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Estilos de conducción de automóviles. Reconocimiento automático usando los sensores de los smartphones
| dc.contributor.advisor | Ávila Buitrago, Gabriel Eduardo | |
| dc.contributor.author | Fernández Joya, Jovan Farik | |
| dc.coverage.spatial | Bogotá D.C. | |
| dc.coverage.temporal | Junio 2019 a junio 2021 | |
| dc.date.accessioned | 2024-02-20T17:33:42Z | |
| dc.date.available | 2024-02-20T17:33:42Z | |
| dc.date.issued | 2021-06-21 | |
| dc.identifier.uri | http://hdl.handle.net/10823/7119 | |
| dc.description.abstract | Los estilos de conducción son aquellos aspectos únicos que identifican la forma en que cada conductor conduce un vehículo. Cada persona tiene un estilo propio que lo identifica y que ha sido desarrollado a través del tiempo y se ha visto influenciado por factores humanos y medioambientales. El presente proyecto busca identificar los estilos de conducción con el apoyo de un conjunto de sensores presentes en los smartphones, con el fin de clasificar a los conductores de vehículos. Este proyecto busca generar un aporte en el estudio y caracterización, por medios computacionales, de uno de los factores que es tercera causa de accidentes de tránsito, cuyos resultados podrán ser usados a futuro en aplicación como: tarifación diferencias de pólizas de seguros de automóviles, mejorar el consumo de gasolina, conducción autónoma, generación de rutas de tráfico vehicular seguro, entre otras. | spa |
| dc.description.tableofcontents | RESUMEN... 7 INTRODUCCIÓN... 8 CONTRIBUCIONES... 12 OBJETIVOS DE LA PROPUESTA... 13 ESTRUCTURA DEL DOCUMENTO... 14 REVISIÓN DEL ESTADO DEL ARTE... 16 BÚSQUEDA SISTÉMICA... 20 HALLAZGOS... 24 ESTRATEGIA METODOLÓGICA... 28 FASE 1... 28 FASE 2 ... . 29 FASE 3 ... 34 RESULTADOS... 36 SELECCIÓN DE CARACTERÍSTICAS... 36 RECONOCIMIENTO DE EVENTOS DE CONDUCCIÓN... 37 EVALUACIÓN CON CARACTERÍSTICAS MIXTAS... 37 EVALUACIÓN CON CARACTERÍSTICAS ESTADÍSTICAS... . 39 RECONOCIMIENTO DE TIPOS DE CONDUCCIÓN... 40 EVALUACIÓN CON CARACTERÍSTICAS MIXTAS... 41 HALLAZGOS... 44 CONCLUSIONES Y RECOMENDACIONES FINALES... 45 REFERENCIAS... 50 ANEXOS... 57 | spa |
| dc.format.mimetype | application/pdf | spa |
| dc.language.iso | spa | spa |
| dc.title | Estilos de conducción de automóviles. Reconocimiento automático usando los sensores de los smartphones | spa |
| dc.type | materThesis | spa |
| dc.type.local | Tesis/Trabajo de grado - Monografía - Maestría | spa |
| dc.type.driver | info:eu-repo/semantics/masterThesis | spa |
| dc.title.translated | Car driving styles. Automatic recognition using smartphone sensors | spa |
| dc.subject.proposal | Conductor de vehículo | spa |
| dc.subject.proposal | Estilos de conducción | spa |
| dc.subject.proposal | Teléfono inteligente | spa |
| dc.subject.lemb | Innovaciones tecnológicas | spa |
| dc.subject.lemb | Tráfico urbano | spa |
| dc.subject.lemb | Vehículos | spa |
| dc.description.abstractenglish | Driving styles are those unique aspects that allow to identify the way a person drives a car. Each person has a unique style of driving, which has evolved with time, and has been influenced by human and environmental factors. This work proposes a contribution to the study and characterization, by computational methods, of a factor that is the third cause of vehicular traffic accidents. The results of this work. Must be used in differential vehicular insurance policies, improve gas consume, automatic driving, generation of safe vehicular paths, among others. | spa |
| dc.subject.keywords | Driving styles | spa |
| dc.subject.keywords | Smartphone | spa |
| dc.subject.keywords | Vehicle driver | spa |
| dc.relation.references | M. Q. Khan and S. Lee, “A Comprehensive Survey of Driving Monitoring and Assistance Systems,” Sensors, vol. 19, no. 11, p. 2574, Jun. 2019, doi: 10.3390/s19112574. | spa |
| dc.relation.references | V. and I. P. (NVI) Management of Noncommunicable Diseases, Disability, “Informe Sobre la Situación Mundial de la Sedguridad Vial 2015,” World Health Organization, 2015. | spa |
