Smart Parking Service Research Articles

Assessing LoRaWAN radio propagation for smart parking service: An experimental study

The increase of the population living in cities has put a lot of pressure in urban transportation systems. It comes, among other things, with noteworthy air pollution, time and energy wastage, and drivers’ discomfort due to parking spots scarcity. Finding a parking spot has become a major problem for drivers. To overcome this problem, smart parking services that detect parking spot occupancy status and inform drivers about their availability have been proposed. The deployment of these solutions is reducing the costs associated to traffic jams or gas consumption. However, one of the main challenges faced when planning and deploying this kind of service is the communication technology used by the parking sensors, which are typically buried under the asphalt, as it has to cover large areas of the city in the most cost-effective way. In this paper, we analyze the behavior and performance of a LoRaWAN network supporting the smart parking service in the city of Santander. The sensors and network deployment are described and the thorough experimental evaluation of the network behavior is presented. The goal of this assessment is to provide insights that could be helpful for better understanding the key factors affecting the communication. The long-termed analysis of the parking sensors deployments studied, have allowed us to derive an experimental propagation model that could be useful for the planning of city-scale IoT infrastructures employing LoRaWAN networks as their wireless access technology. Moreover, we have also analyzed the behavior of the LoRa wireless network in order to evaluate the possibility of leveraging network information to increase the confidence on smart parking sensor readings through AI-based predictors.

Smart Parking Services: An Overall Solution Based on Internet of Things and Fog Computing

Smart Parking Services: An Overall Solution Based on Internet of Things and Fog Computing

Privacy-preserving solution for vehicle parking services complying with EU legislation.

Today, many modern cities adopt online smart parking services as best practices. Citizens can easily access these services using their smartphones or the infotainment panels in their cars. These services' primary objective is to give drivers the ability to quickly identify free parking slots, which should reduce parking time, save fuel, and relieve traffic in urban areas. However, the privacy offered by these services should be comparable to that of the standard paper-based parking solutions offered by parking ticket machines. On the other hand, a privacy-preserving smart parking service's design may raise a number of issues, including how to prevent double or multiple uses of parking tickets, how to prevent user tracking and profiling, how to revoke malicious users, how to handle data statistics without violating users' privacy, and how to comply with regulations like the General Data Protection Regulation (GDPR). In this article, we present multidisciplinary research on a comprehensive vehicle parking system that protects users' privacy. The research includes a range of topics, from the examination of regulatory compliance to the design of privacy-preserving parking registration and vehicle parking services to the implementation of privacy-preserving parking data processing features for data analysts. We provide a security analysis of our concept as well as several experimental results.

Research on Intelligent Parking Operation and Management Planning Based on Revenue Model Function

With the development of the world, people's living standard has also improved significantly. At present, self-driving has become one of the popular ways to travel, but this improvement in living standard has also brought some problems such as "difficult parking" and "indiscriminate parking" to the society. In order to solve the problem, our country has launched the decision to develop smart parking. In the case of Shenyang, starting from 2018, due to the substantial growth of civilian car ownership in Shenyang, in order to alleviate the problems of "difficult parking" and "indiscriminate parking", the relevant areas in Shenyang began to develop smart parking. The current smart parking service mainly adopts two billing methods: mobile video collection vehicle billing and manual billing, and this paper analyzes the route planning and possible benefits of the smart parking service by establishing an appropriate mathematical model to obtain the final optimized design scheme.

Investigating the Usage of IoT-Based Smart Parking Services in the Borough of Westminster

Smart Parking schemes cannot succeed without the engagement and support of the drivers who may benefit from their use. This study investigates engagement with a Smart Parking service in the London Borough of Westminster. Factors likely to influence the use of Smart Parking services were identified from a literature review and incorporated into an explanatory model comprising 9 factors connected by 16 hypotheses. To test the model, residents of Westminster and visitors to the area were surveyed, resulting in a total of 212 valid responses. The responses were used to test a structural equation model, using confirmatory factor analysis. The results of the analysis indicated that Awareness of the scheme; Perceived Ease of Use; Perceived Usefulness; Cost saving; Perceived Privacy and Perceived Security all had a direct impact on Usage, with Awareness being the most influential factor. The results also highlighted the fact that, despite efforts by Westminster Council to publicise the scheme, 74% of respondents had little awareness of it, suggesting the need for improved publicity.

