The collection of necessary data and the provision of real time information to passengers is a keyissue on current cities for both traffic managers and travelers. This paper presents a novelmethodology for estimating travel times in dense urban road networks using point-to-pointdetectors. The aim is to fill in the existing gap related to the weakness of existing travel timeestimation methodologies, which are based on point-to-point detector devices. Bluetooth isconsidered as one of the less expensive technologies for estimating travel times, but while on theone hand travel times data collection can be considered as easy, data filtering and data correctionrequire a demanding methodology, which if not correctly applied may result in inaccurate resultsas compared to other methods. The main difficulty of data processing is to identify the correct setof MAC addresses for estimating the travel times, especially in dense urban networks, wherethree main error sources exist: the existence of various transport modes (private vehicles, buses,pedestrians, bicycles etc.), the existence of more than one possible path between two Bluetoothdetector devices and the existence of stops or trips ending between two Bluetooth devices. Theseerror sources create outliers that need to be identified and taken into account. The results of theproposed methodology confirm that outliers are eliminated, as shown by a case study involving10 Bluetooth detectors, installed at major intersections of Thessaloniki’s central business district.The presented methodology is useful for application related to real-time data provision foradvanced traveler information services as well as for underlying traffic models.
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