Abstract
Sustainable mobility requires a better management of the available infrastructure resources. To achieve this goal, it is necessary to obtain accurate data about road usage, in particular in urban areas. Although a variety of sensor alternates for urban traffic exist, they usually require extensive investments in the form of construction works for installation, processing means, etc. Wireless Sensor Networks (WSN) are an alternative to acquire urban traffic data, allowing for flexible, easy deployment. Together with the use of the appropriate sensors, like Bluetooth identification, and associate processing, WSN can provide the means to obtain in real time data like the origin-destination matrix, a key tool for trend monitoring which previously required weeks or months to be completed. This paper presents a system based on WSN designed to characterize urban traffic, particularly traffic trend monitoring through the calculation of the origin-destination matrix in real time by using Bluetooth identification. Additional sensors are also available integrated in different types of nodes. Experiments in real conditions have been performed, both for separate sensors (Bluetooth, ultrasound and laser), and for the whole system, showing the feasibility of this approach.
Highlights
Intelligent Transportation Systems (ITSs) are a set of solutions to improve transportation efficiency and safety [1]
O-D matrixes have been obtained using counting sensors and user surveys [32]. Regarding their computation by ITS-Wireless Sensor Network (WSN) systems, some references such as Tornero et al [33] make the O-D matrix calculation supposing that all the vehicles have some kind of identifier which can be recognized by the system
The ultrasound node acts as a non-intrusive, vehicle counting, smart sensor. It is built around the basic module shared by all the transmitter nodes and a Smartcities board developed by Libelium and which incorporates the electronics needed to interface with the Maxbotix XL-MaxSonar-WR1 ultrasound sensor (Figure 4)
Summary
Intelligent Transportation Systems (ITSs) are a set of solutions to improve transportation efficiency and safety [1]. Traffic sensors can be classified into two large groups according to their installation [7]: Intrusive sensors: they must be installed on the road, so they are expensive and usually require traffic to be shut for their installation They give a high precision in counting vehicles. O-D matrixes have been obtained using counting sensors and user surveys [32] Regarding their computation by ITS-WSN systems, some references such as Tornero et al [33] make the O-D matrix calculation supposing that all the vehicles have some kind of identifier which can be recognized by the system. The information obtained by its sensors comprises vehicle counting, MAC addresses of vehicles’ Bluetooth devices, gases concentrations and environmental parameters like noise or dust. The article shows how to obtain the trends of origins and destinations relying on the proposed system and it describes some of the experiments made and presents the conclusions
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