Investigating the Usage of IoT-Based Smart Parking Services in the Borough of Westminster

Smart Parking schemes cannot succeed without the engagement and support of the drivers who may benefit from their use. This study investigates engagement with a Smart Parking service in the London Borough of Westminster. Factors likely to influence the use of Smart Parking services were identified from a literature review and incorporated into an explanatory model comprising 9 factors connected by 16 hypotheses. To test the model, residents of Westminster and visitors to the area were surveyed, resulting in a total of 212 valid responses. The responses were used to test a structural equation model, using confirmatory factor analysis. The results of the analysis indicated that Awareness of the scheme; Perceived Ease of Use; Perceived Usefulness; Cost saving; Perceived Privacy and Perceived Security all had a direct impact on Usage, with Awareness being the most influential factor. The results also highlighted the fact that, despite efforts by Westminster Council to publicise the scheme, 74% of respondents had little awareness of it, suggesting the need for improved publicity.

SRSP: A Secure and Reliable Smart Parking Scheme With Dual Privacy Preservation

Finding an empty parking lot in a downtown or busy area is difficult and time consuming. Smart parking services enable vehicles to obtain real-time parking information, which has great potential to mitigate the parking problem. Compared with the existing parking methods, the cooperative parking information sharing based on vehicular crowdsourcing has lower cost and higher accuracy. However, vehicles face the threat of identity and trajectory privacy leakage. In order to provide secure and reliable parking service, we propose a secure and reliable smart parking scheme (SRSP) with dual privacy preservation. Specifically, a novel group signature technique can be equipped to achieve anonymous authentication among vehicles, parking server, and fog node. Meanwhile, the mix zone method combined with differential privacy can be utilized to hide the vehicles' trajectory. Moreover, message-lock encryption technique enables fog node to detect and delete duplicated reports to reduce the computational overhead of parking server. An incentive mechanism is proposed, which can not only reward contributing vehicles but also prevent the same vehicle from getting multiple rewards. In addition, the trust model is designed to evaluate the reliability of vehicles based on direct trust and recommendation trust. Finally, security analysis demonstrates that SRSP can achieve security objectives. Performance evaluation shows that SRSP has lower computational overhead compared with the existing schemes.

Prediction-based parking allocation framework in urban environments

ABSTRACT Finding a parking space is usually challenging in urban areas. The literature shows that 30% of traffic congestion is caused by searching for parking spaces, which results in unnecessary energy consumption and environmental pollution. With the development of sensor technologies, smart parking guidance systems provide users with a variety of real-time parking space information. However, users cannot know whether the target parking space remains available upon arrival. Moreover, parking resources may be under competition when multiple users target the same open parking space. In this research, we develop a new framework named prediction-based parking allocation (PPA) that provides smart parking services to users. In PPA, we first construct a prediction model of parking occupancy and predict the subsequent parking availabilities. Then, we design a matching-based allocation strategy to assign users to selected parking spaces. To the best of our knowledge, this is the first study that combines occupancy prediction and space allocation simultaneously to address smart parking issues. Finally, we collect a real dataset from the SFPark on-street parking system for performance evaluation. According to experimental results, PPA can effectively increase the parking success rate and reduce costs, fuel consumption, and carbon emissions.

Quality of service-based service selection in smart parking

Smartness in the existing environment is required for overall growth of any country. Government is putting tremendous effort and a huge sum of money for making cities smart to achieve smartness. A very first asset that needs to be made smart is smart parking system to avoid the traffic congestion. There are many service providers which are offering smart parking services, but there is no quality of service (QoS) framework available so far. So, for a customer point of view, it is very hard to select the best service provider and gain maximum satisfaction. So, in this paper, we have designed a QoS framework which consists of 33 metrics to evaluate a smart parking service. These parameters are identified from the user as well as vendors' perspective and help to select better service provider. We have also proposed multi criteria decision making (MCDM) approach technique for order preferences by similarity to ideal solution (TOPSIS) to select best smart parking service provider based on identified QoS. We have demonstrated our approach with the help of case studies.

Quality of service-based service selection in smart parking

Smartness in the existing environment is required for overall growth of any country. Government is putting tremendous effort and a huge sum of money for making cities smart to achieve smartness. A very first asset that needs to be made smart is smart parking system to avoid the traffic congestion. There are many service providers which are offering smart parking services, but there is no quality of service (QoS) framework available so far. So, for a customer point of view, it is very hard to select the best service provider and gain maximum satisfaction. So, in this paper, we have designed a QoS framework which consists of 33 metrics to evaluate a smart parking service. These parameters are identified from the user as well as vendors' perspective and help to select better service provider. We have also proposed multi criteria decision making (MCDM) approach technique for order preferences by similarity to ideal solution (TOPSIS) to select best smart parking service provider based on identified QoS. We have demonstrated our approach with the help of case studies.

A Real-Time Automatic Plate Recognition System Based on Optical Character Recognition and Wireless Sensor Networks for ITS.

