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ABSTRACTGovernments require decision tools to deal with road traffic accidents, a pandemic resulting in millions of deaths around the world. Evidence shows that human factors are one of the major causes of road accidents, and there is much interest in identifying variables that may have an impact on drivers’ perception of risk. To this aim, we design a stated choice experiment with eight hypothetical driving scenarios considering attributes that have been strongly associated with increased accident risks: (i) driving speed, (ii) driving the wrong way in a one-way street, (iii) overtaking on a bend, and (iv) driving under the influence of alcohol or drugs. Data from a sample of survey respondents are used to estimate a hybrid discrete choice model incorporating two latent variables, Driver Concentration and Safe Driving. Our results may contribute to the design of public policies geared to prevent accidents by encouraging safer driving behaviour. 相似文献
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Guerrero Thomas E. Guevara C. Angelo Cherchi Elisabetta Ortúzar Juan de Dios 《Transportation》2021,48(4):2081-2102
Transportation - Endogeneity is a potential anomaly in econometric models, which may cause inconsistent parameter estimates. Transport models are prone to this problem and applications that... 相似文献
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