Clasificación de estilos de conducción en el área metropolitana de Bucaramanga con monitoreo a bordo (OBD II) en condiciones reales de carretera

Los sistemas inteligentes de transporte (SIT) permiten optimizar el uso de la infraestructura existente incrementando el control, la efectividad, la eficiencia y la seguridad de los sistemas y la infraestructura de transporte, con el fin de gestionar la creciente demanda de movilidad [1]. Para desar...

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Autores:
Molina Martínez, Juan Danilo
Acuña Olivar, Brayan Ferney
Tipo de recurso:
Trabajo de grado de pregrado
Fecha de publicación:
2022
Institución:
Universidad Autónoma de Bucaramanga - UNAB
Repositorio:
Repositorio UNAB
Idioma:
spa
OAI Identifier:
oai:repository.unab.edu.co:20.500.12749/16806
Acceso en línea:
http://hdl.handle.net/20.500.12749/16806
Palabra clave:
Mechatronic
Micro trip fuel based method
Driving styles
Driving cycles
On-board diagnostics
Road safety
Ground transportation
Electronic data processing
Automobiles
Mecatrónica
Seguridad vial
Transporte terrestre
Procesamiento electrónico de datos
Automóviles
Estilos de conducción
Ciclos de conducción
Diagnóstico a bordo
Rights
License
http://creativecommons.org/licenses/by-nc-nd/2.5/co/
id UNAB2_dda8ae8c044abca818c110a47bb9f0c3
oai_identifier_str oai:repository.unab.edu.co:20.500.12749/16806
network_acronym_str UNAB2
network_name_str Repositorio UNAB
repository_id_str
dc.title.spa.fl_str_mv Clasificación de estilos de conducción en el área metropolitana de Bucaramanga con monitoreo a bordo (OBD II) en condiciones reales de carretera
dc.title.translated.spa.fl_str_mv Classification of driving styles in the metropolitan area of ​​Bucaramanga with on-board monitoring (OBD II) in real road condition
title Clasificación de estilos de conducción en el área metropolitana de Bucaramanga con monitoreo a bordo (OBD II) en condiciones reales de carretera
spellingShingle Clasificación de estilos de conducción en el área metropolitana de Bucaramanga con monitoreo a bordo (OBD II) en condiciones reales de carretera
Mechatronic
Micro trip fuel based method
Driving styles
Driving cycles
On-board diagnostics
Road safety
Ground transportation
Electronic data processing
Automobiles
Mecatrónica
Seguridad vial
Transporte terrestre
Procesamiento electrónico de datos
Automóviles
Estilos de conducción
Ciclos de conducción
Diagnóstico a bordo
title_short Clasificación de estilos de conducción en el área metropolitana de Bucaramanga con monitoreo a bordo (OBD II) en condiciones reales de carretera
title_full Clasificación de estilos de conducción en el área metropolitana de Bucaramanga con monitoreo a bordo (OBD II) en condiciones reales de carretera
title_fullStr Clasificación de estilos de conducción en el área metropolitana de Bucaramanga con monitoreo a bordo (OBD II) en condiciones reales de carretera
title_full_unstemmed Clasificación de estilos de conducción en el área metropolitana de Bucaramanga con monitoreo a bordo (OBD II) en condiciones reales de carretera
title_sort Clasificación de estilos de conducción en el área metropolitana de Bucaramanga con monitoreo a bordo (OBD II) en condiciones reales de carretera
dc.creator.fl_str_mv Molina Martínez, Juan Danilo
Acuña Olivar, Brayan Ferney
dc.contributor.advisor.none.fl_str_mv Maradey Lázaro, Jessica Gissella
Huertas Cardozo, José Ignacio
dc.contributor.author.none.fl_str_mv Molina Martínez, Juan Danilo
Acuña Olivar, Brayan Ferney
dc.contributor.cvlac.spa.fl_str_mv Maradey Lázaro, Jessica Gissella [0000040553]
Huertas Cardozo, José Ignacio [0000057398]
dc.contributor.googlescholar.spa.fl_str_mv Huertas Cardozo, José Ignacio [es&oi=ao]
dc.contributor.orcid.spa.fl_str_mv Maradey Lázaro, Jessica Gissella [0000-0003-2319-1965]
Huertas Cardozo, José Ignacio [0000-0003-4508-6453]
dc.contributor.researchgate.spa.fl_str_mv Maradey Lázaro, Jessica Gissella [profile/Jessica-Maradey-Lazaro]
dc.subject.keywords.spa.fl_str_mv Mechatronic
Micro trip fuel based method
Driving styles
Driving cycles
On-board diagnostics
Road safety
Ground transportation
Electronic data processing
Automobiles
topic Mechatronic
Micro trip fuel based method
Driving styles
Driving cycles
On-board diagnostics
Road safety
Ground transportation
Electronic data processing
Automobiles
Mecatrónica
Seguridad vial
Transporte terrestre
Procesamiento electrónico de datos
Automóviles
Estilos de conducción
Ciclos de conducción
Diagnóstico a bordo
dc.subject.lemb.spa.fl_str_mv Mecatrónica
Seguridad vial
Transporte terrestre
Procesamiento electrónico de datos
Automóviles
dc.subject.proposal.spa.fl_str_mv Estilos de conducción
Ciclos de conducción
Diagnóstico a bordo
description Los sistemas inteligentes de transporte (SIT) permiten optimizar el uso de la infraestructura existente incrementando el control, la efectividad, la eficiencia y la seguridad de los sistemas y la infraestructura de transporte, con el fin de gestionar la creciente demanda de movilidad [1]. Para desarrollar SIT eficaces es muy importante realizar campañas de monitoreo en condiciones reales de carretera que permitan la recolección de datos que describen el patrón de conducción de una región de interés. En el proyecto desarrollado se implementó un sistema de monitoreo a bordo (OBD II) con conexión a bluetooth en una muestra de 16 vehículos adquiriendo datos durante los meses de agosto a diciembre del año 2021 creando una base de datos para el área metropolitana de Bucaramanga con la que se describió el patrón de conducción a partir de tres conceptos, ciclos de conducción, diagramas de distribución de la frecuencia de velocidad- aceleración y la potencia específica del vehículo. También se abordó el tema de estilos de conducción a partir de los métodos de aceleración y del Jerk siendo este otro elemento que permite conocer más sobre los hábitos de conducción de los conductores de la región estudiada. El ciclo desarrollado se construyó con el método Micro Trips Fuel Based (MTFBM) alcanzando una similitud <15% de las diferencias relativas promedio de los parámetros característicos del 68.75%, mientras que el SAFD y el VSP indicaron que las personas conducían en la región a velocidades y aceleraciones bajas, debido a la alta densidad de tráfico. Con los estilos de conducción se validó que un estilo de conducción agresivo aumenta el consumo de combustible en más del 20%.
publishDate 2022
dc.date.accessioned.none.fl_str_mv 2022-06-28T18:53:13Z
dc.date.available.none.fl_str_mv 2022-06-28T18:53:13Z
dc.date.issued.none.fl_str_mv 2022-05-31
dc.type.driver.none.fl_str_mv info:eu-repo/semantics/bachelorThesis
dc.type.local.spa.fl_str_mv Trabajo de Grado
dc.type.coar.none.fl_str_mv http://purl.org/coar/resource_type/c_7a1f
dc.type.redcol.none.fl_str_mv http://purl.org/redcol/resource_type/TP
format http://purl.org/coar/resource_type/c_7a1f
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.12749/16806
dc.identifier.instname.spa.fl_str_mv instname:Universidad Autónoma de Bucaramanga - UNAB
dc.identifier.reponame.spa.fl_str_mv reponame:Repositorio Institucional UNAB
dc.identifier.repourl.spa.fl_str_mv repourl:https://repository.unab.edu.co
url http://hdl.handle.net/20.500.12749/16806
identifier_str_mv instname:Universidad Autónoma de Bucaramanga - UNAB
reponame:Repositorio Institucional UNAB
repourl:https://repository.unab.edu.co
dc.language.iso.spa.fl_str_mv spa
language spa
dc.relation.references.spa.fl_str_mv [1] GSD+, «Esquema de implantación de tecnologías inteligentes de transporte en América Latina: estudios de casos y recomendaciones.,» 2018
[2] Vanguardia, «Vanguardia,» 16 Julio 2019. [En línea]. Available: https://www.vanguardia.com/area-metropolitana/bucaramanga/transitan-4053automotores-nuevos-este-es-el-impacto-en-el-area-LG1190481. [Último acceso: 11 Julio 2021].
