methods, namely observation, interviews, and literature study, and software development methods using the waterfall as well as the PHP programming language and the MYSQL database The information system created aims to make it easier for officers to manage vehicle entry and exit data at the Langsa City Regional General Hospital in Aceh.

Optimal capacity sizing of park‐and‐ride lots with information‐aware commuters

We study capacity sizing of park‐and‐ride lots that offer services to commuters sensitive to congestion and parking availability information. The goal is to determine parking lot capacities that maximize the total social welfare for commuters whose parking lot choices are predicted using the multinomial logit model. We formulate the problem as a nonconvex nonlinear program that involves a lower and an upper bound on each lot's capacity, and a fixed‐point constraint reflecting the effects of parking information and congestion on commuters' lot choices. We show that except for at most one lot, the optimal capacity of each lot takes one of three possible values. Based on analytical results, we develop a one‐variable search algorithm to solve the model. We learn from numerical results that the optimal capacity of a lot with a high intrinsic utility tends to be equal to the upper bound. By contrast, a lot with a low or moderate‐sized intrinsic utility tends to attain an optimal capacity on its effective lower bound. We evaluate the performance of the optimal solution under different choice scenarios of commuters who are shared with real‐time parking information. We learn that commuters are better off in an average choice scenario when both the effects of parking information and congestion are considered in the model than when either effect is ignored from the model.

ParkIT: Smart Parking Application using Deep Learning

One of the main implications of population growth and high lifestyle standards, particularly in urban areas, is the increase in city traffic. Trying to find a parking spot during rush hours is time-consuming and causes unnecessary fuel wastage. Uncoordinated searching for parking spaces often results in traffic in such spaces and increased vehicle exhaust volume has a detrimental effect on the environment. Along with that, the same parking charges regardless of the parking time are quite unreasonable. Dynamic parking fees and reservation-based smart parking systems have therefore become essential. The technique presented in the research communicates parking information to a driver in advance, considerably decreasing the time spent in searching parking spaces.

PAA: A Blockchain-Based Parking Assistance Alliance With User Preference

In order to improve traffic conditions and environmental pollution caused by automobile exhaust, it is critical and challenging to help numerous vehicle users to obtain ideal parking spaces in terms of quality of experience (QoE), security and efficiency. The parking assistance scheme using the consortium blockchain can get a tradeoff between security and efficiency, but it is a key issue to meet the preferences of parking space seekers and design a well-operated incentive sharing mechanism. This paper proposes a Parking Assistance Alliance (PAA) scheme based on double auction for vehicular blockchain. Through truthful incentives, the PAA encourages vehicles in the alliance to provide parking information for nearby vehicle users. Further, the vehicle user’s preference is fully considered when assigning the parking space. The matching priority is introduced by incorporating the parking space supply and demand, as a reference to provide prioritized service. Theoretical proofs and simulation results show that the PAA scheme can achieve individual rationality, budget balance, and truthfulness, with high user satisfaction, and the PAA scheme deployed on the IBM Hyperledger Fabric platform outperforms the existing method with an average of 7.42% higher successful allocation ratio and 35.4% less transaction confirmation time.

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

Smart Parking System Using IoT Sensors

Due to the increasing difficulty of finding vacant parking slots in urban cities, Smart Parking System has been developed to solve the problem. It is a system that can show the status of all parking slots in an area which allows drivers to find parking easily. The objective of this paper is to design a Smart Parking System by using Internet of things (IoT) sensors and evaluate the system’s performance. In this paper, ultrasonic sensors will be used as the IoT sensors while the microcontroller of the system is the NodeMCU ESP8266. The ultrasonic sensors will be placed in each parking slot to detect the presence of a vehicle. When the sensor detects a car, it will send this information to the microcontroller and the microcontroller will update the parking data stored in the cloud server via an internet connection. The users can then access the parking information in the cloud with their mobile devices by scanning the Quick Response (QR) code provided or directly visiting the cloud online. In addition, unique designs are proposed to solve some common problems faced by the parking systems such as the ultrasonic sensor might be malfunctioning and the sensor is unable to differentiate between a vehicle and a pedestrian. The performance of the system will then be evaluated based on its accuracy. From the results obtained, the system prototype achieved an accuracy of 100 %. Comparing this system with other Smart Parking Systems proposed, it proves that this method has higher cost-efficiency and reliability. This shows the significance of this research since higher system reliability and cost-efficiency can increase the confidence of the parking area owners to implement this Smart Parking System which can save the driver’s time and reduce air pollution.

