Determination of the parking place availability using manual data collection enriched by crowdsourced in-vehicle data

Margreiter, Martin; Orfanou, Foteini; Mayer, P.

doi:10.1016/j.trpro.2017.05.432

Cited by 12 publications

(9 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although the numbers presented in this paper (IBM, 2011;Margreiter et al, 2017), refer to large cities, the problem is currently found at every level, regardless of city size; within private institutions premises, there are different but equally pressing problems. IoT techniques, as mentioned by Salpietro et al (2015) open up new possibilities to take advantage of.…”

Section: Discussionmentioning

confidence: 98%

Where to park? Architecture and implementation of an empty parking lot, automatic recognition system

et al. 2019

View full text Add to dashboard Cite

The traffic congestion present in practically every city has, among its increasing factors, the unavailability of enough parking spaces. A typical driver invests a considerable part of the total trip time looking for a free space where to park his vehicle; in many cases, this leads to delays and the consequent discomfort due to the undesired consequences of the generated tardiness. For this problem it is possible to find partial palliative solutions, minimizing the time spent searching for parking by applying Internet of Things techniques, oriented to smart cities and buildings. This research has been focused on finding an appropriate computer architecture that will allow the implementation of a distributed system, which, thanks to the use of computer vision and machine learning techniques, detects free parking spaces inside a parking lot, and provides real time information to the driver, allowing him to go as directly as possible to a vacant parking space.

show abstract

Section: Discussionmentioning

confidence: 98%

Where to park? Architecture and implementation of an empty parking lot, automatic recognition system

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Various sensor techniques are discussed in relation to use cases, advantages versus disadvantages, and prerequisites for deployment (7,14,21). As an alternative to stationary sensors or cameras, some approaches are based on sensors from a collective of moving vehicles to detect onstreet parking occupancy (42)(43)(44). Instead of via direct sensing, some references propose to indirectly derive occupancy information from other, existing data sources, such as parking meter transaction data (38) or smart phone movements (45).…”

Section: Technical Perspectivementioning

confidence: 99%

Smart Parking Systems: A Data-Oriented Taxonomy and a Metadata Model

Lubrich

2021

Transportation Research Record

View full text Add to dashboard Cite

Smart parking systems (SPS) represent an evolving and heterogeneous field of approaches and applications in parking management. One commonality is that all present systems deal with digital data related to the parking domain, such as data about parking infrastructure, parking demand, transactions, and similar. Data offerings of SPS seem to provide essential benefits for actors in parking space management, as long as they can be discovered and assessed efficiently. This paper presents mechanisms for the discovery and assessment of SPS data offerings. First, a taxonomy is developed via an inductive approach, based on a review of existing approaches to categorizing such data offerings. The taxonomy represents a hierarchical classification system, looking at functional, technical, and content perspectives of SPS data. This taxonomy is further integrated and formalized into a metadata model, allowing structured and harmonized descriptions about data offerings of individual SPS. The metadata model is built on established metadata frameworks, namely the Resource Description Framework (RDF). For reasons of reusability and interoperability, it also adopts existing metadata vocabularies from the domain of internet data catalogs. This work intends to make the data offerings of SPS assessable and comparable for potential SPS users, namely actors in parking space management. It also provides a foundation for integrating the various forms and technologies of current SPS deployments. Such integration is missing so far, according to some other authors, and is addressed in this work by an interoperable metadata approach.

show abstract

“…The classification listed in the previous table shows that sensors are not always combined to produce smart parking solutions. Some proposals, like that in [51], do not specify a type of sensor, but the authors assume that a vehicle might contain cameras, ultrasonic, and radar sensors. Other approaches, like [52], specify that a TSOP 1738 infrared sensor is in charge of detecting the presence or absence of a vehicle.…”

Section: Types Of Sensorsmentioning

confidence: 99%

Smart Parking: A Literature Review from the Technological Perspective

et al. 2019

View full text Add to dashboard Cite

The development and high growth of the Internet of Things (IoT) have improved quality of life and strengthened different areas in society. Many cities worldwide are looking forward to becoming smart. One of the most popular use cases in smart cities is the implementation of smart parking solutions, as they allow people to optimize time, reduce fuel consumption, and carbon dioxide emissions. Smart parking solutions have a defined architecture with particular components (sensors, communication protocols, and software solutions). Although there are only three components that compose a smart parking solution, it is important to mention that each component has many types that can be used in the deployment of these solutions. This paper identifies the most used types of every component and highlights usage trends in the established analysis period. It provides a complementary perspective and represents a very useful source of information. The scientific community could use this information to decide regarding the selection of types of components to implement a smart parking solution. For this purpose, herein we review several works related to smart parking solutions deployment. To achieve this goal, a semi-cyclic adaptation of the action research methodology combined with a systematic review is used to select papers related to the subject of study. The most relevant papers were reviewed to identify subcategories for each component; these classifications are presented in tables to mark the relevance of each paper accordingly. Trends of usage in terms of sensors, protocols and software solutions are analyzed and discussed in every section. In addition to the trends of usage, this paper determines a guide of complementary features from the type of components that should be considered when implementing a smart parking solution.

show abstract

Determination of the parking place availability using manual data collection enriched by crowdsourced in-vehicle data

Cited by 12 publications

References 3 publications

Where to park? Architecture and implementation of an empty parking lot, automatic recognition system

Where to park? Architecture and implementation of an empty parking lot, automatic recognition system

Smart Parking Systems: A Data-Oriented Taxonomy and a Metadata Model

Smart Parking: A Literature Review from the Technological Perspective

Contact Info

Product

Resources

About