Entendiendo la percepción del riesgo de accidentes en conductores: Un enfoque con variables latentes

Autores/as

  • Thomas Edison Guerrero Barbosa Universidad Francisco de Paula Santander Ocaña
  • Sebastian Raveau Pontificia Universidad Católica de Chile
  • Juan de Dios Ortúzar Pontificia Universidad Católica de Chile

Palabras clave:

variables latentes, percepción del riesgo, modelos híbridos de elección discreta

Resumen

Las entidades gubernamentales y no gubernamentales necesitan herramientas de decisión que les permitan atacar la pandemia en que se han convertido los accidentes de tránsito, que año a año cobran millones de vidas en todo el planeta. Como la evidencia indica que el factor humano es uno de los grandes causantes de muerte por accidentes viales, esta investigación se enfocó en identificar variables que incidieran sobre la percepción del riesgo de accidentes mientras se conduce, incorporando percepciones subjetivas de las personas en la forma de variables latentes. El enfoque de modelación consideró la estimación de diferentes formas funcionales de modelos Logit a partir de datos de preferencias declaradas. Los escenarios hipotéticos de conducción presentados se caracterizaron mediante cuatro atributos: (i) velocidad de conducción, (ii) conducir en contravía, (iii) adelantar a un vehículo en curva, y (iv) conducir bajo efectos del alcohol o drogas. Además, se estimó las variables latentes Concentración y Conducción Segura que se relacionan fuertemente con características socioeconómicas de los individuos (género, edad, ocupación, y experiencia previa de accidentes). Los resultados indican que las personas con actitudes de conducción segura tienden a no conducir bajo la influencia del alcohol/drogas. Por otro lado, los conductores que no tienden a distraerse con otras actividades (ver el celular, radio, velocímetro o similares) mientras conducen, también procuran no conducir en contravía y no realizar adelantamientos en curva.

Citas

Ashok, K., Dillon, W. y Yuan, S. (2002). Extending discrete choice models to incorporate attitudinal and other latent variables. Journal of Marketing Research, 39, 31–46.

Atchley, P., Shi, J. y Yamamoto, T. (2014). Cultural foundations of safety culture: a comparison of traffic safety culture in China, Japan and the United States. Transportation Research Part F: Traffic Psychology and Behaviour, 26, 317–325.

Bahamonde-Birke, F.J. y Ortúzar, J. de D. (2014). Is sequential estimation a suitable second best for estimation of hybrid choice models? Transportation Research Record, 2429, 51-58.

Bamberg, S., Ajzen, I. y Schmidt, P. (2003). Choice of travel mode in the theory of planned behavior: the roles of past behavior, habit, and reasoned action. Basic Applied Social Psychology, 25, 175–187.

Ben-Akiva, M.E., Walker, J.L., Bernardino, A.T., Gopinath, D.A., Morikawa, T. y Polydoropoulou, A. (2002). Integration of choice and latent variable models. En H.S. Mahmassani (ed.), In Perpetual Motion: Travel Behaviour Research Opportunities and Challenges. Amsterdam: Pergamon.

Bierlaire, M. (2003). BIOGEME: a free package for the estimation of discrete choice models. Proceedings of the Third Swiss Transport Research Conference. Ascona, Suiza.

Bolduc, D. y Alvarez-Daziano, R. (2009). On estimation of hybrid choice models. En S. Hess y A. Daly (eds.), Choice Modelling: The State-of-the-Art and the State-of-Practice. Bingley, Emerald Group Publishing Limited.

Bone, S.A. y Mowen, J.C. (2006). Identifying the traits of aggressive and distracted drivers: a hierarchical trait model approach. Journal of Consumer Behaviour, 5, 454–464.

Buitrago, J.R., Norza, E. y Ruiz, H. (2015). Conductores en estado de embriaguez en Colombia y la implementación de la Ley 1696 de 2013. Revista Criminalidad, 57, 27-40.

Caliendo, C., Guida, M. y Parisi, A. (2007). A crash-prediction model for multilane roads. Accident Analysis and Prevention, 39, 657–670.

Chia-Jung, C. y Pei-Chun, C. (2014). Preferences and willingness to pay for green hotel attributes in tourist choice behaviour: the case of Taiwan. Journal of Travel and Tourism Marketing, 31, 937-957.