[3] Dirección de Tránsito de Bucaramanga, «Informe de gestión 1 trimestre,» Bucaramanga, 2019
[4] Alcaldía de Bucaramanga, «Bucaramanga ciudad de oportunidades,» Bucaramanga, 2020.
[5] Filial de Isa, «Memoria de sostenibilidad sistemas inteligentes en red,» Medellín, 2014.
[6] S. Navarro y R. García, Desarrollo de un ciclo de conducción bajo condiciones reales de carretera en el área metropolitana de Bucaramanga, Bucaramanga, 2021
[7] C. Martínez, M. Heucke, F.-y. Wang, B. Gao y D. Cao, «Driving Style Recognition for Intelligent Vehicle Control and Advanced Driver Assistance: A Survey,» IEEE Transactions on Intelligent Transportation Systems, nº 19(3), pp. 666-676, 2017
[8] H. Deery, «Hazard and risk perception among young novice drivers,» Safety Research, nº 30, pp. 225-236, 1999
[9] F. Saad, «Behavioural adaptions to new driver support systems: Some critical issues,» IEEE International Conference on System, Man and Cybernetics, pp. 288293, 2004
[10] M. Rafael, M. Sanchez, V. Mucino, J. Cervantes y A. Lozano, «Impact of driving styles on exhaust emissions and fuel economy from a heavy-duty truck: Laboratory tests,» International Journal of Heavy Vehicle System., nº 13, pp. 56-73, 2006.
[11] L. Kleisen, The relationship between thinking and driving styles and their contribution to young driver road safety., Bruce, Australia: University of Canberra, 2011.
[12] T. Lajunen y T. Özkan, «Self-report instruments and methods,» Handbook of traffic psychology, pp. 43-59, 2011.
[13] D. Dörr, D. Grabengiesser y F. Gauterin, «Online driving style recognition using fuzzy logic,» IEEE International Conference on Intelligent Trasportation Systems, nº 17, pp. 1021-1026, 2014.
[14] E. Gilman, A. Keskinarkaus, S. Tamminen, S. Pirttikangas, J. Röning y J. Riekki, «Personalised assistance for fuel-efficient driving,» Transportation Research Part C, vol. 58, pp. 681 - 705, 2015.
[15] F. Sagberg, Selpi, G. Bianchi y J. Engström, «A Review of Research on Driving Styles and Road Safety,» Human Factors and Ergonomics Society, vol. 7, nº 57, pp. 1248-1275, 2015.
[16] A. Aljaafreh, N. Alshabatat y Al-Din, «Driving style recognition using fuzzy logic,» de International Conference on Vehicular Electronics and Safety, 2012
[17] Z. Constantinescu, C. Marinoiu y M. Vladoiu, «Driving style analysis using data mining techniques,» International Journal of Computers Communications & Control, vol. 5, nº 5, pp. 654-663, 2010
[18] J. Cordero, J. Aguilar, K. Aguilar, D. Chávez y E. Puerto, «Recognition of the driving style in vehicle drivers,» Sensors, vol. 20, nº 9, 2020
[19] C. Deng, C. Wu, N. Lyu y Z. Huang, «Driving style recognition method using braking characteristics based on hidden Markov model,» PLOS ONE, vol. 12, nº 8, 2017.
[20] O. Derbel y R. Landry, «Driving style assessment based on the GPS data and fuzzy inference systems,» de 12th International Multi-Conference on Systems, Signals & Devices, doi:10.1109/ssd.2015.7348214 , 2015
[21] A. Donkers, D. Yang y M. Viktorović, «Influence of driving style, infrastructure, weather and traffic on electric vehicle performance,» Transportation research part D: transport and environment, 2020
[22] F. Jiménez, J. C. Amarillo, J. E. Naranjo, F. Serradilla y A. Díaz, «Energy consumption estimation in electric vehicles considering driving style,» de IEEE 18th International Conference on Intelligent Transportation Systems, 2015.
[23] T. Felstead, M. McDonald y M. Fowkes, «Driving style extremes and potential vehicle emission effects,» In Proceedings of the Institution of Civil Engineers-Transport, vol. 162, nº 3, pp. 141-148, 2009
[24] Y. Feng, S. Pickering, E. Chappell, P. Iravani y C. Brace, «Driving Style Modelling with Adaptive Neuro-Fuzzy Inference System and Real Driving Data,» In International Conference on Applied Human Factors and Ergonomics, pp. 481-490, 2018
[25] B. Gao, K. Cai, T. Qu, Y. Hu y H. Chen, «Personalized adaptive cruise control based on online driving style recognition technology and model predictive control,» IEEE transactions on vehicular technology, vol. 69, nº 11, pp. 12482-12496, 2020
[26] J. Guo, Y. Jiang, Y. Yu y W. Liu, «A novel energy consumption prediction model with combination of road information and driving style of BEVs,» Sustainable Energy Technologies and Assessments, 42, 100826, 2020.
[27] D. Johnson y M. Trivedi, «Driving style recognition using a smartphone as a sensor platform,» 14th International IEEE Conference on Intelligent Transportation Systems, pp. 1609-1615, 2011
[28] M. Karaduman y H. Eren, «Deep learning based traffic direction sign detection and determining driving style,» 2017 International Conference on Computer Science and Engineering, pp. 1046-1050, 2017
[29] C. F. Lee y P. Öberg, «Classification of Road Type and Driving Style using OBD Data,» SAE Technical Paper, 2015.
[30] K. Li, L. Jin, Y. Jiang, H. Xian y L. Gao, «Effects of driver behavior style differences and individual differences on driver sleepiness detection,» Advances in Mechanical Engineering, vol. 7, nº 4, 2015
[31] R. Liessner, A. Dietermann, B. Bäker y K. Lüpkes, «Derivation of real-world driving cycles corresponding to traffic situation and driving style on the basis of Markov models and cluster analyses,» de 6th Hybrid and Electric Vehicles Conference (HEVC 2016) , 2016.
[32] Y. Liu, J. Wang, P. Zhao, D. Qin y Z. Chen, «Research on classification and recognition of driving styles based on feature engineering,» IEEE Access, vol. 7, pp. 89245-89255, 2019.
[33] O. F. Ozgul, M. U. Cakir, M. Tan, M. F. Amasyali y H. T. Hayvaci, «Fully Unsupervised Framework for Scoring Driving Style,» de 2018 International Conference on Intelligent Systems (IS), 2018
[34] Y. Shi, N. Cui y Y. Du, «Energy Management Strategy based on Driving Style Recognition for Plug-in Hybrid Electric Bus,» de 2020 39th Chinese Control Conference, pp. 5511-5516, 2020.
[35] I. Silva y J. Eugenio Naranjo, «A systematic methodology to evaluate prediction models for driving style classification,» Sensors, vol. 20, nº 6, 2020
[37] T. Colombo, G. Panzani, S. Savaresi y P. Paparo, «Absolute driving style estimation for ground vehicles,» IEEE conference on control technology and applications, pp. 2196-2201, 2017.
[38] J. Gallus, U. Kirchner, R. Vogt y T. Benter, «Impact of driving style and road grade on gaseous exhaust emissions of passenger vehicles measured by a Portable Emission Measurement System (PEMS),» Transportation Research Part D: Transport and Environment 52, 215-226, 2017.
