Density-Based Statistical Clustering: Enabling Sidefire Ultrasonic Traffic Sensing in Smart Cities
Joint Authors
Lücken, Volker
Voss, Nils
Schreier, Julien
Baag, Thomas
Gehring, Michael
Raschen, Matthias
Lanius, Christian
Leupers, Rainer
Ascheid, Gerd
Source
Journal of Advanced Transportation
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-01-04
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Traffic routing is a central challenge in the context of urban areas, with a direct impact on personal mobility, traffic congestion, and air pollution.
In the last decade, the possibilities for traffic flow control have improved together with the corresponding management systems.
However, the lack of real-time traffic flow information with a city-wide coverage is a major limiting factor for an optimum operation.
Smart City concepts seek to tackle these challenges in the future by combining sensing, communications, distributed information, and actuation.
This paper presents an integrated approach that combines smart street lamps with traffic sensing technology.
More specifically, infrastructure-based ultrasonic sensors, which are deployed together with a street light system, are used for multilane traffic participant detection and classification.
Application of these sensors in time-varying reflective environments posed an unresolved problem for many ultrasonic sensing solutions in the past and therefore widely limited the dissemination of this technology.
We present a solution using an algorithmic approach that combines statistical standardization with clustering techniques from the field of unsupervised learning.
By using a multilevel communication concept, centralized and decentralized traffic information fusion is possible.
The evaluation is based on results from automotive test track measurements and several European real-world installations.
American Psychological Association (APA)
Lücken, Volker& Voss, Nils& Schreier, Julien& Baag, Thomas& Gehring, Michael& Raschen, Matthias…[et al.]. 2018. Density-Based Statistical Clustering: Enabling Sidefire Ultrasonic Traffic Sensing in Smart Cities. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1181847
Modern Language Association (MLA)
Lücken, Volker…[et al.]. Density-Based Statistical Clustering: Enabling Sidefire Ultrasonic Traffic Sensing in Smart Cities. Journal of Advanced Transportation No. 2018 (2018), pp.1-15.
https://search.emarefa.net/detail/BIM-1181847
American Medical Association (AMA)
Lücken, Volker& Voss, Nils& Schreier, Julien& Baag, Thomas& Gehring, Michael& Raschen, Matthias…[et al.]. Density-Based Statistical Clustering: Enabling Sidefire Ultrasonic Traffic Sensing in Smart Cities. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1181847
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181847