Automatic License Plate Recognition has been a recurrent research topic due to the increasing number of cameras available in cities, where most of them, if not all, are connected to the Internet. The video traffic generated by the cameras can be analyzed to provide useful insights for the transportation segment. This paper presents the development of an intelligent vehicle identification system based on optical character recognition (OCR) method to be used on intelligent transportation systems. The proposed system makes use of an intelligent parking system named Smart Parking Service (SPANS), which is used to manage public or private spaces. Using computer vision techniques, the SPANS system is used to detect if the parking slots are available or not. The proposed system makes use of SPANS framework to capture images of the parking spaces and identifies the license plate number of the vehicles that are moving around the parking as well as parked in the parking slots. The recognition of the license plate is made in real-time, and the performance of the proposed system is evaluated in real-time.

Towards a Fog Enabled Efficient Car Parking Architecture

The automotive industry is growing day by day and personal vehicles have become a significant transportation resource now. With the rise in private transportation vehicles, getting a free space for parking one's car, especially in populated areas, has not only become difficult but also results in several issues, such as: (i) traffic congestion, (ii) wastage of time, (iii) environmental pollution, and most importantly (iv) unnecessary fuel consumption. On the other hand, car parking spaces in urban areas are not increasing at the same rate as the vehicles on roads. Therefore, smart car parking systems have become an essential need to address the issues mentioned above. Several researchers have attempted to automate the parking space allocation by utilizing state-of-the-art technologies. Significant work has been done in the domains of Wireless Sensor Networks (WSN), Cloud Computing, Fog Computing, and Internet of Things (IoT) to facilitate the advancements in smart parking services. Few researchers have proposed methods for smart car parking using the cloud computing infrastructures. However, latency is a significant concern in cloud-based applications, including intelligent transportation and especially in smart car parking systems. Fog computing, bringing the cloud computing resources in proximate vicinity to the network edge, overcomes not only the latency issue but also provides significant improvements, such as on-demand scaling, resource mobility, and security. The primary motivation to employ fog computing in the proposed approach is to minimize the latency as well as network usage in the overall smart car parking system. For demonstrating the effectiveness of the proposed approach for reducing the lag and network usage, simulations have been performed in iFogSim and the results have been compared with that of the cloud-based deployment of the smart car parking system. Experimental results exhibit that the proposed fog-based implementation of the efficient parking system minimizes latency significantly. It is also observed that the proposed fog-based implementation reduces the overall network usage in contrast to the cloud-based deployment of the smart car parking.

DESIGN AND STUDY OF A SMART PARK SYSTEM: UNIVERSITY OF KUFA AS A CASE STUDY

Finding a vacant parking space nowadays is time and fuel consuming. This problem may cause drivers to get frustrated and eventually improper parking will appear. The universities, in particular, are one of these places, which needs more attention for providing parking services. Therefore, this study has focused on finding the parking required for such facilities and the benefit of applying smart parking services there. The main campus of the University of Kufa has been evaluated by collecting parking data for both on-street and off-street parking. The results of field data show a clear lack of parking space for most of the faculties in the main campus. The required additional parking spaces are 260.This study has suggested using the smart parks. The model of smart park system has been introduced by this study as a solution to the parking problem, especially in the university and generally in other places. Arduino and ultrasonic sensors were used to detect the empty places in a park and display this status to the screen. The model has been applied at the park of College of Engineering with encouraging results.

A Survey of Smart Parking Solutions

Considering the increase of urban population and traffic congestion, smart parking is always a strategic issue to work on, not only in the research field, but also from economic interests. Thanks to information and communication technology evolution, drivers can more efficiently find satisfying parking spaces with smart parking services. The existing and ongoing works on smart parking are complicated and transdisciplinary. While deploying a smart parking system, cities, as well as urban engineers, need to spend a very long time to survey and inspect all the possibilities. Moreover, many varied works involve multiple disciplines, which are closely linked and inseparable. To give a clear overview, we introduce a smart parking ecosystem and propose a comprehensive and thoughtful classification by identifying their functionalities and problematic focuses. We go through the literature over the period of 2000–2016 on parking solutions as they were applied to smart parking development and evolution, and propose three macro-themes: information collection, system deployment, and service dissemination. In each macro-theme, we explain and synthesize the main methodologies used in the existing works and summarize their common goals and visions to solve current parking difficulties. Finally, we give our engineering insights and show some challenges and open issues. Our survey gives an exhaustive study and a prospect in a multidisciplinary approach. Besides, the main findings of the current state-of-the-art throw out recommendations for future research on smart cities and the Internet architecture.

