Long-range, Seamless Traffic Density Monitoring using Fibre Optic Acoustic Sensing

Abstract

Accurate real-time traffic sensing is of key importance, especially in the urban environment to be able to optimise traffic flow by intelligent traffic systems (ITS). Often the high density of traffic sensors, needed to achieve an accurate real-time monitoring of important arterial roads, is difficult to implement due to technical contraints or because of high installation cost. Furthermore, existing traffic sensing technology uses sensors that are only able to measure traffic flow on a cross-section of the road where they are installed (typically on a junction), giving no information on the situation in between. An alternative "seamless" measuring technology, is to use floating car data, with Google Maps being the most prominant example. This technology allows to derive traffic information over wide road sections, however it is unable to deliver real- time information, and it relies on the “cooperation” of the data providers (the fleet owner or the mobile phone users). Fiber optic acoustic sensing (FOAS) is a new alternative technology that allows a seamless, real-time monitoring of the road traffic situation over large distances of up to 50 km using the existing telecom fiber optic cable infrastructure. In our previous work we presented an algorithm and results for traffic flow and average speed computation from FOAS raw data at a specific location along a highway and compared it to reference traffic data [1],[2]. In this paper we demonstrate the potential of the seamless nature of the technique by evaluating the traffic density over a length of 25 km of the monitored highway for different days and times of the day