A system for automatic notification and severity estimation of automotive accidents

IEEE Transactions on Mobile Computing

Volumn 13, Issue 5, 2014, Pages 948-963

  Fogue, Manuel ^a   Garrido, Piedad ^a   Martinez, Francisco J ^a   Cano, Juan Carlos ^b   Calafate, Carlos T ^b   Manzoni, Pietro ^b  

^a UNIVERSITY OF ZARAGOZA   (Spain)

^b UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

Author keywords

Communication Networking and Information Technology; Computer Systems Organization; Mobile communication systems; Mobile Computing; Network Architecture and Design; Wireless communication

Indexed keywords

EMERGENCY SERVICES; HIGHWAY ACCIDENTS; INFORMATION TECHNOLOGY; INTELLIGENT SYSTEMS; MOBILE COMPUTING; MOBILE TELECOMMUNICATION SYSTEMS; NETWORK ARCHITECTURE; RADIO BROADCASTING; WIRELESS TELECOMMUNICATION SYSTEMS;

ARTIFICIAL INTELLIGENCE SYSTEMS; AUTOMATIC NOTIFICATION; COMMUNICATION CAPABILITIES; COMMUNICATION TECHNOLOGIES; COMPUTER SYSTEMS ORGANIZATION; KNOWLEDGE DISCOVERY IN DATABASE; OFF-THE-SHELF DEVICES; WIRELESS COMMUNICATIONS;

VEHICLES;

EID: 84901768279     PISSN: 15361233     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMC.2013.35     Document Type: Article

References (35)