Implementation of Knowledge Management in the Electronic Parking System for Public Roadsides

Regulation of public roadside parking levies with knowledge management can help local governments to increase their productivity, performance, and income so that progress and alignment are created under the Local Government Medium-Term Development Plan. The vision and policy direction taken by the local government aims to increase people's welfare based on religious and cultural values. One implementation of knowledge management is the use of an electronic parking system. E-parking or electronic parking is a condition where parking management is carried out systematically using a parking information system. E-parking systems that can be implemented on the public roadside can also increase efficiency in parking transactions. This research was conducted at several public roadside parking points in Ponorogo, Indonesia. The methods is qualitative which interviews and research team had discussion with the parking attendants and representatives of the Department of Transportation and the Agency for Revenue, Financial Management and Regional Assets of Ponorogo regarding implementing the E-parking system. This system consists of electronic records with Android-based applications synchronized on website-based applications and using handheld-pos. The results showed that this system could improve the weaknesses of conventional systems and increase the productivity of parking service managers as a form of service to customers.

Parking information system with artificial neural network

Intelligent parking systems are necessary for deploying smart cities. For safe and comfortable parking in the parking places, it is necessary to install an information parking system that can show the current number of free and possibly also occupied parking places. Private parking places can be limited to their owners and the access can be protected by an arm barrier or retractable post. For vehicle presence sensing or vehicle transition sensing we can use various types of sensors. Every sensing technology has its own limitations or advantages, and it does not exist one universal solution for all possible situations. This article presents and describes the parking information system (PIS) based on real-time vehicle video detection with a safety IP camera and an artificial neural network. The proposed PIS consists of trained Yolo v5 neural networks trained to detect cars, vans, and trucks. To prevent false counts many control mechanisms were implemented (Zheng, 2015)

Evaluation of parking-related financial toxicity associated with cancer treatments in Western Canada

Introduction/BackgroundPatients and their caregivers incur numerous out-of-pocket costs while receiving oncologic treatments. These expenses are often overlooked by clinicians, even in countries with publicly funded healthcare systems. Parking fees are one such category of expenses that contribute to financial toxicity in cancer care. Patients with cancer often have protracted treatment courses, especially if they are receiving external beam radiation therapy. It is not clear if cancer center parking fees influence city-specific indices such as city-specific cost of living. The aim of this study was to evaluate cancer center parking fees in Western Canada and to elucidate any correlation between daily cost of parking and the city-specific indices. MethodsThis was a cross sectional study conducted from February 1st, 2022, to March 1st, 2022. An online search was undertaken to obtain the publicly available parking information for the regional and community cancer centers in the provinces of British Columbia, Alberta, Manitoba, and Saskatchewan. Telephone calls were made with parking offices or switchboards to obtain this information for the cancer centers that did not have online information on parking. Cancer center address transit scores, median city household income, and city-specific cost of living scores were obtained online for the cities where the cancer centers were located. Pearson correlation and a zero-inflated negative binomial model were used for statistical analysis. ResultsData was collected from 115 community and regional cancer centers distributed across the 4 provinces. The median hourly parking fee across all provinces was 2.00 Canadian Dollars (CAD) (Interquartile range (IQR), 0-4.25), whereas the median daily cost of parking was 9.50 CAD (IQR, 0-13.13). The median cancer center address transit score was 41.00 (IQR, 12.00-50.50). There was a statistically significant (p=0.029) positive correlation between the daily cost of parking and city cost of living. The correlation coefficient between the two variables was 0.412. Furthermore, there was a statistically significant (p<0.001) positive correlation between daily cost of parking and cancer center address transit score. The correlation coefficient between the two variables was 0.676. In addition, there was a strong negative correlation between the cancer center address transit score and the presence of free parking with a correlation coefficient of -0.613 (p<0.001). There was a nonsignificant (p=0.88) negative correlation between cost of living and the presence of free parking with a correlation coefficient of -0.028. DiscussionThe results of this study demonstrate that daily cost of parking for community and regional cancer centers in Western Canada significantly influences city-specific cost of living and cancer center address transit scores to a varying degree. This demonstrates that the influence of parking fees on patients with cancer is multilayered with significant direct and indirect effects. This can contribute to loss of wage and added financial burden on patients and their caregivers in higher-cost provinces. The presence of free parking at community and regional cancer centers had a statistically significant negative correlation with the cancer center address transit score. This suggests that cities with more free parking also have less robust public transit systems. Conversely, the presence of an extensive public transit system leads to a lower likelihood of free parking being available at cancer centers. ConclusionThe presence of a strong public healthcare system does not necessarily address all aspects of cancer-related financial toxicity. There is strong evidence of both positive and negative correlations between city specific indices and cancer center parking fees in Western Canada. Policy makers and stakeholders should be cognizant of this interplay between the various city specific indices and parking fees for patients with cancer. Policies on provincial and federal levels should be implemented to address this increasingly problematic burden on oncologic patients.

