The sensor location problem: methodological approach and application

    Evangelos Mitsakis Affiliation
    ; Evangelia Chrysohoou Affiliation
    ; Josep M. S. Grau Affiliation
    ; Panagiotis Iordanopoulos Affiliation
    ; Georgia Aifadopoulou Affiliation


The sensor location problem is of particular importance when planning the allocation of limited field equipment intended to be used for advanced traffic management systems and traveller information services. The locations within a network that satisfy specific goals need to be carefully selected, based on predefined goals related to the effective collection of data and the subsequent estimation of traffic related information. The detection of traffic volumes is mainly associated with two purposes, the travel time and the Origin–Destination (O–D) trip matrix estimation. In this context, this paper presents a quadratic programing model, able to determine the optimal location of tracking sensors. The model is implemented in the urban road network of the city of Thessaloniki (Greece) in which specific number of sensors is installed and utilized for real-time travel time information provision. The proposed methodology models the sensor location problem under the general framework of a set covering problem, which is one of the most popular optimization problems and has been applied in many industrial problems. The results of the case study in Thessaloniki reveal that the proposed model defines the optimal location of the limited number of sensors in such a way that the network, which is created having all sensors as origin or destination of all possible paths, represents to great extent (87% of the traffic flow along the major paths) the traffic volumes of the whole road network of the city.

First published online: 11 Jan 2017

Keyword : sensor location, travel time estimation, BT sensors, advanced traveller information services, point-to-point sensors

How to Cite
Mitsakis, E., Chrysohoou, E., Grau, J. M. S., Iordanopoulos, P., & Aifadopoulou, G. (2017). The sensor location problem: methodological approach and application. Transport, 32(2), 113–119.
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May 30, 2017
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