[39] P. Jardin, I. Moisidis, S. S. Zetina y S. Rinderknecht, «Rule-Based Driving Style Classification Using Acceleration Data Profiles,» 23rd International Conference on Intelligent Transportation Systems (ITSC), 2020
[40] G. Li, F. Zhu, X. Qu, B. Cheng, S. Li y P. Green, «Driving style classification based on driving operational pictures,» IEEE Access, 1-1, 2019
[41] J. E. Meseguer, C. K. Toh, C. T. Calafate, J. C. Cano y P. Manzoni, «Drivingstyles: a mobile platform for driving styles and fuel consumption characterization,» Journal of Communications and networks, vol. 19, nº 2, pp. 162-168, 2017
[42] A. Mohammadnazar, R. Arvin y A. Khattak, «Classifying travelers’ driving style using basic safety messages generated by connected vehicles: Application of unsupervised machine learning,» Transportation Research Part C, nº 122, 2021.
[43] G. Li, S. E. Li, B. Cheng y P. Green, «Estimation of driving style in naturalistic highway traffic using maneuver transition probabilities,» Transportation Research Part C: Emerging Technologies, vol. 74, pp. 113-125, 2017.
[44] V. Nikulin, «Driving style identification with unsupervised learning,» de In International Conference on Machine Learning and Data Mining in Pattern Recognition, Springer, Cham, 2016.
[45] K. M. Sentoff, L. Aultman-Hall y B. A. Holmén, «Implications of driving style and road grade for accurate vehicle activity data and emissions estimates,» Transportation Research Part D: Transport and Environment, vol. 35, pp. 175-188, 2015.
[46] F. Schockenhoff, H. Nehse y M. Lienkamp, «Maneuver-based objectification of user comfort affecting aspects of driving style of autonomous vehicle concepts,» Applied Sciences, vol. 10, nº 11, 2020
[47] O. Shouno, «Deep unsupervised learning of a topological map of vehicle maneuvers for characterizing driving styles,» de In 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 2917-2922, 2018
[48] M. Brambilla, P. Mascetti y A. Mauri, «Comparison of different driving style analysis approaches based on trip segmentation over GPS information,» de IEEE International Conference on Big Data (Big Data), 2017
[49] R. Wang y S. M. Lukic, «Review of Driving COnditions Prediction and Driving Style Recognition Based Control Algorithms for Hybrid Electric Vehicles,» de IEEE Vehicle Power and Propulsion Conference, 2011.
[50] G. Castignani, T. Derrmann, R. Frank y T. Engel, «Driver Behavior Profiling Using Smartphones: A Low-Cost Platform for Driver Monitoring,» IEEE Intelligent transportation systems magazine, vol. 7, nº 1, pp. 91-102, 2015.
[51] J. Barbé y G. Boy, «On-board system design to optimize energy management,» de In Proceedings of the European Annual Conference on Human Decision-Making and Manual Control, Valenciennes, France (pp. 27-29)., 2006
[52] O. H. Koskinen, «Improving vehicle fuel economy and reducing emissions by driving technique,» 15th World Congress on Intelligent Transport Systems and ITS America's, 2008.
[53] G. Priyadharshini y J. Femilda, «A comprehensive review of various data collection approaches, features, and algorithms used for the classification of driving style,» de Materials Science and Engineering, 2020
[54] S. Laapotti, E. Keskinen y S. Rajalin, «Comparison of young male and female drivers’ attitude and self-reported traffic behaviour in Finland in 1978 and 2001,» Journal of Safety Research, vol. 34, nº 5, p. 579–587, 2002
[55] D. De Waard, C. Dijksterhuis y K. A. Brookhuis, «Merging into heavy motorway traffic by young and elderly drivers,» Accident Analysis & Prevention, vol. 41, nº 3, p. 588– 597, 2009.
[56] B. Reimer, B. Donmez, M. Lavallière, B. Mehler, J. F. Coughlin y N. Teasdale, «Impact of age and cognitive demand on lane choice and changing under actual highway conditions.,» Accident Analysis & Prevention, 52, p. 125–132, 2013.
[57] F. M. Poó y R. D. Ledesma, «A Study on the Relationship Between Personality and Driving Styles,» Traffic Injury Prevention, vol. 14, nº 4, pp. 346-352, 2013.
[58] N. Karginova, S. Byttner y M. Svensson, «Data-driven methods for classification of driving styles in buses,» SAE Technical Paper Series, 2012.
[59] J. Rios-Torres, J. Liu y A. Khattak, «Fuel consumption for various driving styles in conventional and hybrid electric vehicles: Integrating driving cycle predictions with fuel consumption optimization,» International Journal of Sustainable Transportation, vol. 13, nº 2, pp. 123-137, 2019
[60] I. Del Campo, E. Asua, V. Martínez, Ó. Mata-Carballeira y J. Echanobe, «Driving style recognition based on ride comfort using a hybrid machine learning algorithm,» 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 3251-3258, 2018
[61] R. Stoichkov, Android smartphone application for driving style recognition, 2013. [
[62] H. Y. Tong y W. T. Hung, «A Framework for Developing Driving Cycles with On‐Road Driving Data,» Transport Reviews: A Transnational Transdisciplinary Journal, vol. 30, nº 5, pp. 589-615, 2010
[63] A. Gomez Hurtado, «Desarrollo de ciclos de conducción para el área metropolitana centro occidente – AMCO,» Pereira, 2014
[64] T. L. S. Barlow, I. McCrae y P. Boulter, A reference book of driving cycles for use in the measurement of road vehicle emissions, TRL Published Project Report: Tercera, 2009
[65] D. D. Espimberra, «Estudio de los ciclos de conducción para determinar párametros de manejo en condiciones reales de operación mediante la metodología Micro-Trip.,» Santo Domingo de los Tsáchilas, 2018
[66] A. Alessandrini, F. Filippi y F. Ortenzi, «Consumption calculation of vehicles using OBD data,» de In 20th International Emission Inventory Conference-" Emission Inventories-Meeting the Challenges Posed by Emerging Global, National, and Regional and Local Air Quality Issues, 2012
[67] P. Nouri y C. Morency, «Evaluating Microtrip Definitions for Developing Driving Cycles,» de Transportation Research Record: Journal of the Transportation Research Board, 2627, 86-92, 2017
[68] J. Huertas, L. Quirama, M. Giraldo y J. Díaz, «Comparison of Three Methods for Constructing Real Driving Cycles,» Energies, vol. 12, nº 4, 2019.
[69] J. I. Huertas, M. Giraldo, L. F. Quirama y J. Díaz, «Driving Cycles Based on Fuel Consumption,» energies, vol. 11, nº 11, 2018.
[70] W. Wang, J. Xi, A. Chong y L. Li, «Driving Style Classification Using a Semisupervised Support Vector Machine,» IEEE Transactions on Human-Machine Systems, vol. 47, nº 5, pp. 650-660, 2017.
[71] J. C. Ferreira, J. de Almeida y R. A. da Silva, «The Impact of Driving Styles on Fuel Consumption: A Data-Warehouse-and-Data-Mining-Based Discovery Process,» IEEE Transactions on Intelligent Transportation Systems, vol. 16, nº 5, pp. 2653-2662, 2015
[72] J. Heywood, «Internal combustion engine fundamentals,» Mcgraw-hill, New York, 1998
[73] B. Shi, L. Xu, J. Hu, Y. Tang, H. Jiang, W. Meng y H. Liu, «Evaluating Driving Styles by Normalizing Driving Behavior Based on Personalized Driver Modeling,» IEEE Transactions on Intelligent Transportation Systems, vol. 45, nº 12, pp. 1502-1508, 2015
[74] W. Wang y J. Xi, «A Rapid Pattern-Recognition Method for Driving Styles Using Clustering-Based Support Vector Machines,» de American Control Conference (ACC), Boston, 2016
[75] G. Castignani, T. Derrmann, R. Frank y T. Engel, «Smartphone-Based Adaptive Driving Maneuver Detection: A Large-Scale Evaluation Study,» IEEE Transactions on Intelligent Transportation Systems, vol. 18, nº 9, pp. 2330-2339, 2017
[76] F. Martinelli, F. Mercaldo, A. Orlando, V. Nardone, A. Santone y A. Sangaiah, «Human behavior characterization for driving style recognition in vehicle system,» Computers and Electrical Engineering, 2018.
[77] I. S. Feraud y J. E. Naranjo, «Are you a good driver? A Data-driven Approach to Estimate Driving Style,» de 11th International Conference on Computer Modeling and Simulation (ICCMS), 2019.