Impacts of low citizen awareness and usage in smart city services: the case of London’s smart parking system

Smart city applications and services are increasingly considered as strategic means to cope with emerging global challenges such as climate change, pollution, the ageing population, and energy shortage. In particular, smart parking is a type of smart services used to improve traffic congestion and pollution within cities. Nevertheless, although smart city services are driven by advanced information technologies, their success is highly dependent on user engagement, which is historically problematic. This paper presents and discusses the results of a case study on the smart parking service in London. A questionnaire (involved a total of 212 local drivers) was adopted as the main data collection method. This was complemented by the collection and analysis of 470 online user comments left for the service. The results showed that London’s smart parking service may potentially help each driver to save an average of £68 (62.2 l) on petrol annually and reduce CO2 emissions by 238.14 kg per car per year. At city level, a smart parking system could help London save £183.6 million worth of petrol per year and reduce its annual CO2 emissions by 642,978 tons. However, public awareness, actual usage, and user satisfaction of this smart service are currently very low. These present substantial barriers to realise the potential economic and environmental benefits of the service. This paper concluded that further to the very technological efforts, local authorities and service providers need to make a stronger endeavour to enhance public engagement and user satisfaction towards smart services, in order to realise the promises of such solutions.

Urban Infrastructure Deployment for Wireless On-Street Parking Sensor Networks

The deployment strategy of wireless applications in metropolitan areas is essential for their efficiency and functionality. In this paper, we introduce and study a deployment strategy for wireless on-street parking sensor networks. We define a multiple-objective problem in our analysis, and solve it with two real-world street parking maps. We present the results on the trade-off among minimum energy consumption, sensing information delay and the amount of deployed mesh routers and Internet gateways, i.e., the cost of city infrastructure. These results yield engineering insights for appraising and deploying city mesh infrastructure to provide smart parking services to urban users. We also analyze these trade-offs to see how different urban layouts affect the optimal solutions.

A Wireless Sensor Network based Market Parking Scheme

Parking in major cities, especially around a market vicinity is not only limited but costly. Innovative parking systems to curb this phenomenon is required. This paper proposes a novel and strategic approach using wireless sensor networks (WSNs) as a solution. The WSNs consisting of sensor nodes are known for offering detection, sensing and communication services. The market parking scheme serves as smart parking service, for monitoring the state of the market parking garage. To function, each slot within the parking space is fit with a magnetic sensor node. The parking process is modelled as an Entry-Exit stochastic process. Vehicles identified as they approach using the Licence Plate Recognition (LPR) program. Post identification, Low-Energy Adaptive Clustering Hierarchy (LEACH) routing protocol of the WSNs is used to route the information concerning the parking garage to the base station. The Performance and evaluation of this proposed innovatory system, proves its efficiency.

Transit-Based Smart Parking in the San Francisco Bay Area, California: Assessment of User Demand and Behavioral Effects

This paper presents early findings from an application of advanced parking technologies to increase effective parking capacity at a transit station during the first half of 2004 in the San Francisco Bay Area, California. It begins with an extensive review of the literature related to transit-based smart parking management systems to illustrate the range of system configurations and their potential travel, economic, and environmental effects. Two important conclusions from this review are that the lack of parking spaces at transit stations may be a significant constraint to transit use and that pretrip information and perhaps en route information on parking availability at transit stations may increase transit use. A survey of commuters at the Rockridge Bay Area Rapid Transit (BART) station was implemented to gain insight into parking information needs, the travel effects of a new monthly paid parking program, and the potential travel effects of a smart parking service. First, it was found that a potential market existed for a daily paid parking information service among current and new riders with relatively high incomes, high automobile availability, and variable work locations and schedules. Second, the current monthly reserved paid parking service might have increased the frequency of BART use among subscribers, but it might not have reduced net auto travel for two reasons: subscribers appear to have switched to BART for their main commute mode from carpool, bus, and bike modes; and subscribers might have increased their use of the drive-alone mode to access the BART station.

Transit-Based Smart Parking in the San Francisco Bay Area, California

This paper presents early findings from an application of advanced parking technologies to increase effective parking capacity at a transit station during the first half of 2004 in the San Francisco Bay Area, California. It begins with an extensive review of the literature related to transit-based smart parking management systems to illustrate the range of system configurations and their potential travel, economic, and environmental effects. Two important conclusions from this review are that the lack of parking spaces at transit stations may be a significant constraint to transit use and that pretrip information and perhaps en route information on parking availability at transit stations may increase transit use. A survey of commuters at the Rockridge Bay Area Rapid Transit (BART) station was implemented to gain insight into parking information needs, the travel effects of a new monthly paid parking program, and the potential travel effects of a smart parking service. First, it was found that a potential market existed for a daily paid parking information service among current and new riders with relatively high incomes, high automobile availability, and variable work locations and schedules. Second, the current monthly reserved paid parking service might have increased the frequency of BART use among subscribers, but it might not have reduced net auto travel for two reasons: subscribers appear to have switched to BART for their main commute mode from carpool, bus, and bike modes; and subscribers might have increased their use of the drive-alone mode to access the BART station.