Journal of Industrial Management Perspective

Journal of Industrial Management Perspective

Developing a Model to Optimize Maximum Coverage of Roadside Units Placement in Vehicular Ad–hoc Network for Intelligent Transportation System

Document Type : Original Article

Authors
Ali Mohaghar 1
Hojjat Heydarzadeh Moghaddam 2
Rohollah Ghasemi 3
1 Professor, Department of Industrial management, Faculty of management, University of Tehran.
2 Ph.D. Candidate, Department of Industrial management, Alborz Campus, University of Tehran.
3 Ph.D, Department of Industrial management, Faculty of management, University of Tehran.
10.48308/jimp.13.2.211
Abstract
Roadside units are crucial elements of intelligent transportation systems that provide vehicle–vehicle and vehicle–equipment information communication. Due to the high cost of installation, the deployment of roadside units is the most critical. Aim of this study is developing a model to optimize of roadside units placement to achieve maximum coverage. A multi–objective mathematical model presented, based on the three main parameters. These parameters are traffic volume, incident rate and adjacency to important centers, which determine for alternative points. The maximum coverage problem is NP–hard. Consequently, conventional mathematical methods are not accurate for large scale problem. A meta–heuristic method based on the greedy algorithm was developed which conciders marking points as definitive–select or non–selectable. Result of the model were evaluated through testing of three scenarios, 200, 500 and 1000 meters coverage in District 5 of Tehran by using MATLAB and the best one, 1000 meters was chosen with 71% coverage. Observations showed the effect of various parameters such as equipment coverage radius, number of equipment and budget on the results of distribution. This algorithm makes it possible to solve the problem on a large scale by using the geolocation of the candidate points.
Keywords
Roadside Units
Intelligent Transportation System
VANET
Maximum SET Coverage Problem
Location
Subjects
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