| dc.relation.references | S. J. Valbuena Cortés, “Muertes y lesiones no fatales por accidentes de transporte, Colombia, 2011,” Instituto Nacional de Medicina Legal y Ciencias Forenses, 2012. | spa |
| dc.relation.references | Ministerio de Transporte, “Plan Nacional de Seguridad Vial Colombia 2011 - 2021,” Bogotá D.C., 2015. | spa |
| dc.relation.references | J. C. Martínez Rojas, C. E. Villalobos Cuadrado, and E. Benítez, “Elaboración de un modelo de negocio de asistencia a la conducción mediante una propuesta de IoT para la prevención de accidentes de tránsito en la ciudad de Bogotá,” Chía, 2018. | spa |
| dc.relation.references | R. I. Lugo Hernández, “Análisis y reconocimiento de patrones de conducción temeraria mediante algoritmos de aprendizaje computacional,” 2016. | spa |
| dc.relation.references | B. M. Leiner et al., “A Brief History of the Internet,” Baseline, 1999. https://arxiv.org/abs/cs/9901011 (accessed May 16, 2019). | spa |
| dc.relation.references | I. Machorro-Cano, G. Alor-Hernández, N. A. Cruz-Ramos, C. Sánchez-Ramírez, and M. G. Segura-Ozuna, “A Brief Review of IoT Platforms and Applications in Industry,” Springer, Cham, 2018, pp. 293–324. doi: 10.1007/978-3-319-56871-3_15. | spa |
| dc.relation.references | S. Moosavi, B. Omidvar-Tehrani, R. B. Craig, A. Nandi, and R. Ramnath, “Characterizing Driving Context from Driver Behavior,” in GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, 2017, vol. 2017-Novem, pp. 1–4. doi: 10.1145/3139958.3139992. | spa |
| dc.relation.references | I. Skog et al., “Insurance telematics: opportunities and challenges with the smartphone solution.” | spa |
| dc.relation.references | J. Engelbrecht, M. J. Booysen, F. J. Bruwer, and G.-J. van Rooyen, “Survey of smartphone-based sensing in vehicles for intelligent transportation system applications,” IET Intelligent Transport Systems, vol. 9, no. 10, pp. 924–935, Dec. 2015, doi: 10.1049/iet-its.2014.0248. | spa |
| dc.relation.references | C. Marina Martinez, M. Heucke, F. Y. Wang, B. Gao, and D. Cao, “Driving Style Recognition for Intelligent Vehicle Control and Advanced Driver Assistance: A Survey,” IEEE Transactions on Intelligent Transportation Systems, vol. 19, no. 3. Institute of Electrical and Electronics Engineers Inc., pp. 666–676, Mar. 01, 2018. doi: 10.1109/TITS.2017.2706978. | spa |
| dc.relation.references | A. Chowdhury, T. Banerjee, T. Chakravarty, and P. Balamuralidhar, “Smartphone based estimation of relative risk propensity for inducing good driving behavior,” in UbiComp and ISWC 2015 - Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the Proceedings of the 2015 ACM International Symposium on Wearable Computers, Sep. 2015, pp. 743–752. doi: 10.1145/2800835.2804392. | spa |
| dc.relation.references | J. F. Fernández Joya, G. Á. Buitrago, H. Luna-García, and W. J. Samiento, “Smartphones, Suitable Tool for Driver Behavior Recognition. A Systematic Review,” in Communications in Computer and Information Science, 2020, vol. 1334. doi: 10.1007/978-3-030-66919-5_24. | spa |
| dc.relation.references | Lu Tan and Neng Wang, “Future internet: The Internet of Things,” in 2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE), Aug. 2010, pp. V5-376-V5-380. doi: 10.1109/ICACTE.2010.5579543. | spa |
| dc.relation.references | O. Vermesan et al., “Internet of Things Strategic Research Roadmap,” 2009. | spa |
| dc.relation.references | O. Moreno and J. Díaz Fernández, “Diseño y despliegue de una arquitectura IoT para el análisis de datos en tiempo real,” 2016. | spa |
| dc.relation.references | L. Coetzee and J. Eksteen, The Internet of Things – Promise for the Future? An Introduction. 2011. | spa |
| dc.relation.references | D. L. Pinzón Niño, “Panorama de aplicación de internet de las cosas (IoT).” | spa |
| dc.relation.references | S. Kaplan, M. A. Guvensan, A. G. Yavuz, and Y. Karalurt, “Driver Behavior Analysis for Safe Driving: A Survey,” IEEE Transactions on Intelligent Transportation Systems, vol. 16, no. 6, pp. 3017–3032, Dec. 2015, doi: 10.1109/TITS.2015.2462084. | spa |
| dc.relation.references | D. M. Vlachogiannis, E. I. Vlahogianni, and J. Golias, “A reinforcement learning model for personalized driving policies identification,” International Journal of Transportation Science and Technology, no. xxxx, 2020, doi: 10.1016/j.ijtst.2020.03.002. | spa |