SAMPARK: Secure and lightweight communication protocols for smart parking management

Many vehicles on the road create significant problems, like parking, traffic congestion, fuel/energy consumption, and so on. Specifically, finding an appropriate parking spot is challenging for vehicle users while moving. Renting private parking spots is worthwhile using information and communications technology to solve parking challenges and offers mutual benefits to vehicle users and parking spot owners. However, security and privacy are prime concerns, as unknown vehicle users use private parking spots. The existing parking schemes are vulnerable to important security and privacy attributes and also inefficient due to high computational costs.We propose secure and lightweight communication protocols for smart parking management (named as SAMPARK) using lightweight cryptographic primitives, (i) to send available parking information and (ii) to reserve a parking spot ahead of time. Security proofs are discussed based on the random oracle model to confirm the security robustness of SAMPARK, considering vital vehicular communication attacks for security analysis. The test-bed results (on Raspberry Pi 3B+) show that the SAMPARK is relatively efficient in computation time, storage cost, and communication overhead.

Providing curb availability information to delivery drivers reduces cruising for parking

Delivery vehicle drivers are experiencing increasing challenges in finding available curb space to park in urban areas, which increases instances of cruising for parking and parking in unauthorized spaces. Policies traditionally used to reduce cruising for parking for passenger vehicles, such as parking fees and congestion pricing, are not effective at changing delivery drivers’ travel and parking behaviors. Intelligent parking systems that use real-time curb availability information to better route and park vehicles can reduce cruising for parking, but they have never been tested for delivery vehicle drivers. The current study tested whether providing real-time curb availability information to delivery drivers reduces the travel time and distance spent cruising for parking. A curb parking information system deployed in a study area in Seattle, Wash., displayed real-time curb availabilities on a mobile app called OpenPark. A controlled experiment assigned drivers’ deliveries in the study area with and without access to OpenPark. The data collected showed that when curb availability information was provided to drivers, their cruising for parking time significantly decreased by 27.9 percent, and their cruising distance decreased by 12.4 percent. These results demonstrate the potential for implementing intelligent parking systems to improve the efficiency of urban logistics systems.

Edge–Artificial Intelligence-Powered Parking Surveillance With Quantized Neural Networks

The rapid development of urbanization has raised challenges for existing parking facilities to serve increasing parking demand. Being constrained by the limited urban land resources for newly constructed parking facilities, improving the efficiency of existing parking infrastructures relies more on an advanced parking management strategy. Video-based parking surveillance technology, with abundant information, easy installation, and powerful algorithms, is the most popular method to provide real-time parking information as the required data feed for a parking management system. Meanwhile, deep learning-based algorithms gradually replace traditional computer vision methods for video processing since the detection accuracy has been increased considerably by learning fine-grained features. However, the excessive computational complexity of deep learning-based algorithms occupies considerable computational resources, which certainly hurts the entire system’s efficiency. Due to the limited computing power of edge devices, most parking surveillance systems deploy video processing algorithms on a server or cloud platform, which raises concerns about data transmission latency and central computation pressure. Deploying efficient algorithms on an edge-side device is a potential solution to solve these problems. This article proposes an edge computing parking occupancy detection system with a quantized deep learning model. Model quantization is employed to boost the inference speed while maintaining accuracy. In addition, knowledge distillation is applied to improve the quantized model’s training performance. Experiments are conducted to demonstrate the model’s superiority compared to state-of-the-art algorithms and the feasibility of edge computing. The proposed method can improve the accuracy and efficiency of parking surveillance systems. It is a systematic solution for obtaining parking information with limited computational resources.

Drivers' Subjective Assessment of the Ease of Finding a Vacant Parking Space in an Area Equipped with Vehicle Detection Devices.