[78] J. Fan, Y. Li, Y. Liu, Y. Zhang y C. Ma, «Analysis of taxi driving behavior and driving risk based on trajectory data,» IEEE Intelligent Vehicles Symposium (IV), 2019
[79] P. Seers, G. Nachin y M. Glaus, «Development of two driving cycles for utility vehicles,» Transportation Research Part D: Transport and Environment, pp. 377-385, 2015.
[80] J. Brady y M. O'Mahony, «Development of a driving cycle to evaluate the energy economy of electric vehicles in urban areas,» Applied Energy, pp. 165-178, 2016
[81] N. H. Arun, S. Mahesh y G. Ramadurai, «Development of driving cycles for passenger cars and motorcycles in Chennai, India,» Sustainable Cities and Society, pp. 508-512, 2017
[82] J. Huertas, J. Díaz, D. Cordero y K. Cedillo, «A new methodology to determine typical driving cycles for the design of vehicles power trains,» International Journal on Interactive Design and Manufacturing (IJIDeM), vol. 12, nº 1, pp. 319-326, 2017
[83] J. Zhang, Z. Wang, P. Liu, Z. Zhang, X. Li y C. Qu, «Driving cycles construction for electric vehicles considering road environment: A case study in Beijing,» Applied Energy, 253, 113514, 2019
[84] C. M. León, Estimación del consumo de combustible mediante la determinación de ciclos de conducción representativos en Bucaramanga, Santander., Bucaramanga, 2019
[85] L. F. Quirama, M. Giraldo, J. I. Huertas y M. Jallerd, «Driving cycles that reproduce driving patterns, energy consumptions and tailpipe emissions,» Transportation Research Part D: Transport and Environment, 82, 102294, 2020
[86] R. Yu, X. Long y J. Li, «Driving Style Analyses for Car-sharing Users Utilizing Lowfrequency Trajectory Data,» de 5th International Conference on Transportation Information and Safety (ICTIS), 2019
[87] Y. Feng, S. Pickering, E. Chappell, P. Iravani y C. Brace, «A support vector clustering based approach for driving style classification,» International Journal of Machine Learning and Computing, vol. 9, nº 3, pp. 344-350, 2019.
[88] W. Han, W. Wang, X. Li y J. Xi, «Statistical-based approach for driving style recognition using Bayesian probability with kernel density estimation,» IET Intelligent Transport Systems, vol. 13, nº 1, pp. 22-30, 2019
[89] Universidad Industrial de Santander, «Plan maestro de movilidad, área metropolitana de Bucaramanga 2011-2030,» Bucaramanga.
[90] J. Jiménez-Palacios, Understanding and Quantifying Motor Vehicle Emissions with Vehicle Specific Power and TILDAS Remote Sensing, Massachusetts, 1999
[91] W. Hung, H. Tong, C. Lee, K. Ha y L. Pao, «Development of a practical driving cycle construction methodology: A case study in Hong Kong,» Transportation Research Part D: Transport and Environment, vol. 12, nº 2, pp. 115-128
[92] «Embitel,» [En línea]. Available: https://www.embitel.com/automotive-insights/onboard-diagnostics-obd-ii-stack. [Último acceso: 02 Agosto 2021].
[93] «Sparkfun,» [En línea]. Available: https://learn.sparkfun.com/tutorials/accelerometerbasics. [Último acceso: 02 Agosto 2021]
[94] J. D. Molina Martínez y B. F. Acuña Olivar, Clasificación de estilos de conducción en el área metropolitana de Bucaramanga con monitoreo a bordo (OBD II) en condiciones reales de carretera, Bucaramanga: Universidad Autónoma de Bucaramanga, 2022
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dc.publisher.faculty.spa.fl_str_mv Facultad Ingeniería
dc.publisher.program.spa.fl_str_mv Pregrado Ingeniería Mecatrónica
institution Universidad Autónoma de Bucaramanga - UNAB
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spelling Maradey Lázaro, Jessica Gissellad6570851-23e5-44e4-8c29-fd312d351b94Huertas Cardozo, José Ignacio17418668-38f4-44e4-87f6-3705d87a6144Molina Martínez, Juan Danilo66a36440-49ff-4e4a-8278-d30e81324f6eAcuña Olivar, Brayan Ferney0f1d7958-b392-4d21-bd55-c02e8feaaedaMaradey Lázaro, Jessica Gissella [0000040553]Huertas Cardozo, José Ignacio [0000057398]Huertas Cardozo, José Ignacio [es&oi=ao]Maradey Lázaro, Jessica Gissella [0000-0003-2319-1965]Huertas Cardozo, José Ignacio [0000-0003-4508-6453]Maradey Lázaro, Jessica Gissella [profile/Jessica-Maradey-Lazaro]Bucaramanga (Santander, Colombia)2022-06-28T18:53:13Z2022-06-28T18:53:13Z2022-05-31http://hdl.handle.net/20.500.12749/16806instname:Universidad Autónoma de Bucaramanga - UNABreponame:Repositorio Institucional UNABrepourl:https://repository.unab.edu.coLos sistemas inteligentes de transporte (SIT) permiten optimizar el uso de la infraestructura existente incrementando el control, la efectividad, la eficiencia y la seguridad de los sistemas y la infraestructura de transporte, con el fin de gestionar la creciente demanda de movilidad [1]. Para desarrollar SIT eficaces es muy importante realizar campañas de monitoreo en condiciones reales de carretera que permitan la recolección de datos que describen el patrón de conducción de una región de interés. En el proyecto desarrollado se implementó un sistema de monitoreo a bordo (OBD II) con conexión a bluetooth en una muestra de 16 vehículos adquiriendo datos durante los meses de agosto a diciembre del año 2021 creando una base de datos para el área metropolitana de Bucaramanga con la que se describió el patrón de conducción a partir de tres conceptos, ciclos de conducción, diagramas de distribución de la frecuencia de velocidad- aceleración y la potencia específica del vehículo. También se abordó el tema de estilos de conducción a partir de los métodos de aceleración y del Jerk siendo este otro elemento que permite conocer más sobre los hábitos de conducción de los conductores de la región estudiada. El ciclo desarrollado se construyó con el método Micro Trips Fuel Based (MTFBM) alcanzando una similitud <15% de las diferencias relativas promedio de los parámetros característicos del 68.75%, mientras que el SAFD y el VSP indicaron que las personas conducían en la región a velocidades y aceleraciones bajas, debido a la alta densidad de tráfico. Con los estilos de conducción se validó que un estilo de conducción agresivo aumenta el consumo de combustible en más del 20%.1. INTRODUCCIÓN ...................................................................................................... 13 1.1 DESCRIPCIÓN DEL PROBLEMA .................................................................... 13 1.2 JUSTIFICACIÓN DEL PROBLEMA .................................................................. 14 1.3 OBJETIVOS ...................................................................................................... 15 1.3.2 Objetivos específicos .................................................................................. 15 2. MARCO TEÓRICO ................................................................................................... 16 2.1 ESTILOS DE CONDUCCIÓN ............................................................................ 16 2.1.1 Definición del estilo de conducción .................................................................. 16 2.1.1 Clasificación de estilos de conducción ............................................................. 17 2.1.2 Importancia de los estilos de conducción ................................................... 18 2.1.3 Factores que influyen en los estilos de conducción .................................... 18 2.1.4 Instrumentación utilizada para la adquisición de datos ............................... 19 2.1.5 Métodos para la clasificación de estilos de conducción. ............................. 20 2.2 CICLOS DE CONDUCCIÓN .............................................................................. 