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This work was partially supported by Comunidad de Madrid, through the scheme "Convenio Plurianual con la Universidad Politecnica de Madrid en la linea de actuacion Programa de Excelencia para el Profesorado Universitario".

Analysis of institutional authors

Pozo, RfAuthorGonzalez, AbrAuthorWilby, Mark RichardAuthorDiaz, JjvCorresponding Author

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July 6, 2022
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Analysis of Extended Information Provided by Bluetooth Traffic Monitoring Systems to Enhance Short-Term Level of Service Prediction

Publicated to:Sensors. 22 (12): 4565- - 2022-06-01 22(12), DOI: 10.3390/s22124565

Authors: Fernandez Pozo, Ruben; Rodriguez Gonzalez, Ana Belen; Wilby, Mark Richard; Vinagre Diaz, Juan Jose

Affiliations

Univ Politecn Madrid, Dept Math Appl Informat & Commun Technol, Madrid 28040, Spain - Author

Abstract

Bluetooth monitoring systems (BTMS) have opened a new era in traffic sensing, providing a reliable, economical, and easy-to-deploy solution to uniquely identify vehicles. Raw data from BTMS have traditionally been used to calculate travel time and origin-destination matrices. However, we could extend this to include other information like the number of vehicles or their residence times. This information, together with their temporal components, can be applied to the complex task of forecasting traffic. Level of service (LOS) prediction has opened a novel research line that fulfills the need to anticipate future traffic states, based on a standard link-based variable, accepted for both researchers and practitioners. In this paper, we incorporate BTMS's extended variables and temporal information to an LOS classifier based on a Random Undersampling Boost algorithm, which is proven to efficiently respond to the data unbalance intrinsic to this problem. By using this approach, we achieve an overall recall of 87.2% for up to 15-min prediction horizons, reaching 96.6% predicting congestion, and improving the results for the intermediate traffic states, especially complex given their intrinsic instability. Additionally, we provide detailed analyses on the impact of temporal information on the LOS predictor's performance, observing improvements up to a separation of 50 min between last features and prediction horizons. Furthermore, we study the predictor importance resulting from the classifiers to highlight those features contributing the most to the final achievements.

Keywords

AlgorithmsBluetoothBluetooth traffic monitoring systemClassification (of information)FlowForecastingLevel of serviceModelMonitoringMonitoring systemNeural-networkPrediction horizonSpeed predictionTemporal component of traffic informationTemporal components of traffic informationTemporal informationTraffic congestionTraffic informationTraffic monitoring systemsTraffic predictionTraffic stateTravel timeTravel-time

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Sensors due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2022, it was in position , thus managing to position itself as a Q1 (Primer Cuartil), in the category Analytical Chemistry.

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-11-03:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 1 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.

Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (FERNÁNDEZ POZO, RUBÉN) and Last Author (Vinagre Díaz, Juan José).

the author responsible for correspondence tasks has been Vinagre Díaz, Juan José.