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Embedded mobile systems to assist road users in urban environments

Identyfikatory
Warianty tytułu
PL
Mobilne systemy wbudowane do wspierania użytkowników dróg w obszarach zurbanizowanych
Konferencja
IEEE SPA 2015 (19 ; 23-25.09.2015 ; Poznań, Poland)
Języki publikacji
EN
Abstrakty
EN
This paper presents three applications for mobile phones dedicated to pedestrians, cyclists, motorcyclists, and car drivers, i.e., generally to various road users in order to assist them with innovative control of traffic flow – thus to substantially improve the traffic safety. The prepared software processes in real time a video sequence acquired with a camera built-in a smartphone. The first application detects changes of traffic lights. The second warns pedestrians in cases of approaching vehicles. The third one indicates turn signals of vehicles from adjacent lanes. Results of the prepared experiments show high efficiency of the proposed solutions.
PL
W artykule przedstawiono trzy aplikacje do urządzeń mobilnych przeznaczone dla pieszych, rowerzystów, motocyklistów i kierowców samochodów, a więc dla różnych użytkowników dróg, w celu pomocy im w usprawnieniu sterowania ruchem i w konsekwencji w celu zwiększenia bezpieczeństwa na drogach. Opracowane oprogramowanie przetwarza w czasie rzeczywistym sygnał wideo kamery wbudowanej w smartfon. Pierwsza aplikacja służy do wykrywania zmian świateł sygnalizacji ulicznej, druga – do wykrywania nadjeżdżających pojazdów i ostrzegania o tym pieszych. Trzecia służy zaś do wykrywania kierunkowskazów pojazdów na sąsiednich pasach ruchu. Wyniki przeprowadzonych eksperymentów wskazują na wysoką skuteczność zaproponowanych rozwiązań.
Rocznik
Strony
7--13
Opis fizyczny
Bibliogr. 30 poz., il., rys., tab.
Twórcy
autor
  • Poznań University of Technology, Faculty of Computing, Chair of Control and Systems Engineering, Division of Signal Processing and Electronic Systems
autor
  • Poznań University of Technology, Faculty of Computing, Chair of Control and Systems Engineering, Division of Signal Processing and Electronic Systems
autor
  • Poznań University of Technology, Faculty of Computing, Chair of Control and Systems Engineering, Division of Signal Processing and Electronic Systems
  • Poznań University of Technology, Faculty of Computing, Chair of Control and Systems Engineering, Division of Signal Processing and Electronic Systems
  • Poznań University of Technology, Faculty of Computing, Chair of Control and Systems Engineering, Division of Signal Processing and Electronic Systems
Bibliografia
  • [1] Official website of the European Commission, Miasta przyszłości – wyzwania, wizje, perspektywy, http://ec.europa.eu/regional_policy/sources/docgener/studies/pdf/citiesoftomorrow/citiesoftomorrow_final_pl.pdf, 2011, access: 04.03.2016.
  • [2] Statista, the statistics portal, The ten most traffic jam prone cities in Europe, http://www.statista.com/statistics/235780/most-trafficjam-prone-cities-in-europe/, access: 04.03.2016.
  • [3] European Commision, Roadmap to a Single Transport Area –Towards competitive and resource efficient transport system, Brussels, 28.03.2011.
  • [4] Official website of the Eur. Commission, Statistics – accidents data, http://ec.europa.eu/transport/road_safety/specialist/statistics/index_en.htm, access: 04.03.2016.
  • [5] Official website of the European Commission, EU ratifies UN Convention on disability rights, Brussels, 05.01.2011, http://europa.eu/rapid/press-release_IP-11-4_en.htm, access: 04.03.2016.
  • [6] Balcerek J. et al., Recognition of threats in urban areas by means of the analysis of video sequences, Proc. of Multimedia Communications, Services and Security, MCSS 2010, IEEE International Conference, Kraków, 6–7 May 2010, pp. 41–48.
  • [7] Balcerek J. et al., Prototype multimedia database system for registration of emergency situations, Proc. of Signal Processing − Algorithms, Architectures, Arrangements and Applications SPA’2009, IEEE International Conference, Poznań, Poland, 24–26 September 2009, pp. 144–148.
  • [8] Balcerek J. et al., Database of emergency telephone calls – system tools for real-time registration and metadata searching, Proc. of Signal Processing − Algorithms, Architectures, Arrangements and Applications SPA’2010, IEEE International Conference, Poznań, Poland, 23–25 September 2010, pp. 89−94.
  • [9] Balcerek J. et al., Automatic detection of traffic lights changes from red to green and car turn signals in order to improve urban traffic, Proc. of Signal Processing − Algorithms, Architectures, Arrangements and Applications SPA’2014, IEEE International Conference, Poznań, Poland, 22−24 September 2014, pp. 110−115.