21 2.2.1 Definición de ciclos de conducción .................................................................. 21 2.2.1 Tipos de ciclos de conducción ......................................................................... 22 2.2.2 Métodos para el desarrollo de ciclos de conducción ................................... 24 2.2.3 Metodología base para la construcción de ciclos de conducción. ............... 26 3. ESTADO DEL ARTE ................................................................................................ 27 3.1 ESTILOS DE CONDUCCIÓN ............................................................................ 27 3.2 CICLOS DE CONDUCCIÓN .............................................................................. 31 4. METODOLOGÍA ...................................................................................................... 34 4.1 CAMPAÑA DE MONITOREO ........................................................................... 35 4.1.1 Ruta seleccionada ...................................................................................... 35 4.1.2 Datos técnicos de los vehículos monitoreados ........................................... 36 4.1.3 Datos sociodemográficos de los conductores ............................................. 37 4.1.4 Variables monitoreadas .............................................................................. 38 4.2 SISTEMA DE MONITOREO IMPLEMENTADO ................................................ 38 4.2.1 Sistema de adquisición de datos ................................................................ 39 4.2.2 Tipo de conectividad para el envío de información ..................................... 41 4.2.3 Registrador de datos .................................................................................. 43 4.2.4 Almacenamiento de datos en la nube ......................................................... 46 4.3 ADQUISICIÓN DE DATOS ............................................................................... 47 4.4 ELIMINACIÓN DE DATOS ATÍPICOS .............................................................. 48 4.5 REGISTRO DE DATOS EN LA NUBE .............................................................. 50 4.6 METODOLOGÍA APLICADA PARA LA CLASIFICACIÓN DE ESTILOS DE CONDUCCIÓN ............................................................................................................ 50 4.6.1 Selección de las características para la clasificación de los estilos de conducción ............................................................................................................... 51 4.6.2 Segmentación del tipo de carretera ............................................................ 54 4.6.3 Identificación de los rangos intercuartílicos ................................................. 54 4.6.4 Método de la aceleración para la clasificación de estilos de conducción .... 55 4.6.5 Método del Jerk para la clasificación de estilos de conducción ................... 56 4.6.6 Construcción del algoritmo desarrollado ..................................................... 56 4.7 MÉTODO APLICADO PARA LA CONSTRUCCIÓN DEL CICLO DE CONDUCCIÓN ............................................................................................................ 57 4.7.1 Método micro-trips fuel based method (MTFBM) ........................................ 57 4.7.2 Selección de los parámetros característicos ............................................... 58 4.7.3 Ecuaciones para el cálculo de los parámetros característicos .................... 58 4.7.4 Cálculos de los parámetros característicos de los datos monitoreados ...... 60 4.7.5 Obtención de los micro viajes ..................................................................... 61 4.7.6 Clúster y distribución de probabilidad ......................................................... 61 4.7.7 Selección cuasi aleatoria y empalme de los micro viajes ............................ 62 4.7.8 Validación del ciclo de conducción ............................................................. 62 4.8 POTENCIA ESPECÍFICA DEL VEHÍCULO (VSP) ............................................ 65 4.8.1 Proceso de obtención de las variables para calcular el VSP....................... 66 4.9 DISTRIBUCIÓN DE FRECUENCIA DE VELOCIDAD-ACELERACIÓN (SAFD) 67 4.9.1 Proceso de obtención del diagrama SAFD ................................................. 67 5. RESULTADOS Y ANÁLISIS DE DATOS ................................................................. 68 5.1 BASE DE DATOS PROYECTO ACTUAL 2022 ................................................ 68 5.2 BASE DE DATOS CONCATENADA (PROYECTO 2021 Y 2022) .................... 69 5.3 CICLOS DE CONDUCCIÓN OBTENIDOS, MUESTRA DE 16 Y 26 VEHÍCULOS 70 5.3.1 Parámetros característicos y diferencias relativas .......................................... 72 5.4 ANÁLISIS DE LA POTENCIA ESPECIFICA DEL VEHÍCULO ......................... 73 5.5 ANÁLISIS DE LOS DIAGRAMAS SAFD .......................................................... 75 5.5.1 Análisis de la variable de velocidad en los diagramas SAFD ...................... 75 5.5.2 Análisis de la variable de aceleración en los diagramas SAFD ................... 76 5.5.3 Análisis del diagrama SAFD de forma generalizada ................................... 77 5.6 CLASIFICACIÓN DE ESTILOS DE CONDUCCIÓN MUESTRA DE 16 VEHÍCULOS ................................................................................................................ 78 5.6.1 Clasificación de estilos de conducción base de datos general .................... 78 5.6.2 Correlación del consumo de combustible y los estilos de conducción ........ 80 5.6.3 Consumo de combustible por tipo de carretera........................................... 81 5.7 CLASIFICACIÓN DE ESTILOS DE CONDUCCIÓN POR CONDUCTOR ......... 81 5.7.1 Clasificación de estilos de conducción por conductor ................................. 82 5.7.2 Correlación del consumo de combustible y los estilos de conducción ........ 84 5.7.3 Clasificación de los estilos de conducción por conductor y correlación de la edad. 85 5.7.4 Correlación del consumo de combustible y los estilos de conducción por cada conductor. ........................................................................................................ 86 6. VALIDACIÓN Y COMPARACIÓN DEL CICLO DE CONDUCCIÓN ......................... 87 6.1 COMPARACIÓN DE LOS PARÁMETROS CARACTERÍSTICOS ......................... 87 6.1.1 Comparación con los ciclos de conducción desarrollados en Bucaramanga .. 88 6.1.2 Comparación con los ciclos de conducción desarrollados para la homologación........................................................................................................... 88 6.2 VALIDACIÓN DE LOS CICLOS DE CONDUCCIÓN......................................... 91 6.2.1 Validación del ciclo de conducción a partir de la diferencia relativa promedio 91 7. CONCLUSIONES ..................................................................................................... 93 8. RECOMENDACIONES Y TRABAJOS A FUTURO .................................................. 95 BIBLIOGRAFÍA ................................................................................................................ 96 9. ANEXOS ................................................................................................................ 