Choudhary, P. y Velaga, N.R. (2017). Modelling driver distraction effects due to mobile phone use on reaction time. Transportation Research Part C: Emerging Technologies, 77, 351-365.

Christ, R., Delhomme, P., Kaba, A., Makinen, T.S., Sagberg, F., Schulze, H. y Siegrist, S. (1999). GADGET. Guarding Automobile Drivers through Guidance Education and Technology. Final report. Vienna: Kuratorium für Verkehrssicherheit (KfV).

Danaf, M., Abou-Zeid, M. y Kaysi, I. (2015). Modeling anger and aggressive driving behavior in a dynamic choice–latent variable model. Accident Analysis and Prevention, 75, 105-118.

Domencich, T. y McFadden, D. (1975). Urban Travel Demand: A Behavioral Analysis. Amsterdam, North Holland.

Dirección Nacional de Planeación. (2010). Formulación del Plan Maestro de Movilidad del Municipio de Ocaña. Bogotá DC.

Francis, J., Eccles, M., Johnston, M., Walker, A., Grimshaw, J., Foy, R. y Bonetti, D. (2004). Constructing questionnaire based on the theory of planned behavior. A manual for health services researchers. Centre for Health Services Research, University of Newcaste upon Tyne.

Hassen, A., Godesso, A., Abebe, L. y Girma, E. (2011). Risky driving behaviors for road traffic accident among drivers in Mekele city, Northern Ethiopia. BioMed Central Research Notes, 4, 535.

Hess, S. y Beharry-Borg, N. (2012). Accounting for latent attitudes in willingness-to-pay studies: the case of coastal water quality improvements in Tobago. Environmental and Resource Economics, 52, 109-131.

Homel, R. (1988). Policing and Punishing the Drinking Driver. A Study of General and Specific Deterrence. Nueva York: Springer-Verlag.

Hongsranagon, P., Khompratya, T. y Hongpukdee, S. (2011). Traffic risk behavior and perceptions of Thai motorcyclists: a case study. IATSS Research, 35, 30–33.

Humlum, M.K., Kleinjans, K.J. y Nielsen, H.S. (2012). An economic analysis of identity and career choice. Economic Inquiry, 50, 39-61.

Hurtubia, R. y Bierlaire, M. (2014). Estimation of bid functions for location choice and price modelling with a latent variable approach. Networks and Spatial Economics, 14, 47-65.

Instituto Nacional de Medicina Legal y Ciencias Forenses. (2014). Forensis 2014 Datos para la Vida. Bogotá D.C.

Iversen, H. (2004). Risk-taking attitudes and risky driving behaviour. Transportation Research Part F: Traffic Psychology and Behaviour, 7, 135-150.

Joreskog, K. y Goldberger, A. (1975). Estimation of a model with multiple indicators and multiple causes of a single latent variable. Journal of American Statistical Association, 70, 631-639.

Kocur, G., Adler, T., Hyman, W. y Aunet, B. (1982). Guide to forecasting travel demand with direct utility assessment. Report Nº UMTANH-11-0001-82, Urban Mass Administration, US Department of Transportation. Washington, D.C.

Krueger, R. y Casey, M.A. (2009). Focus Groups: A Practical Guide for Applied Research (Cuarta ed.). Beverly Hills: SAGE Publications, Inc.

Louviere, J.J., Hensher, D.A. y Swait, F.D. (2000). Stated Choice Methods: Analysis and Applications in Marketing, Transportation and Environmental Valuation. Cambridge: Cambridge University Press.

Lam, S.K., Ahearne, M., Hu, Y. y Schillewaert, N. (2010). Resistance to brand switching when a radically new brand is introduced: a social identity theory perspective. Journal of Marketing, 74, 128-146.

Luna-Blanco, R. (2013). Percepción del riesgo y de seguridad ante la conducción de vehículos. Carreteras, 189, 48-56.

Luo, L., Kannan, P.K. y Ratchford, B.T. (2008). Incorporating subjective characteristics in product design and evaluations. Journal of Marketing Research, 45, 182-194.

Machado, J.L., de Oña, J., de Oña, R., Eboli, L. y Mazzulla, G. (2016). Socio-economic and driving experience factors affecting drivers’ perceptions of traffic crash risk. Transportation Research Part F: Traffic Psychology and Behaviour, 37, 41–51.

