Abstract
Since technology is advancing at a rapid pace, new smart electronic devices are continually emerging to solve everyday problems. One of the most important problems of the world is related to road safety, so the mitigation of traffic accidents has become one of the biggest challenges for researchers. As a result, many proposals have emerged within the Intelligent Transport System (ITS) initiative. This paper proposes a new ITS-based system to automatically detect and warn about the breach of traffic lights. In the proposal, the vehicle that violates traffic lights self-reports of it, so the system can warn nearby vehicles to make they drive with greater caution. This self-reporting is done in a completely anonymously way so that users do not stop using the application. Besides, the method uses cryptographic algorithms to guarantee trust, integrity and authenticity of the information. The proposed system has been designed and implemented using sensors, smartphones and a server in the cloud, and the obtained results are promising.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Bin, T., Morris, B.T., Ming, T., Yuqiang, L., Chao, G., Dayong, S., Shaohu, T.: Hierarchical and networked vehicle surveillance in ITS: a survey. IEEE Trans. Intell. Transp. Syst. 16(2), 557–580 (2015)
Bochner, B., Walden, T.: Effectiveness of red light cameras. Transp. Eng. J. 80(5), 18 (2010)
Caballero-Gil C., Molina-Gil J., Hernandez-Serrano J., Leon O., Soriano M., On the revocation of malicious users in anonymous and non-traceable VANETs. In: XIII Reunion Española sobre Criptologia y Seguridad de la Informacion, pp. 87–91 (2014)
Charette, R., Nashashibi, F.: Traffic light recognition using image processing compared to learning processes. In: ICEE/RSI International Conference on Intelligent Robots and Systems, pp. 333–338 (2009)
Choi, C., Park, Y.: Enhanced traffic light detection method using geometry information. Int. J. Comput. Control, Quant. Inf. Eng. 8(8), 1264–1268 (2014)
de Trafico, D.G.: Portal Estadistico Parque de Vehiculos. http://www.dgt.es/. Accessed 2015
Fairfield, N., Urmson, C.: Traffic light mapping and detection. In: IEEC International Conference on Robotics and Automation (ICRA), pp. 5421–5426 (2011)
Gradinescu, V., Gorgorin, C., Diaconescu, R., Cristea, V., Iftode, L.: Adaptive traffic lights using car-to-car communication. In: IEEE Vehicular Technology Conference, VTC2007-Spring, pp. 21–25 (2007)
ISO/IEC 9796–2:2010: Information technology, Security techniques, Digital signature schemes giving message recovery, Part 2: Integer factorization based mechanisms. ISO (2010)
Johnson, D., Menezes, A., Vanstone, A.: The elliptic curve digital signature algorithm (ECDSA). Int. J. Inf. Secur. 1(1), 36–61 (2001)
Al-Khateeb, K.A., Johari, J.A., Al-Khateeb, W.F.: Dynamic traffic light sequence algorithm using RFID. J. Comput. Sci. 4, 517–524 (2008)
Kham, N.H., Nwe, C.M.: Implementation of modern traffic light control system. Int. J. Sci. Res. Publ. 4(6), 82–89 (2014)
RFDuino: http://www.rfduino.com/. Accessed May 2015
Sweeney, L.: k-anonymity: a model for protecting privacy. Int. J. Uncertainty Fuzziness Knowl. Based Syst. 10(5), 557–570 (2002)
U.S. Department of Transportation, Traffic Safety Facts 2008 Report. National Statistics (2008)
Acknowledgments
Research supported by TIN2011-25452, BES-2012-051817, IPT-2012-0585-370000, RTC-2014-1648-8 and TEC2014-54110-R.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Martín-Fernández, F., Caballero-Gil, P., Caballero-Gil, C. (2015). Detection and Report of Traffic Lights Violation Using Sensors and Smartphones. In: García-Chamizo, J., Fortino, G., Ochoa, S. (eds) Ubiquitous Computing and Ambient Intelligence. Sensing, Processing, and Using Environmental Information. UCAmI 2015. Lecture Notes in Computer Science(), vol 9454. Springer, Cham. https://doi.org/10.1007/978-3-319-26401-1_23
Download citation
DOI: https://doi.org/10.1007/978-3-319-26401-1_23
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-26400-4
Online ISBN: 978-3-319-26401-1
eBook Packages: Computer ScienceComputer Science (R0)