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CBPRS: A City Based Parking and Routing System

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TLDR
A City Based Parking Routing System (CBPRS) that monitors and reserves parking places for CBPRS participants within a city and guides vehicles using an ant based distributed hierarchical routing algorithm to their reserved parking place is proposed.
Abstract
textNavigational systems assist drivers in finding a route between two locations that is time optimal in theory but seldom in practice due to delaying circumstances the system is unaware of, such as traffic jams Upon arrival at the destination the service of the system ends and the driver is forced to locate a parking place without further assistance We propose a City Based Parking Routing System (CBPRS) that monitors and reserves parking places for CBPRS participants within a city The CBPRS guides vehicles using an ant based distributed hierarchical routing algorithm to their reserved parking place Through means of experiments in a simulation environment we found that reductions of travel times for participants were significant in comparison to a situation where vehicles relied on static routing information generated by the well known Dijkstra’s algorithm Furthermore, we found that the CBPRS was able to increase city wide traffic flows and decrease the number and duration of traffic jams throughout the city once the number of participants increased

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Citations
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A Survey of Smart Parking Solutions

TL;DR: A smart parking ecosystem is introduced and a comprehensive and thoughtful classification by identifying their functionalities and problematic focuses is proposed, and three macro-themes are proposed: information collection, system deployment, and service dissemination.
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Parking slot assignment games

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Reaching Available Public Parking Spaces in Urban Environments Using Ad Hoc Networking

TL;DR: This work forms the question at hand as a Time-Varying Travelling Salesman problem and proposes an approach for computing the route that a vehicle must traverse in order to visit all parking spaces known to be available, taking into account the limited computational resources of vehicles.
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How likely am I to find parking? – A practical model-based framework for predicting parking availability

TL;DR: A model-based practical framework to predict future occupancy from historical occupancy data alone is proposed and it is found that this approach delivers equal or better performance, but requires a computation time that is orders of magnitude less to tune and train the model.
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Opportunistically assisted parking service discovery: Now it helps, now it does not

TL;DR: This paper explores the way the discovery of service can be facilitated or not by utilizing service location information that is opportunistically disseminated primarily by the service consumers themselves, and outlines models providing analytical insights to the behaviour of the centralized approach.
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