| dc.relation.references | Z. Ouyang, J. Niu, Y. Liu, and X. Liu, “An Ensemble Learning-Based Vehicle Steering Detector Using Smartphones,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 5, pp. 1964–1975, 2020, doi: 10.1109/TITS.2019.2909107. | spa |
| dc.relation.references | A. Kashevnik, I. Lashkov, and A. Gurtov, “Methodology and Mobile Application for Driver Behavior Analysis and Accident Prevention,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 6, pp. 2427–2436, 2020, doi: 10.1109/TITS.2019.2918328. | spa |
| dc.relation.references | H. R. Eftekhari and M. Ghatee, “A similarity-based neuro-fuzzy modeling for driving behavior recognition applying fusion of smartphone sensors,” Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, vol. 23, no. 1, pp. 72–83, 2019, doi: 10.1080/15472450.2018.1506338. | spa |
| dc.relation.references | E. Papadimitriou, A. Argyropoulou, D. I. Tselentis, and G. Yannis, “Analysis of driver behaviour through smartphone data: The case of mobile phone use while driving,” Safety Science, vol. 119, no. May, pp. 91–97, 2019, doi: 10.1016/j.ssci.2019.05.059. | spa |
| dc.relation.references | A. A. Rahman, W. Saleem, and V. V. Iyer, “Driving Behavior Profiling and Prediction in KSA using Smart Phone Sensors and MLAs,” 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology, JEEIT 2019 - Proceedings, pp. 34–39, 2019, doi: 10.1109/JEEIT.2019.8717533. | spa |
| dc.relation.references | N. Lourenco, B. Cabral, and J. Granjal, “Driving Profile using Evolutionary Computation,” 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings, no. Ml, pp. 2466–2473, 2019, doi: 10.1109/CEC.2019.8790154. | spa |
| dc.relation.references | D. I. Tselentis, E. I. Vlahogianni, and G. Yannis, “Driving safety efficiency benchmarking using smartphone data,” Transportation Research Part C: Emerging Technologies, vol. 109, no. November, pp. 343–357, 2019, doi: 10.1016/j.trc.2019.11.006. | spa |
| dc.relation.references | E. G. Mantouka, E. N. Barmpounakis, and E. I. Vlahogianni, “Identifying driving safety profiles from smartphone data using unsupervised learning,” Safety Science, vol. 119, no. January, pp. 84–90, 2019, doi: 10.1016/j.ssci.2019.01.025. | spa |
| dc.relation.references | M. M. Bejani and M. Ghatee, “A context aware system for driving style evaluation by an ensemble learning on smartphone sensors data,” Transportation Research Part C: Emerging Technologies, vol. 89, no. February, pp. 303–320, 2018, doi: 10.1016/j.trc.2018.02.009. | spa |
| dc.relation.references | Y. Guo, B. Guo, Y. Liu, Z. Wang, Y. Ouyang, and Z. Yu, “CrowdSafe: Detecting extreme driving behaviors based on mobile crowdsensing,” 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017 - , pp. 1–8, 2018, doi: 10.1109/UIC-ATC.2017.8397522. | spa |
| dc.relation.references | A. U. Nambi et al., “Demo: HAMS: Driver and driving monitoring using a smartphone,” Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM, pp. 840–842, 2018, doi: 10.1145/3241539.3267723. | spa |
| dc.relation.references | F. Tahmasbi, Y. Wang, Y. Chen, and M. Gruteser, “Poster: Your phone tells us the truth : R identification using smartphone on one turn,” Proceedings of the Annual International Conference on Mobile Computing and Networking, MOBICOM, no. October, pp. 762–764, 2018, doi: 10.1145/3241539.3267769. | spa |
| dc.relation.references | L. Kang and S. Banerjee, “Practical driving analytics with smartphone sensors,” IEEE Vehicular Networking Conference, VNC, vol. 2018-Janua, pp. 303–310, 2018, doi: 10.1109/VNC.2017.8275595. | spa |
| dc.relation.references | S. K. Al-luhaibi, A. M. Said, and M. S. Najim Al-Din, “Recognition of driving maneuvers based accelerometer sensor,” International Journal of Civil Engineering and Technology, vol. 9, no. 11, pp. 1542–1547, 2018. | spa |
| dc.relation.references | C. Streiffer, R. Raghavendra, T. Benson, and M. Srivatsa, “DarNet: A deep learning solution for distracted driving detection,” Middleware 2017 - Proceedings of the 2017 International Middleware Conference (Industrial Track), pp. 22–28, 2017, doi: 10.1145/3154448.3154452. | spa |