103PregradoIntelligent transport systems (ITS) allow optimizing the use of existing infrastructure by increasing the control, effectiveness, efficiency and safety of transport systems and infrastructure, in order to manage the growing demand for mobility [1] . To develop effective SITs, it is very important to carry out monitoring campaigns in real road conditions that allow the collection of data that describe the driving pattern of a region of interest. In the developed project, an on-board monitoring system (OBD II) with bluetooth connection was implemented in a sample of 16 vehicles, acquiring data during the months of August to December of the year 2021, creating a database for the metropolitan area of ​​Bucaramanga with which described the driving pattern from three concepts, driving cycles, speed-acceleration frequency distribution diagrams and the specific power of the vehicle. The issue of driving styles was also addressed based on acceleration and Jerk methods, this being another element that allows us to learn more about the driving habits of drivers in the region studied. The developed cycle was built with the Micro Trips Fuel Based (MTFBM) method, reaching a similarity <15% of the average relative differences of the characteristic parameters of 68.75%, while the SAFD and the VSP indicated that people drove in the region at low speeds and accelerations, due to the high density of traffic. With the driving styles it was validated that an aggressive driving style increases fuel consumption by more than 20%.application/pdfspahttp://creativecommons.org/licenses/by-nc-nd/2.5/co/Abierto (Texto Completo)Atribución-NoComercial-SinDerivadas 2.5 Colombiahttp://purl.org/coar/access_right/c_abf2Clasificación de estilos de conducción en el área metropolitana de Bucaramanga con monitoreo a bordo (OBD II) en condiciones reales de carreteraClassification of driving styles in the metropolitan area of ​​Bucaramanga with on-board monitoring (OBD II) in real road conditionIngeniero MecatrónicoUniversidad Autónoma de Bucaramanga UNABFacultad IngenieríaPregrado Ingeniería Mecatrónicainfo:eu-repo/semantics/bachelorThesisTrabajo de Gradohttp://purl.org/coar/resource_type/c_7a1fhttp://purl.org/redcol/resource_type/TPMechatronicMicro trip fuel based methodDriving stylesDriving cyclesOn-board diagnosticsRoad safetyGround transportationElectronic data processingAutomobilesMecatrónicaSeguridad vialTransporte terrestreProcesamiento electrónico de datosAutomóvilesEstilos de conducciónCiclos de conducciónDiagnóstico a bordo[1] GSD+, «Esquema de implantación de tecnologías inteligentes de transporte en América Latina: estudios de casos y recomendaciones.,» 2018[2] Vanguardia, «Vanguardia,» 16 Julio 2019. [En línea]. Available: https://www.vanguardia.com/area-metropolitana/bucaramanga/transitan-4053automotores-nuevos-este-es-el-impacto-en-el-area-LG1190481. [Último acceso: 11 Julio 2021].[3] Dirección de Tránsito de Bucaramanga, «Informe de gestión 1 trimestre,» Bucaramanga, 2019[4] Alcaldía de Bucaramanga, «Bucaramanga ciudad de oportunidades,» Bucaramanga, 2020.[5] Filial de Isa, «Memoria de sostenibilidad sistemas inteligentes en red,» Medellín, 2014.[6] S. Navarro y R. García, Desarrollo de un ciclo de conducción bajo condiciones reales de carretera en el área metropolitana de Bucaramanga, Bucaramanga, 2021[7] C. Martínez, M. Heucke, F.-y. Wang, B. Gao y D. Cao, «Driving Style Recognition for Intelligent Vehicle Control and Advanced Driver Assistance: A Survey,» IEEE Transactions on Intelligent Transportation Systems, nº 19(3), pp. 666-676, 2017[8] H. Deery, «Hazard and risk perception among young novice drivers,» Safety Research, nº 30, pp. 225-236, 1999[9] F. Saad, «Behavioural adaptions to new driver support systems: Some critical issues,» IEEE International Conference on System, Man and Cybernetics, pp. 288293, 2004[10] M. Rafael, M. Sanchez, V. Mucino, J. Cervantes y A. Lozano, «Impact of driving styles on exhaust emissions and fuel economy from a heavy-duty truck: Laboratory tests,» International Journal of Heavy Vehicle System., nº 13, pp. 56-73, 2006.[11] L. Kleisen, The relationship between thinking and driving styles and their contribution to young driver road safety., Bruce, Australia: University of Canberra, 2011.[12] T. Lajunen y T. Özkan, «Self-report instruments and methods,» Handbook of traffic psychology, pp. 43-59, 2011.[13] D. Dörr, D. Grabengiesser y F. Gauterin, «Online driving style recognition using fuzzy logic,» IEEE International Conference on Intelligent Trasportation Systems, nº 17, pp. 1021-1026, 2014.[14] E. Gilman, A. Keskinarkaus, S. Tamminen, S. Pirttikangas, J. Röning y J. Riekki, «Personalised assistance for fuel-efficient driving,» Transportation Research Part C, vol. 58, pp. 681 - 705, 2015.[15] F. Sagberg, Selpi, G. Bianchi y J. Engström, «A Review of Research on Driving Styles and Road Safety,» Human Factors and Ergonomics Society, vol. 7, nº 57, pp. 1248-1275, 2015.[16] A. Aljaafreh, N. Alshabatat y Al-Din, «Driving style recognition using fuzzy logic,» de International Conference on Vehicular Electronics and Safety, 2012[17] Z. Constantinescu, C. Marinoiu y M. Vladoiu, «Driving style analysis using data mining techniques,» International Journal of Computers Communications & Control, vol. 5, nº 5, pp. 654-663, 2010[18] J. Cordero, J. Aguilar, K. Aguilar, D. Chávez y E. Puerto, «Recognition of the driving style in vehicle drivers,» Sensors, vol. 20, nº 9, 2020[19] C. Deng, C. Wu, N. Lyu y Z. Huang, «Driving style recognition method using braking characteristics based on hidden Markov model,» PLOS ONE, vol. 12, nº 8, 2017.[20] O. Derbel y R. Landry, «Driving style assessment based on the GPS data and fuzzy inference systems,» de 12th International Multi-Conference on Systems, Signals & Devices, doi:10.1109/ssd.2015.7348214 , 2015[21] A. Donkers, D. Yang y M. Viktorović, «Influence of driving style, infrastructure, weather and traffic on electric vehicle performance,» Transportation research part D: transport and environment, 2020[22] F. Jiménez, J. C. Amarillo, J. E. Naranjo, F. Serradilla y A. Díaz, «Energy consumption estimation in electric vehicles considering driving style,» de IEEE 18th International Conference on Intelligent Transportation Systems, 2015.[23] T. Felstead, M. McDonald y M. Fowkes, «Driving style extremes and potential vehicle emission effects,» In Proceedings of the Institution of Civil Engineers-Transport, vol. 162, nº 3, pp. 141-148, 2009[24] Y. Feng, S. Pickering, E. Chappell, P. Iravani y C. Brace, «Driving Style Modelling with Adaptive Neuro-Fuzzy Inference System and Real Driving Data,» In International Conference on Applied Human Factors and Ergonomics, pp. 481-490, 2018[25] B. Gao, K. Cai, T. Qu, Y. Hu y H. Chen, «Personalized adaptive cruise control based on online driving style recognition technology and model predictive control,» IEEE transactions on vehicular technology, vol. 69, nº 11, pp. 12482-12496, 2020[26] J. Guo, Y. Jiang, Y. Yu y W. Liu, «A novel energy consumption prediction model with combination of road information and driving style of BEVs,» Sustainable Energy Technologies and Assessments, 42, 100826, 2020.[27] D. Johnson y M. Trivedi, «Driving style recognition using a smartphone as a sensor platform,» 14th International IEEE Conference on Intelligent Transportation Systems, pp. 1609-1615, 2011[28] M. Karaduman y H. Eren, «Deep learning based traffic direction sign detection and determining driving style,» 2017 International Conference on Computer Science and Engineering, pp. 1046-1050, 2017[29] C. F. Lee y P. Öberg, «Classification of Road Type and Driving Style using OBD Data,» SAE Technical Paper, 2015.