Paper Info
Title
Street Sensors Set Selection through Road Network Modeling and Observability Measures
Abstract
Nowadays, vehicle flow monitoring, model-based traffic management and congestion prediction are becoming fundamental elements for the realization of the Smart City paradigm. These tasks usually require wide sensor deployments, but, due to economical, practical and environmental constraints, they must be accomplished with a limited number of sensors. Thus motivated, this work addresses the sensors selection problem for urban street monitoring, by employing vector maps as the basic information and considering the placement of at most one sensor along each road, but with a fixed number of available devices. To solve the problem, the concept of system observability is exploited as the criterion for optimal sensor placement, specifically related to the capability of estimating the traffic flow in each road using the available output measurements. In this framework, different integer nonlinear programming problems are proposed, whose solutions are studied and analyzed by means of numerical simulations on a real case scenario.
Year
DOI
Venue
2019
10.1109/MED.2019.8798593
2019 27th Mediterranean Conference on Control and Automation (MED)
Keywords
Field
DocType
economical constraints,practical constraints,environmental constraints,sensors selection problem,urban street monitoring,vector maps,system observability,optimal sensor placement,traffic flow,street sensors set selection,vehicle flow monitoring,model-based traffic management,congestion prediction,wide sensor deployments,integer nonlinear programming problems,smart city paradigm
Observability,Traffic flow,Congestion prediction,Computer science,Flow (psychology),Control engineering,Nonlinear mixed integer programming,Smart city,Network model,Vector map
Conference
ISSN
ISBN
Citations 
2325-369X
978-1-7281-2804-7
0
PageRank 
References 
Authors
0.34
2
3
Name
Order
Citations
PageRank
Luca Varotto102.03
Alessandra Zampieri200.34
Angelo Cenedese39227.71