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Road traffic estimation using Bluetooth sensors

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The Bluetooth standard is a low-cost, very popular communication protocol offering a wide range of applications in many fields. In this paper, a novel system for road traffic estimation using Bluetooth sensors has been presented. The system consists of three main modules: filtration, statistical analysis of historical, and traffic estimation and prediction. The filtration module is responsible for the classification of road users and detecting measurements that should be removed. Traffic estimation has been performed on the basis of the data collected by Bluetooth measuring devices and information on external conditions (e.g., temperature), all of which have been gathered in the city of Bielsko-Biala (Poland). The obtained results are very promising. The smallest average relative error between the number of cars estimated by the model and the actual traffic was less than 10%.
Słowa kluczowe
Rocznik
Tom
Strony
15--25
Opis fizyczny
Bibliogr. 17 poz.
Twórcy
autor
  • Faculty of Biomedical Engineering, The Silesian University of Technology, Roosevelta 40, 41-800 Zabrze, Poland.
autor
  • Faculty of Biomedical Engineering, The Silesian University of Technology, Roosevelta 40, 41-800 Zabrze, Poland
  • Pattern Recognition Group, University of Siegen, Hoelderlinstr. 3, D-57076 Siegen, Germany
autor
  • Faculty of Biomedical Engineering, The Silesian University of Technology, Roosevelta 40, 41-800 Zabrze, Poland.
Bibliografia
  • 1. Middleton Dan, Hassan Charara, Ryan Longmire. 2009. Alternative Vehicle Detection Technologies for Traffic Signal Systems: Technical Report. The Texas A&M University System, College Station: Texas Transportation Institute.
  • 2. Bolla Raffaele, Franco Davoli. 2000. “Road traffic estimation from location tracking data in the mobile cellular network.” IEEE Wireless Communications and Networking Conference: 1107-1112. 23-28 September 2000, Chicago, USA. ISBN: 0-7803-6596-8.
  • 3. Promnoi Sunisa, Poj Tangamchit, Wasan Pattara-Atikom. 2008. “Road traffic estimation based on position and velocity of a cellular phone.” Eighth International Conference on ITS Telecommunications: 108-111. 24 October 2008, Phuket, Thailand. ISBN: 978-1- 4244-2857-1.
  • 4. Lin Bon-Yen, Chen Chi-Hua, Lo Chi-Chun. 2011. “A traffic information estimation model using periodic location update events from cellular network.” In: R. Chen, ed., Intelligent Computing and Information Science, Vol. 135: Communications in Computer and Information Science: 72-77. Springer: Berlin Heidelberg. DOI: http://doi.org/10.1007/978-3-642-18134-4_12.
  • 5. Valerio Danilo, Tobias Witek, Fabio Ricciato, Rene Pilz, Werner Wiedermann. 2009. “Road traffic estimation from cellular network monitoring: a hands-on investigation.” In: IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications: 3035-3039. 13-16 September 2009, Tokyo, Japan. ISBN: 978-1-4244- 5122-7.
  • 6. Mao Ruixue, Guoqiang . Mao. 2013. “Road traffic density estimation in vehicular networks.” In: IEEE Wireless Communications and Networking Conference: 4653-4658. 15 April 2013, Shanghai, China. ISBN: 978-1-4673-5938-2.
  • 7. Sananmongkhonchai Sappaya, Poj Tangamchit, Pornanong Pongpaibool. 2008. “Road traffic estimation from multiple GPS data using incremental weighted update.” In: Eighth International Conference ITS Telecommunications: 62-66. 24 October 2008, Phuket, Thailand. ISBN: 978-1-4244-2857-1.
  • 8. Promnoi Sunisa, Poj Tangamchit, Wasan Pattara-Atikom. 2009. “Road traffic estimation with signal matching in mobile phone using large-size database.” In: 12th International IEEE Conference on Intelligent Transportation Systems: 1-6. 4-7 October 2009, St. Louis, USA. ISBN: 978-1-4244-5519-5.
  • 9. Bhoraskar Ravi, Nagamanoj Vankadhara, Bhaskaran Raman, Purushottam Kulkarni. 2012. “Wolverine: traffic and road condition estimation using smartphone sensors.” In: Fourth International Conference on Communication Systems and Networks: 1-6. 3-7 January 2012, Bangalore, India. ISBN: 978-1-4673-0296-8.
  • 10. Pasolini Gianni, Roberto Verdone. 2002. “Bluetooth for ITS?” In: Fifth International Symposium on Wireless Personal Multimedia Communications Vol. 1: 315-319. 27-30 October 2002, Honolulu, USA. ISBN: 0-7803-7442-8.
  • 11. Sawant Hamjit, Tan Jindong, Yang Qingyan, Wang QiZhi. 2004. “Using Bluetooth and sensor networks for intelligent transportation systems.” In: Seventh International IEEE Conference on Intelligent Transportation Systems: 767-772. 3-6 October 2004, Washington, USA. ISBN: 0-7803-8500-4.
  • 12. Ahmed Hazem, El-Darieby Mohamed, Morgan Yesser, Abdulhai Baher. 2008. “A wireless mesh network-based platform for ITS.” In: IEEE Vehicular Technology Conference: 3047-3051. 11-14 May 2008, Singapore, Singapore. ISBN: 978-1-4244- 1644-8.
  • 13. Araghi Bahar Namaki, Pedersen Kristian Skoven, Christensen Lars Torholm, Krishnan Rajesh, Lahrmann Harry. 2014. “Accuracy of travel time estimation using Bluetooth technology: case study Limfjord Tunnel Aalborg.” International Journal of Intelligent Transportation Systems Research 13 (3): 166-191. ISSN: 1868-8659. DOI: http://doi.org/10.1007/s13177-014-0094-z.
  • 14. Laharotte Pierre-Antoine, Romain Billot, Etienne Come, Latifa Oukhellou, Alfredo Nantes, El Faouzi Nour-Eddin. 2014. “Spatiotemporal analysis of Bluetooth data: application to a large urban network.” IEEE Transactions on Intelligent Transportation Systems 16 (3):1439-1448. ISSN: 524-9050. DOI: http://doi.org/10.1109/TITS.2014.2367165.
  • 15. Hellwig Zdzisław. 1968. On the Optimal Choice of Predictors. Toward a System of Quantitative Indicators of Components of Human Resources Development. Ed. Z. Gostkowski. UNESCO: Paris.
  • 16. Efroymson M.A. 1960. Multiple regression analysis. In: A. Ralston and H.S. Wilf, eds., Mathematical Methods for Digital Computers: 191-203. New York: John Wiley & Sons.
  • 17. Darbari Jyoti D., Vernika Agarwal, Venkata S.S. Yadavalli, Diego Galar, Prakash C. Jha. 2017. “A multi-objective fuzzy mathematical approach for sustainable reverse supply chain configuration.” Journal of Transport and Supply Chain Management 11: 1-12. ISSN: 2310-8789. DOI: http://doi.org/10.4102/jtscm.v11i0.267.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-70ff4c2e-87b4-4df4-aa8a-5a6474d1f63d
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