[30] K. Li, L. Jin, Y. Jiang, H. Xian y L. Gao, «Effects of driver behavior style differences and individual differences on driver sleepiness detection,» Advances in Mechanical Engineering, vol. 7, nº 4, 2015[31] R. Liessner, A. Dietermann, B. Bäker y K. Lüpkes, «Derivation of real-world driving cycles corresponding to traffic situation and driving style on the basis of Markov models and cluster analyses,» de 6th Hybrid and Electric Vehicles Conference (HEVC 2016) , 2016.[32] Y. Liu, J. Wang, P. Zhao, D. Qin y Z. Chen, «Research on classification and recognition of driving styles based on feature engineering,» IEEE Access, vol. 7, pp. 89245-89255, 2019.[33] O. F. Ozgul, M. U. Cakir, M. Tan, M. F. Amasyali y H. T. Hayvaci, «Fully Unsupervised Framework for Scoring Driving Style,» de 2018 International Conference on Intelligent Systems (IS), 2018[34] Y. Shi, N. Cui y Y. Du, «Energy Management Strategy based on Driving Style Recognition for Plug-in Hybrid Electric Bus,» de 2020 39th Chinese Control Conference, pp. 5511-5516, 2020.[35] I. Silva y J. Eugenio Naranjo, «A systematic methodology to evaluate prediction models for driving style classification,» Sensors, vol. 20, nº 6, 2020[37] T. Colombo, G. Panzani, S. Savaresi y P. Paparo, «Absolute driving style estimation for ground vehicles,» IEEE conference on control technology and applications, pp. 2196-2201, 2017.[38] J. Gallus, U. Kirchner, R. Vogt y T. Benter, «Impact of driving style and road grade on gaseous exhaust emissions of passenger vehicles measured by a Portable Emission Measurement System (PEMS),» Transportation Research Part D: Transport and Environment 52, 215-226, 2017.[39] P. Jardin, I. Moisidis, S. S. Zetina y S. Rinderknecht, «Rule-Based Driving Style Classification Using Acceleration Data Profiles,» 23rd International Conference on Intelligent Transportation Systems (ITSC), 2020[40] G. Li, F. Zhu, X. Qu, B. Cheng, S. Li y P. Green, «Driving style classification based on driving operational pictures,» IEEE Access, 1-1, 2019[41] J. E. Meseguer, C. K. Toh, C. T. Calafate, J. C. Cano y P. Manzoni, «Drivingstyles: a mobile platform for driving styles and fuel consumption characterization,» Journal of Communications and networks, vol. 19, nº 2, pp. 162-168, 2017[42] A. Mohammadnazar, R. Arvin y A. Khattak, «Classifying travelers’ driving style using basic safety messages generated by connected vehicles: Application of unsupervised machine learning,» Transportation Research Part C, nº 122, 2021.[43] G. Li, S. E. Li, B. Cheng y P. Green, «Estimation of driving style in naturalistic highway traffic using maneuver transition probabilities,» Transportation Research Part C: Emerging Technologies, vol. 74, pp. 113-125, 2017.[44] V. Nikulin, «Driving style identification with unsupervised learning,» de In International Conference on Machine Learning and Data Mining in Pattern Recognition, Springer, Cham, 2016.[45] K. M. Sentoff, L. Aultman-Hall y B. A. Holmén, «Implications of driving style and road grade for accurate vehicle activity data and emissions estimates,» Transportation Research Part D: Transport and Environment, vol. 35, pp. 175-188, 2015.[46] F. Schockenhoff, H. Nehse y M. Lienkamp, «Maneuver-based objectification of user comfort affecting aspects of driving style of autonomous vehicle concepts,» Applied Sciences, vol. 10, nº 11, 2020[47] O. Shouno, «Deep unsupervised learning of a topological map of vehicle maneuvers for characterizing driving styles,» de In 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 2917-2922, 2018[48] M. Brambilla, P. Mascetti y A. Mauri, «Comparison of different driving style analysis approaches based on trip segmentation over GPS information,» de IEEE International Conference on Big Data (Big Data), 2017[49] R. Wang y S. M. Lukic, «Review of Driving COnditions Prediction and Driving Style Recognition Based Control Algorithms for Hybrid Electric Vehicles,» de IEEE Vehicle Power and Propulsion Conference, 2011.[50] G. Castignani, T. Derrmann, R. Frank y T. Engel, «Driver Behavior Profiling Using Smartphones: A Low-Cost Platform for Driver Monitoring,» IEEE Intelligent transportation systems magazine, vol. 7, nº 1, pp. 91-102, 2015.[51] J. Barbé y G. Boy, «On-board system design to optimize energy management,» de In Proceedings of the European Annual Conference on Human Decision-Making and Manual Control, Valenciennes, France (pp. 27-29)., 2006[52] O. H. Koskinen, «Improving vehicle fuel economy and reducing emissions by driving technique,» 15th World Congress on Intelligent Transport Systems and ITS America's, 2008.[53] G. Priyadharshini y J. Femilda, «A comprehensive review of various data collection approaches, features, and algorithms used for the classification of driving style,» de Materials Science and Engineering, 2020[54] S. Laapotti, E. Keskinen y S. Rajalin, «Comparison of young male and female drivers’ attitude and self-reported traffic behaviour in Finland in 1978 and 2001,» Journal of Safety Research, vol. 34, nº 5, p. 579–587, 2002[55] D. De Waard, C. Dijksterhuis y K. A. Brookhuis, «Merging into heavy motorway traffic by young and elderly drivers,» Accident Analysis & Prevention, vol. 41, nº 3, p. 588– 597, 2009.[56] B. Reimer, B. Donmez, M. Lavallière, B. Mehler, J. F. Coughlin y N. Teasdale, «Impact of age and cognitive demand on lane choice and changing under actual highway conditions.,» Accident Analysis & Prevention, 52, p. 125–132, 2013.[57] F. M. Poó y R. D. Ledesma, «A Study on the Relationship Between Personality and Driving Styles,» Traffic Injury Prevention, vol. 14, nº 4, pp. 346-352, 2013.[58] N. Karginova, S. Byttner y M. Svensson, «Data-driven methods for classification of driving styles in buses,» SAE Technical Paper Series, 2012.[59] J. Rios-Torres, J. Liu y A. Khattak, «Fuel consumption for various driving styles in conventional and hybrid electric vehicles: Integrating driving cycle predictions with fuel consumption optimization,» International Journal of Sustainable Transportation, vol. 13, nº 2, pp. 123-137, 2019[60] I. Del Campo, E. Asua, V. Martínez, Ó. Mata-Carballeira y J. Echanobe, «Driving style recognition based on ride comfort using a hybrid machine learning algorithm,» 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 3251-3258, 2018[61] R. Stoichkov, Android smartphone application for driving style recognition, 2013. [[62] H. Y. Tong y W. T. Hung, «A Framework for Developing Driving Cycles with On‐Road Driving Data,» Transport Reviews: A Transnational Transdisciplinary Journal, vol. 30, nº 5, pp. 589-615, 2010[63] A. Gomez Hurtado, «Desarrollo de ciclos de conducción para el área metropolitana centro occidente – AMCO,» Pereira, 2014[64] T. L. S. Barlow, I. McCrae y P. Boulter, A reference book of driving cycles for use in the measurement of road vehicle emissions, TRL Published Project Report: Tercera, 2009[65] D. D. Espimberra, «Estudio de los ciclos de conducción para determinar párametros de manejo en condiciones reales de operación mediante la metodología Micro-Trip.,» Santo Domingo de los Tsáchilas, 2018[66] A. Alessandrini, F. Filippi y F. Ortenzi, «Consumption calculation of vehicles using OBD data,» de In 20th International Emission Inventory Conference-" Emission Inventories-Meeting the Challenges Posed by Emerging Global, National, and Regional and Local Air Quality Issues, 2012[67] P. Nouri y C. Morency, «Evaluating Microtrip Definitions for Developing Driving Cycles,» de Transportation Research Record: Journal of the Transportation Research Board, 2627, 86-92, 2017[68] J. Huertas, L. Quirama, M. Giraldo y J. Díaz, «Comparison of Three Methods for Constructing Real Driving Cycles,» Energies, vol. 12, nº 4, 2019.