1. Dirección General de Tráfico (DGT). (2010). The Main Statistics of Road Accidents Spain [Online]. Available: http://www.dgt.es/ portal/es/seguridad-vial/estadistica
2. Eurostat: Statistical Office of the European Communities. (2012) Transport Statistics in the EU [Online]. Available: http://epp.eurostat.ec. europa.eu/portal/page/portal/transport/data/main-tables
3. J. Miller, "Vehicle-to-vehicle-to-infrastructure (V2V2I) intelligent transportation system architecture," in Proc. IEEE Intell. Veh. Symp., Eindhoven, Netherlands, Jun. 2008, pp. 715-720.
4. F. Martinez, C.-K. Toh, J.-C. Cano, C. Calafate, and P. Manzoni, "Emergency services in future intelligent transportation systems based on vehicular communication networks," IEEE Intell. Transp. Syst. Mag., vol. 2, no. 2, pp. 6-20, Oct. 2010.
5. M. Fogue et al., "Prototyping an automatic notification scheme for traffic accidents in vehicular networks," in Proc. 4th IFIP WD, Niagara Falls, ON, Canada, Oct. 2011.
6. M. Fogue et al., "Evaluating the impact of a novel message dissemination scheme for vehicular networks using real maps," Transp. Res. Part C: Emerg. Technol., vol. 25, pp. 61-80, Dec. 2012.
7. B&B Electronics. (2012). The OBD-II Home Page [Online]. Available: http://www.obdii.com
8. U. Fayyad, G. Piatetsky-Shapiro, and P. Smyth, "The KDD process for extracting useful knowledge from volumes of data," Commun. ACM, vol. 39, pp. 27-34, Nov. 1996. (Pubitemid 126428076)
9. M. Hall et al., "The WEKA data mining software: An update," SIGKDD Explor., vol. 11, pp. 10-18, Nov. 2009.
10. European New Car Assessment Programme (Euro NCAP). (2012) Test Procedures [Online]. Available: http://www.euroncap.com/testprocedures.aspx
11. Nat. Hwy. Traffic Safety Admin. (NHTSA). (2012). National Automotive Sampling System (NASS) and General Estimates System (GES) [Online]. Available: http://www.nhtsa.gov/NASS/
12. Nat. Hwy. Traffic Safety Admin. (NHTSA). (2012). FTP Site for the General Estimates System (GES) [Online]. Available: ftp://ftp.nhtsa.dot.gov/GES/
13. K. Yu and E. Dutkiewicz, "Geometry and motion-based positioning algorithms for mobile tracking in NLOS environments," IEEE Trans. Mobile Comput., vol. 11, no. 2, pp. 254-263, Feb. 2012.
14. M. Hall, "Correlation-based feature selection for machine learning," Ph.D. dissertation, Dept. Comput. Sci., Univ. Waikato, Hamilton, New Zealand, 2008.
15. R. Kohavi and G. H. John, "Wrappers for feature subset selection," Artif. Intell., vol. 97, pp. 273-324, Dec. 1997. (Pubitemid 127401107)
16. J. R. Quinlan, C4.5: Programs For Machine Learning. San Francisco, CA, USA: Morgan Kaufmann Publishers, Inc., 1993.
17. G. F. Cooper and E. Herskovits, "A Bayesian method for the induction of probabilistic networks from data," Mach. Learn., vol. 9, pp. 309-347, Oct. 1992.
18. J. C. Platt, Fast Training of Support Vector Machines Using Sequential Minimal Optimization. Cambridge, MA, USA: MIT Press, 1999, pp. 185-208.
19. T. Fawcett, "ROC graphs: Notes and practical considerations for researchers," HP Labs, Palo Alto, CA, USA, Tech. Rep. HPL-2003-4, 2004.
20. A. P. Bradley, "The use of the area under the ROC curve in the evaluation of machine learning algorithms," Pattern Recognit., vol. 30, no. 7, pp. 1145-1159, 1997. (Pubitemid 127406521)
21. SAE Int. (2010). DSRC Implementation Guide-A Guide to Users of SAE J2735 Message Sets Over DSRC [Online]. Available: http://www.sae.org/standardsdev/ dsrc/DSRCImplementationG uide.pdf
22. M. Modsching, R. Kramer, and K. Hagen, "Field trial on GPS accuracy in a medium size city: The influence of built-up," in Proc. 3rd WPNC, Hannover, Germany, Mar. 2006, pp. 209-218.
23. IDIADA: Instituto de Investigación Aplicada del Automóvil. (2012). Applus+ IDIADA Web Site [Online]. Available: http://www.idiada.es
24. U.S. Dept. Transp.-Research and Innovative Technology Administration (RITA). (2012). Safety Pilot Program Overview [Online]. Available: http://www.its.dot.gov/safety-pilot/
25. A. Amoroso, G. Marfia, M. Roccetti, and G. Pau, "To live and drive in L.A.: Measurements from a real intervehicular accident alert test," in Proc. IEEE WCNCW, Paris, France, Apr. 2012, pp. 328-332.
26. H.-S. Shin, S.-J. Jung, J.-J. Kim, and W.-Y. Chung, "Real time car driver's condition monitoring system," in Proc. IEEE Sensors, Kona, HI, USA, Nov. 2010, pp. 951-954.
27. E. Palantei et al., "A 2.5 GHz wireless ECG system for remotely monitoring heart pulses," in Proc. IEEE APSURSI, Chicago, IL, USA, Jul. 2012, pp. 1-2.
28. S. Jung, H. Shin, J. Yoo, and W. Chung, "Highly sensitive driver condition monitoring system using nonintrusive active electrodes," in Proc. IEEE ICCE, Las Vegas, NV, USA, Jan. 2012, pp. 305-306.
29. T. Beshah and S. Hill, "Mining road traffic accident data to improve safety: Role of road-related factors on accident severity in ethiopia," in Proc. AAAI AI-D, Stanford, CA, USA, Mar. 2010.
30. T. B. Tesema, A. Abraham, and C. Grosan, "Rule mining and classification of road accidents using adaptive regression trees," IJSSST, vol. 6, no. 10-11, pp. 80-94, 2005.
31. S. Sohn and H. Shin, "Pattern recognition for road traffic accident severity in Korea," Ergonomics, vol. 44, no. 1, pp. 107-117, Jan. 2001. (Pubitemid 32058490)
32. S. Y. Sohn and S. H. Lee, "Data fusion, ensemble and clustering to improve the classification accuracy for the severity of road traffic accidents in Korea," Safety Sci., vol. 41, no. 1, pp. 1-14, 2003. (Pubitemid 35299564)
33. M. Chong, A. Abraham, and M. Paprzycki, "Traffic accident analysis using machine learning paradigms," Informatica, vol. 29, no. 1, pp. 89-98, 2005. (Pubitemid 41161824)
34. T. K. Anderson, "Kernel density estimation and K-means clustering to profile road accident hotspots," Accident Anal. Prev., vol. 41, no. 3, pp. 359-364, 2009.
35. R. Nayak, D. Emerson, J. Weligamage, and N. Piyatrapoomi, "Road crash proneness prediction using data mining," in Proc. 14th Int. Conf. EDBT, New York, NY, USA, 2011, pp. 521-526.