Notice of Violation of IEEE Publication Principles: Smart Parking Space Allocation Based on a Cooperative System

Abstract

Notice of Violation of IEEE Publication Principles<br><br> "Smart Parking Space Allocation Based on a Cooperative System"<br> by Sofiene Abidi, Arben Cela, Rene Natowicz<br> in the Proceedings of the International Conference in Engineering Applications (ICEA), October 2019<br><br> After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE’s Publication Principles.<br><br> This paper contains portions of text from the paper(s) cited below. A credit notice is used, but due to the absence of quotation marks or offset text, copied material is not clearly referenced or specifically identified.<br><br> "On-The-Fly Curbside Parking Assignment"<br> by Abeer Hakeem, Narain Gehani, Xiaoning Ding, Reza Curtmola, Cristian Borcea<br> in the Proceedings of the 8th EAI International Conference on Mobile Computing, Applications and Services, December 2016<br><br> <br/> Advanced research solutions for `smart parking' involve the use of vehicular cooperation to share parking information via vehicular ad hoc network. Solutions can be opportunistic when looking for parking spaces, which can increase the competing level and in turn, increase the searching time. Considering the parking resource limitations, we need to take vehicular cooperation to a next level by relaxing the constraints of cooperating drivers and so expanding the feasibility of the search space. This paper presents smart parking model Based on a Cooperative System; a Reward System that allows better use of resources especially during peak hours, by relaxing the constraints of cooperating drivers and so contributing to parking assignment efficiency increase. Subscribed drivers in the Reward System will be able to manage their delays induced by the traffic, since a readjustment of the parking space allocation it will be made dynamically by the system, based on the driver remaining travel time to his destination. In order to work with large-scale parking optimization, a real case mobility scenario is simulated using a SUMO/MATLAB framework. Based on simulation results, compared with non-cooperative parking processes, our model reduces the average parking rate failure and the traveling cost, whereas the overall parking capacity is more efficiently utilized.