ACOp: An Algorithm Based on Ant Colony Optimization for Parking Slot Detection

Balzano, Walter; Stranieri, Silvia

doi:10.1007/978-3-030-15035-8_81

Cited by 18 publications

(2 citation statements)

References 22 publications

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“…In [10], the authors provide a large survey on smart parking modeling, solutions, and technologies as well as identify challenges and open issues. Algorithmic solutions have been also proposed in the VANET research field, see for example [18,16,17,6,5,4]. Less common is the use of game-theoretic approaches to address the parking problem.…”

Section: Related Workmentioning

confidence: 99%

The Parking Problem: A Game-Theoretic Solution

Calise¹,

Murano²,

Stranieri³

2022

Preprint

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In this paper, we propose a game-theoretic solution to the parking problem, by exploiting a strategic-reasoning approach for multi-agent systems. Precisely, cars are modeled by agents interacting among them in a multi-player game setting, whose aim is to get a free slot parking-place satisfying their own constraints. The overall assignment is then given as a Nash equilibrium solution. We come up with an algorithm (and its implementation in a tool) that works in quadratic time. We give evidence of the benefits of our approach by running our tool on a large hospital parking space.

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Section: Related Workmentioning

confidence: 99%

The Parking Problem: A Game-Theoretic Solution

Calise¹,

Murano²,

Stranieri³

2022

Preprint

Self Cite

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“…Balzano and Stranieri 120 have proposed an ACO‐based algorithm for parking slot detection known as ACOp for VANETs. It aims to find a free parking slot efficiently.…”

Section: Applicability Of Nature‐inspired Algorithms In Iovmentioning

confidence: 99%

A survey on nature‐inspired algorithms and its applications in the Internet of Vehicles

Sharma

Kaushik

2021

Int J Communication

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The concept of the Internet of Vehicles (IoV) was evolved to cater to the increasing demands of emerging and advanced vehicular applications such as intelligent transportation systems (ITS). IoV plays a vital role in the development of smart cities and smart transportation. As IoV involves real-time data, so efficient routing mechanisms, as well as secure protocols, are very much needed to enhance the efficiency and security of the IoV network. In the existing literature, numerous researchers have focused on enhancing the efficiency of the IoV network. However, there still exist some flaws keeping in view the new security vulnerabilities that keep on emerging. So, there is a need to optimize the capabilities of existing frameworks for dealing with such issues.Nature-inspired algorithms are a category of powerful tools to solve problems of optimization. In this first of its kind state-of-the-art study, the potential of applicability of nature-inspired algorithms in IoV networks for improving the overall performance of IoV is explored. First, various categories of natureinspired algorithms are presented to make the readers well acquainted with the concepts of nature-inspired algorithms. Different nature-inspired algorithms having their applicability in different aspects of IoV are studied with a special focus on security, routing, and parking space management for strengthening the existing IoV network. Various open issues and research challenges in the use of different nature-inspired algorithms in IoV are also presented. Based upon the study conducted, it has been analyzed that natureinspired algorithms can optimize the overall performance of IoV networks.

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