| dc.relation.references | E. I. Vlahogianni and E. N. Barmpounakis, “Driving analytics using smartphones: Algorithms, comparisons and challenges,” Transportation Research Part C: Emerging Technologies, vol. 79, pp. 196–206, 2017, doi: 10.1016/j.trc.2017.03.014. | spa |
| dc.relation.references | X. Xu, S. Yin, and P. Ouyang, “Fast and low-power behavior analysis on vehicles using smartphones,” 2017 6th International Symposium on Next Generation Electronics, ISNE 2017, 2017, doi: 10.1109/ISNE.2017.7968748. | spa |
| dc.relation.references | W. Cho and S. H. Kim, “Multimedia sensor dataset for the analysis of vehicle movement,” Proceedings of the 8th ACM Multimedia Systems Conference, MMSys 2017, pp. 175–180, 2017, doi: 10.1145/3083187.3083217. | spa |
| dc.relation.references | D. M. Vlachogiannis, E. I. Vlahogianni, and J. Golias, “A reinforcement learning model for personalized driving policies identification,” International Journal of Transportation Science and Technology, no. xxxx, 2020, doi: 10.1016/j.ijtst.2020.03.002. | spa |
| dc.relation.references | Z. Ouyang, J. Niu, Y. Liu, and X. Liu, “An Ensemble Learning-Based Vehicle Steering Detector Using Smartphones,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 5, pp. 1964–1975, 2020, doi: 10.1109/TITS.2019.2909107. | spa |
| dc.relation.references | A. Kashevnik, I. Lashkov, and A. Gurtov, “Methodology and Mobile Application for Driver Behavior Analysis and Accident Prevention,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 6, pp. 2427–2436, 2020, doi: 10.1109/TITS.2019.2918328. | spa |
| dc.relation.references | R. Wang, F. Xie, B. Zhang, W. Liu, W. Qian, and W. Xian, “Detecting abnormal driving behaviors by smartphone sensors based on multi-feature convolutional neural network,” Chinese Control Conference, CCC, vol. 2019-July, no. 2, pp. 6639–6644, 2019, doi: 10.23919/ChiCC.2019.8865705. | spa |
| dc.relation.references | C. Streiffer, R. Raghavendra, T. Benson, and M. Srivatsa, “DarNet: A deep learning solution for distracted driving detection,” Middleware 2017 - Proceedings of the 2017 International Middleware Conference (Industrial Track), pp. 22–28, 2017, doi: 10.1145/3154448.3154452. | spa |
| dc.relation.references | X. Xu, S. Yin, and P. Ouyang, “Fast and low-power behavior analysis on vehicles using smartphones,” 2017 6th International Symposium on Next Generation Electronics, ISNE 2017, 2017, doi: 10.1109/ISNE.2017.7968748. | spa |
| dc.relation.references | W. Cho and S. H. Kim, “Multimedia sensor dataset for the analysis of vehicle movement,” Proceedings of the 8th ACM Multimedia Systems Conference, MMSys 2017, pp. 175–180, 2017, doi: 10.1145/3083187.3083217. | spa |
| dc.relation.references | T. L. L. Mon and T. L. L. Thein, “Design and implementation of smart alert system for reducing road traffic accidents in Myanmar,” AIP Conference Proceedings, vol. 2129, no. July, 2019, doi: 10.1063/1.5118022. | spa |
| dc.relation.references | I. Lashkov, A. Kashevnik, N. Shilov, V. Parfenov, and A. Shabaev, “Driver dangerous state detection based on OpenCV & dlib libraries using mobile video processing,” Proceedings - 22nd IEEE International Conference on Computational Science and Engineering and 17th IEEE International Conference on Embedded and Ubiquitous Computing, CSE/EUC 2019, pp. 74–79, 2019, doi: 10.1109/CSE/EUC.2019.00024. | spa |
| dc.publisher.program | Ingeniería de Sistemas | spa |
| dc.type.coar | http://purl.org/coar/resource_type/c_bdcc | spa |
| dc.publisher.faculty | Facultad de ingeniería y Diseño e Innovación | spa |
| dc.identifier.instname | instname:Politécnico Grancolombiano | spa |
| dc.identifier.reponame | reponame:Alejandría Repositorio Comunidad | spa |
| dc.type.hasversion | info:eu-repo/semantics/acceptedVersion | |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
| dc.identifier.repourl | repourl:http://alejandria.poligran.edu.co | spa |
| dc.type.redcol | https://purl.org/redcol/resource_type/TP | |
| dc.rights.creativecommons | Atribución-NoComercial-SinDerivadas 2.5 Colombia | spa |
| dc.type.version | info:eu-repo/semantics/draft | spa |