  • [10] Balcerek J. et al., Video processing approach for supporting pedestrians in vehicle detection, Proc. of Signal Processing − Algorithms, Architectures, Arrangements and Applications SPA’2014, IEEE International Conference, Poznań, Poland, 22−24 September 2014, pp. 100−103.
  • [11] Balcerek J. et al., Automatyczne systemy wizyjne usprawniające ruch drogowy i zwiększające bezpieczeństwo (Automatic vision systems for improvement of traffic efficiency and safety), Elektronika – konstrukcje, technologie, zastosowania, no 4/2015, pp. 7−13, DOI:10.15199/13.2015.4.1.
  • [12] Balcerek J. et al., Mobile applications for driver and pedestrian assistance, Proc. of Signal Processing − Algorithms, Architectures, Arrangements and Applications SPA’2015, IEEE International Conference, Poznań, Poland, 23−25 September 2015, pp. 197−202.
  • [13] Chou T.S. et al., CaNPAs: A Campus Navigation and Parking Assistant System, IEEE International Conference on Systems, Man and Cybernetics, SMC, 8–11 Oct. 2006, vol. 1, pp. 631–638.
  • [14] Smirnov A. et al., Mobile application for guiding tourist activities: tourist assistant – TAIS, 16th Conference of Open Innovations Association (FRUCT16), 27–31 Oct. 2014, pp. 95–100.
  • [15] Beomju S. et al., Indoor 3D pedestrian tracking algorithm based on PDR using smarthphone, 12th International Conference on Control, Automation and Systems (ICCAS), 17–21 Oct. 2012, pp. 1442–1445.
  • [16] Alzantot M., Youssef M., UPTIME: Ubiquitous pedestrian tracking using mobile phones, IEEE Wireless Communications and Networking Conference (WCNC), 1–4 April 2012, pp. 3204–3209.
  • [17] Arthur D., 13 of the best smartphone cycling apps for iPhone and Android, 24.07.2015, http://road.cc/content/buyersguide/158533-13-best-smartphone-cycling-apps-iphone-andandroid, access: 10.11.2015.
  • [18] Siahaan T., Top 10 Motorcycle Apps, 31.07.2014, http://www.motorcycle.com/top10/top-10-motorcycle-apps.html, access: 04.03.2016.
  • [19] Corcoba Magana V., Munoz-Organero M., Artemisa: An eco-driving assistant for Android OS, IEEE International Conference on Consumer Electronics – Berlin (ICCE-Berlin), 6–8 Sept. 2011, pp. 211–215.
  • [20] Khanapuri A.V. et al., On road: A car assistant application, International Conference on Technologies for Sustainable Development (ICTSD), 4–6 Feb. 2015, pp. 1–7.
  • [21] Jiangpeng D. et al., Mobile phone based drunk driving detection, 4th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), 22–25 March 2010, pp. 1–8.
  • [22] Rozanowski K., Piotrowski Z., Ciolek M., Mobile Application for Driver’s Health Status Remote Monitoring, 9th International Wireless Communications and Mobile Computing Conference (IWCMC), 1–5 July 2013, pp. 1738–1743.
  • [23] Piniarski K., Pawłowski P., Dąbrowski A., Video Processing Algorithms for Detection of Pedestrians, Computational Methods in Science and Technology (CMST), vol. 21 (3) 2015, pp. 141–150.
  • [24] Negru M., Benea V., Nedevschi S., Fog assistance on smart mobile devices, IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), 4–6 Sept. 2014, pp. 197–204.
  • [25] Acharya A., Lee J., Chen A., Real Time Car Detection and Tracking in Mobile Devices, International Conference on Connected Vehicles and Expo (ICCVE), 12–16 Dec. 2012, pp. 239–240.
  • [26] Itu R., Danescu R., An efficient obstacle awareness application for Android mobile devices, IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), 4–6 Sept. 2014, pp. 157–163.
  • [27] Pritt C., Road sign detection on a smartphone for traffic safety, IEEE Applied Imagery Pattern Recognition Workshop (AIPR), 14–16 Oct. 2014, pp. 1–6.
  • [28] Pawłowski P., Prószyński D., Dąbrowski A., Real-time procedures for automatic recognition of road signs, Elektronika – konstrukcje, technologie, zastosowania, miesięcznik n-t, Wyd. Sigma NOT, 3/2009, pp. 57–61.
  • [29] Munoz-Organero M., Magana V. C., Validating the Impact on Reducing Fuel Consumption by Using an EcoDriving Assistant Based on Traffic Sign Detection and Optimal Deceleration Patterns, IEEE Transactions on Intelligent Transportation Systems, 2013, Vol. 14, Issue 2, pp. 1023–1028.
  • [30] Johnson K., Late Merge... the Zipper System, http://www.dot.state.mn.us/trafficeng/workzone/doc/When-latemerge-zipper.pdf, Minnesota Department of Transportation, United States, Oct. 2008.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e252e188-ecab-4b4b-a625-b594998d9fd9
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