Mairean, C., Havârneanu, G.M., Popușoi, S.A. y Havârneanu, C.E. (2017). Traffic locus of control scale – Romanian version: psychometric properties and relations to the driver’s personality, risk perception, and driving behavior. Transportation Research Part F: Traffic Psychology and Behaviour, 45, 131–146.

Márquez, L.G., Cantillo, V.M. y Arellana, J. (2015). Mobile phone use while driving: a hybrid modeling approach. Accident Analysis and Prevention, 78, 73-80.

Organización Mundial de la Salud. (2009). Informe Sobre la Situación Mundial de la Seguridad Vial: Es Hora de Pasar a la Acción. OMS, Ginebra.

Orozco, M., Arévalo, A., Gutiérrez, M. y Guerrero, T. (2017). Bicycle choice modelling: a study of university trips in a small Colombian city. Journal of Transport and Health (en revision).

Ortúzar, J. de D. y Willumsen, L.G. (2011). Modelling Transport (Cuarta ed.). Chichester: John Wiley and Sons.

Pachón, V. y Zabaleta, J. (2015). Modelación de la Percepción del Riesgo de Accidentes en Conductores: Un Enfoque de Preferencias Declaradas. Tesis para optar al título de Ingeniero Civil, Universidad Francisco de Paula Santander Ocaña, Ocaña.

Perdomo, M., Rezaei, A., Patterson, Z., Saunier, N. y Miranda-Moreno, L.F. (2014). Pedestrian preferences with respect to roundabouts-a video-based stated preference survey. Accident Analysis and Prevention, 70, 84-91.

Petridou, E. y Moustaki, M. (2000). Human factors in the causation of road traffic crashes. European Journal of Epidemiology, 16, 819–826.

Ram, T. y Chand, K. (2016). Effect of drivers’ risk perception and perception of driving tasks on road safety attitude. Transportation Research Part F: Traffic Psychology and Behaviour, 42, 162–176.

Raveau, S., Alvarez-Daziano, R., Yañez, M.F., Bolduc, D. y Ortúzar, J. de D. (2010). Sequential and simultaneous estimation of hybrid discrete choice models: some new findings. Transportation Research Record, 2156, 131–139.

Raveau, S., Ortúzar, J. de D. y Yañez, M.F. (2009). Simultaneous estimation of discrete choice models with latent variables. XIII Euro Working Group on Transportation. Padua, Italy.

Rizzi, L. y Ortúzar, J. de D. (2006). Road safety valuation under a stated choice framework. Journal of Transport Economics and Policy, 40, 69-94.

Rupp, M.A., Gentzler, M.D., y Smither, J.A. (2016). Driving under the influence of distraction: examining dissociations between risk perception and engagement in distracted driving. Accident Analysis and Prevention, 97, 220-230.

Ulleberg, P. y Rundmo, T. (2003). Personality, attitudes and risk perception as predictors of risky driving behaviour among young drivers. Safety Science, 41, 427-443.

Vanlaar, W. y Yannis, G. (2006). Perception of road accident causes. Accident Analysis and Prevention, 38, 155-161.

Vieira Gomes, S. (2013). The influence of the infrastructure characteristics in urban road accidents occurrence. Accident Analysis and Prevention, 60, 289–297.

Wang, B., Hensher, D.A. y Ton, T. (2002). Safety in the road environment: a driver behavioural response perspective. Transportation, 29, 253–270.

Williams, H.C.W.L. (1977). On the formation of travel demand models and economic evaluation measures of user benefit. Enviroment and Planning, 9A, 285-344.

Yáñez, M.F., Raveau, S. y Ortúzar, J. de D. (2010). Inclusion of latent variables in mixed logit models: modelling and forecasting. Transportation Research Part A: Policy and Practice, 44, 744–753.

Yao, L. y Wu, C. (2011). Traffic safety of e-bike riders in China: safety attitudes, risk perception and aberrant riding behaviors. Transportation Research Record, 2314, 49–56.

Zhao, X.G., He, X.D., Wu, J.S., Zhao, G.F., Ma, Y.F. y Zhang, M. (2009). Risk factors for urban road traffic injuries in Hangzhou, China. Arch Orthopnea Trauma Surgery, 129, 507–513.

Zwerina, K., Huber, J. y Kuhfeld, W. (2005). A General Method for Constructing Efficient Choice Designs. Ludwigshafen, SAS Institute.

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Publicado

01-02-2019

Número

Sección

Artículo Sistemas de Transporte