A Conceptual Framework for Forecasting Car Driver’s On-Street Parking Decisions

Khaliq, Annum; Janssens, Davy; Wets, Geert

doi:10.1016/j.trpro.2018.12.175

Cited by 19 publications

(7 citation statements)

References 22 publications

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“…Parking models aim to describe and evaluate phenomena of parking, such as parking-choice behavior and cruising-for-parking. They have been explored by the research community for many decades (18,50,51). In such models, parking-related data are commonly used and described as variables in mathematical representations, for example, by using such variables to describe relationships between parking supply and parking demand.…”

Section: Content Perspectivementioning

confidence: 99%

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

Lubrich

2021

Transportation Research Record: Journal of the Transportation R

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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.

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Section: Content Perspectivementioning

confidence: 99%

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

Lubrich

2021

Transportation Research Record: Journal of the Transportation R

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“…When drivers are driving towards their destination they enter streets in search of parking opportunities while considering the existing road conditions and parking policies. Based on car drivers' onstreet parking choices can be abstracted using the following framework [10].  How to pay for parking: There are several techniques available for payment to drivers, including credit card, coins and cashless parking with PayStay  Pay by phone with PayStay  Handy hints for using PayStay  Pay with credit card  Coins using a parking meter or ticket machine…”

Section: Iiiframework Of On Street Smartmentioning

confidence: 99%

Detecting Predominance of on-Street Parking Payment Schemes by Means of Linear Regression

Waheed,

Krishna

2020

IJRTE

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—On street parking is one of the important and crucial components of urban traffic and transportation system. Allocation of parking space on street is major reason for traffic congestion. Optimizing traffic congestion and facilitating on street parking is a long stand issue. According to urban environment it is expected that car drivers prefers parking space based on road conditions, speed limit and surrounding activities and availability of parking space. The other major components to be ponder while searching parking space is payment method used while parking the car. This paper investigates car driver’s behaviors in selecting parking payment schemas, visualized data as well predicted via machine learning technique of linear regression analysis on the open data set of On-street Car Parking Meters with Location of City of Melbourne's in the Australian.

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“…This model parameter can be dynamically adjusted. Driving behavior and parking search are complex processes [37][38][39] and several studies have applied realistic behaviors [3,13,19,27], even considering recent trends like driver-less vehicles [40] or specific contexts like a city center [41] and university campuses with specific policies and notable parking supply shortages [42]. We chose two simple parking search behaviors for our model because obtaining an approximate parking occupancy, rather than the most realistic one, was enough for our simulator goal.…”

Section: Search Behaviormentioning

confidence: 99%

An Occupancy Simulator for a Smart Parking System: Developmental Design and Experimental Considerations

Mendoza-Silva

Gould

Montoliu

et al. 2019

IJGI

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This paper presents the development of a parking occupancy simulator to support a smart parking system. The simulator uses an agent-based approach to model drivers who follow activity plans and who may or may not use the smart parking system. We illustrate how the process of developing our simulator helped in the design and implementation of the smart parking system components. The paper also shows how the simulator was used to study the possible usage of the smart parking system in a university campus, foreseeing (1) support for the smart parking system’s overall suitability, (2) reservation guarantee violation problems, and (3) the value of using total traveled distance as a metric for the smart parking evaluation. The experience presented in this paper may prove valuable to teams planning the development of a smart parking system for similar contexts.

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A Conceptual Framework for Forecasting Car Driver’s On-Street Parking Decisions

Cited by 19 publications

References 22 publications

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

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

Detecting Predominance of on-Street Parking Payment Schemes by Means of Linear Regression

An Occupancy Simulator for a Smart Parking System: Developmental Design and Experimental Considerations

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