The growing traffic on city streets leads to traffic disruptions, lowering the level of road safety, as well as the problem of finding a vacant parking space. Drivers looking for a vacant parking space on the street generate so-called search traffic. Paid parking zones are introduced to increase the availability of parking spaces for more drivers in many cities around the world. The development in the technology and information sector has contributed to the development of systems guiding drivers to vacant parking spaces. This article aims to analyze drivers’ subjective assessment of the ease of finding a vacant parking space in an area equipped with vehicle detection devices. Data from the Municipal Roads Authority in Gliwice (Poland) were obtained for the study, covering the use of parking spaces in the paid parking zone covered by dynamic parking information. Moreover, a survey was conducted among users of the paid parking zone in Gliwice. The answers of the respondents were used to build a logit model that allows determining the probability of a driver’s positive subjective assessment of the ease of finding a vacant parking space in an area equipped with vehicle detection devices. The results from the model allow the characterization of drivers who positively assess the ease of finding a vacant parking space in the area equipped with vehicle detection devices. In addition, it is possible to reach a group of drivers who negatively assessed the ease of finding a vacant parking space to learn about the factors that may cause them to change their assessment to a positive one. The research results allow city authorities to better manage parking spaces equipped with vehicle detection devices in the paid parking zone. This may change the negative assessment of the ease of finding a vacant parking space into a positive one.

IMPLEMENTATION OF RFID-BASED AUTOMATED PARKING MANAGEMENT SYSTEM: A FEASIBILITY STUDY

The difficulties of finding a parking spot in any business area are well-known to drivers. Parking tends to put them behind schedule owing to inefficient parking systems, making it much longer due to lost tickets, slow payment procedures, and insufficient parking information. To help lessen the delays caused by these problems, the researchers intend to integrate a technology-based solution in the three important parking procedures — the car entry and exit, the payment mechanism, and the location of parking slots — to significantly reduce the time spent handling these processes, with a particular emphasis on the management system’s ability to improve the parking experience. This study, titled Implementation of RFID-based Automated Parking Management System: A Project Feasibility, seeks to determine the feasibility of an RFID-based parking management system at Victory Mall and Market in Tanauan City, Batangas as its initial client. The project consists of two parts: (1) the system itself as the product and (2) the service that it will provide, featured by its cashless, contactless, and paperless transactions, making the overall service effective and efficient. The researchers conclude that the project is attainable, anticipating an initial service capacity of 929,888.07 parking hours with a 5% annual increase that will result in an average gross profit ratio of 68% per year. It is expected to have a three-year payback period for the total investments of its shareholders amounting to PHP 15,000,000.00. The assumed start of operation where the company caters to its first client is in June 2023.

Applying the Business Model Canvas on Haji Yahya’s Restaurant in Ipoh

The purpose of this research was to evaluate a business model for Haji Yahya’s restaurant in Ipoh. It is a traditional restaurant situated at one of the busiest roads in the new town. The Business Model Canvas (BMC) applied here consists of customer segments, value propositions, channels, customer relationship, revenue streams, key resources, key activities, key partnership, and cost structure. A qualitative descriptive analysis was used to analyse the data that was collected through focus group discussions and observation. A TOWS analysis was conducted for strategy creation. From the TOWS matrix, alternative strategies in business development of this restaurant were chosen. The authors have suggested several ways to promote the restaurant, such as running happy hour deals, offering video tutorials on how to cook signature dishes, such as rendang tok and chicken rendang, bundling and loyalty offerings, franchising, collaborations with more third-party deliverers, and improving parking by providing parking information to restaurant-goers.

Smart car parking system for smart cities using IoT

Using internet of things technology, an effective and smart solution to automate the administration of the parking system that assigns an efficient parking spot. The Internet of Things gives wireless connectivity to the system, and the user may keep track of the parking area's availability. With a growth in the number of automobiles in metropolitan centres, road congestion is a big issue. The purpose of this study is to address this issue. The user frequently wastes time and effort looking for available parking spaces in a certain parking lot. The user receives parking information through notification. As a result, the user's waiting time for a parking place is reduced.

Application of Clustering Algorithms in the Location of Electric Taxi Charging Stations

The reasonable layout of charging stations is an important measure to improve the penetration rate of the electric taxi market. Based on the multi-type clustering algorithm, a widely applicable electric taxi charging stations locating method is proposed. By analyzing the massive gasoline taxi GPS trajectory data, the parking information and charging requirements of electric taxis are extracted, and the research area is divided into reasonable grids. Then, the divided grids are respectively subjected to multiple same-type clustering and multiple multi-type clustering algorithms, so as to help find out the location of the charging station, and a comparative analysis is performed. The empirical analysis shows that the positioning results of the multiple multi-type clustering algorithms are more reasonable than the multiple same-type clustering algorithms, which can effectively prolong the driving distance of electric taxis and save the travel time of drivers.