[69] J. I. Huertas, M. Giraldo, L. F. Quirama y J. Díaz, «Driving Cycles Based on Fuel Consumption,» energies, vol. 11, nº 11, 2018.[70] W. Wang, J. Xi, A. Chong y L. Li, «Driving Style Classification Using a Semisupervised Support Vector Machine,» IEEE Transactions on Human-Machine Systems, vol. 47, nº 5, pp. 650-660, 2017.[71] J. C. Ferreira, J. de Almeida y R. A. da Silva, «The Impact of Driving Styles on Fuel Consumption: A Data-Warehouse-and-Data-Mining-Based Discovery Process,» IEEE Transactions on Intelligent Transportation Systems, vol. 16, nº 5, pp. 2653-2662, 2015[72] J. Heywood, «Internal combustion engine fundamentals,» Mcgraw-hill, New York, 1998[73] B. Shi, L. Xu, J. Hu, Y. Tang, H. Jiang, W. Meng y H. Liu, «Evaluating Driving Styles by Normalizing Driving Behavior Based on Personalized Driver Modeling,» IEEE Transactions on Intelligent Transportation Systems, vol. 45, nº 12, pp. 1502-1508, 2015[74] W. Wang y J. Xi, «A Rapid Pattern-Recognition Method for Driving Styles Using Clustering-Based Support Vector Machines,» de American Control Conference (ACC), Boston, 2016[75] G. Castignani, T. Derrmann, R. Frank y T. Engel, «Smartphone-Based Adaptive Driving Maneuver Detection: A Large-Scale Evaluation Study,» IEEE Transactions on Intelligent Transportation Systems, vol. 18, nº 9, pp. 2330-2339, 2017[76] F. Martinelli, F. Mercaldo, A. Orlando, V. Nardone, A. Santone y A. Sangaiah, «Human behavior characterization for driving style recognition in vehicle system,» Computers and Electrical Engineering, 2018.[77] I. S. Feraud y J. E. Naranjo, «Are you a good driver? A Data-driven Approach to Estimate Driving Style,» de 11th International Conference on Computer Modeling and Simulation (ICCMS), 2019.[78] J. Fan, Y. Li, Y. Liu, Y. Zhang y C. Ma, «Analysis of taxi driving behavior and driving risk based on trajectory data,» IEEE Intelligent Vehicles Symposium (IV), 2019[79] P. Seers, G. Nachin y M. Glaus, «Development of two driving cycles for utility vehicles,» Transportation Research Part D: Transport and Environment, pp. 377-385, 2015.[80] J. Brady y M. O'Mahony, «Development of a driving cycle to evaluate the energy economy of electric vehicles in urban areas,» Applied Energy, pp. 165-178, 2016[81] N. H. Arun, S. Mahesh y G. Ramadurai, «Development of driving cycles for passenger cars and motorcycles in Chennai, India,» Sustainable Cities and Society, pp. 508-512, 2017[82] J. Huertas, J. Díaz, D. Cordero y K. Cedillo, «A new methodology to determine typical driving cycles for the design of vehicles power trains,» International Journal on Interactive Design and Manufacturing (IJIDeM), vol. 12, nº 1, pp. 319-326, 2017[83] J. Zhang, Z. Wang, P. Liu, Z. Zhang, X. Li y C. Qu, «Driving cycles construction for electric vehicles considering road environment: A case study in Beijing,» Applied Energy, 253, 113514, 2019[84] C. M. León, Estimación del consumo de combustible mediante la determinación de ciclos de conducción representativos en Bucaramanga, Santander., Bucaramanga, 2019[85] L. F. Quirama, M. Giraldo, J. I. Huertas y M. Jallerd, «Driving cycles that reproduce driving patterns, energy consumptions and tailpipe emissions,» Transportation Research Part D: Transport and Environment, 82, 102294, 2020[86] R. Yu, X. Long y J. Li, «Driving Style Analyses for Car-sharing Users Utilizing Lowfrequency Trajectory Data,» de 5th International Conference on Transportation Information and Safety (ICTIS), 2019[87] Y. Feng, S. Pickering, E. Chappell, P. Iravani y C. Brace, «A support vector clustering based approach for driving style classification,» International Journal of Machine Learning and Computing, vol. 9, nº 3, pp. 344-350, 2019.[88] W. Han, W. Wang, X. Li y J. Xi, «Statistical-based approach for driving style recognition using Bayesian probability with kernel density estimation,» IET Intelligent Transport Systems, vol. 13, nº 1, pp. 22-30, 2019[89] Universidad Industrial de Santander, «Plan maestro de movilidad, área metropolitana de Bucaramanga 2011-2030,» Bucaramanga.[90] J. Jiménez-Palacios, Understanding and Quantifying Motor Vehicle Emissions with Vehicle Specific Power and TILDAS Remote Sensing, Massachusetts, 1999[91] W. Hung, H. Tong, C. Lee, K. Ha y L. Pao, «Development of a practical driving cycle construction methodology: A case study in Hong Kong,» Transportation Research Part D: Transport and Environment, vol. 12, nº 2, pp. 115-128[92] «Embitel,» [En línea]. Available: https://www.embitel.com/automotive-insights/onboard-diagnostics-obd-ii-stack. [Último acceso: 02 Agosto 2021].[93] «Sparkfun,» [En línea]. Available: https://learn.sparkfun.com/tutorials/accelerometerbasics. [Último acceso: 02 Agosto 2021][94] J. D. Molina Martínez y B. F. Acuña Olivar, Clasificación de estilos de conducción en el área metropolitana de Bucaramanga con monitoreo a bordo (OBD II) en condiciones reales de carretera, Bucaramanga: Universidad Autónoma de Bucaramanga, 2022ORIGINAL2022_Tesis_Juan_Danilo_Molina_Martinez.pdf2022_Tesis_Juan_Danilo_Molina_Martinez.pdfTesisapplication/pdf6612045https://repository.unab.edu.co/bitstream/20.500.12749/16806/1/2022_Tesis_Juan_Danilo_Molina_Martinez.pdfa61172c1e34f7547091b9f72d577c99fMD51open access2022_Licencia_Juan_Danilo_Molina_Martinez.pdf2022_Licencia_Juan_Danilo_Molina_Martinez.pdfLicenciaapplication/pdf298821https://repository.unab.edu.co/bitstream/20.500.12749/16806/2/2022_Licencia_Juan_Danilo_Molina_Martinez.pdff78ab13ee69dd99a86a496374e635f5fMD52metadata only accessLICENSElicense.txtlicense.txttext/plain; charset=utf-8829https://repository.unab.edu.co/bitstream/20.500.12749/16806/3/license.txt3755c0cfdb77e29f2b9125d7a45dd316MD53open accessTHUMBNAIL2022_Tesis_Juan_Danilo_Molina_Martinez.pdf.jpg2022_Tesis_Juan_Danilo_Molina_Martinez.pdf.jpgIM Thumbnailimage/jpeg4784https://repository.unab.edu.co/bitstream/20.500.12749/16806/4/2022_Tesis_Juan_Danilo_Molina_Martinez.pdf.jpgd25e4b410e946eef754c1ff5adfc1037MD54open access2022_Licencia_Juan_Danilo_Molina_Martinez.pdf.jpg2022_Licencia_Juan_Danilo_Molina_Martinez.pdf.jpgIM Thumbnailimage/jpeg10035https://repository.unab.edu.co/bitstream/20.500.12749/16806/5/2022_Licencia_Juan_Danilo_Molina_Martinez.pdf.jpg6c277dc46dc56a66a5183a0c094ce2d2MD55metadata only access20.500.12749/16806oai:repository.unab.edu.co:20.500.12749/168062022-06-28 22:00:29.488open accessRepositorio Institucional | Universidad Autónoma de Bucaramanga - UNABrepositorio@unab.edu.coRUwoTE9TKSBBVVRPUihFUyksIG1hbmlmaWVzdGEobWFuaWZlc3RhbW9zKSBxdWUgbGEgb2JyYSBvYmpldG8gZGUgbGEgcHJlc2VudGUgYXV0b3JpemFjacOzbiBlcyBvcmlnaW5hbCB5IGxhIHJlYWxpesOzIHNpbiB2aW9sYXIgbyB1c3VycGFyIGRlcmVjaG9zIGRlIGF1dG9yIGRlIHRlcmNlcm9zLCBwb3IgbG8gdGFudG8sIGxhIG9icmEgZXMgZGUgZXhjbHVzaXZhIGF1dG9yw61hIHkgdGllbmUgbGEgdGl0dWxhcmlkYWQgc29icmUgbGEgbWlzbWEuCgpFbiBjYXNvIGRlIHByZXNlbnRhcnNlIGN1YWxxdWllciByZWNsYW1hY2nDs24gbyBhY2Npw7NuIHBvciBwYXJ0ZSBkZSB1biB0ZXJjZXJvIGVuIGN1YW50byBhIGxvcyBkZXJlY2hvcyBkZSBhdXRvciBzb2JyZSBsYSBvYnJhIGVuIGN1ZXN0acOzbi4gRWwgQVVUT1IgYXN1bWlyw6EgdG9kYSBsYSByZXNwb25zYWJpbGlkYWQsIHkgc2FsZHLDoSBlbiBkZWZlbnNhIGRlIGxvcyBkZXJlY2hvcyBhcXXDrSBhdXRvcml6YWRvcywgcGFyYSB0b2RvcyBsb3MgZWZlY3RvcyBsYSBVTkFCIGFjdMO6YSBjb21vIHVuIHRlcmNlcm8gZGUgYnVlbmEgZmUuCgpFbCBBVVRPUiBhdXRvcml6YSBhIGxhIFVuaXZlcnNpZGFkIEF1dMOzbm9tYSBkZSBCdWNhcmFtYW5nYSBwYXJhIHF1ZSBlbiBsb3MgdMOpcm1pbm9zIGVzdGFibGVjaWRvcyBlbiBsYSBMZXkgMjMgZGUgMTk4MiwgTGV5IDQ0IGRlIDE5OTMsIERlY2lzacOzbiBBbmRpbmEgMzUxIGRlIDE5OTMgeSBkZW3DoXMgbm9ybWFzIGdlbmVyYWxlcyBzb2JyZSBsYSBtYXRlcmlhLCB1dGlsaWNlIGxhIG9icmEgb2JqZXRvIGRlIGxhIHByZXNlbnRlIGF1dG9yaXphY2nDs24uCg==