Assessing the effect of inattention-related error and anger in driving on road accidents among Iranian heavy vehicle drivers

Extensive studies have examined the effect of variables such as demographic characteristics, insomnia, and working conditions of drivers individually on inattention-related error as well as expression of anger in driving. Nevertheless, so far no study has tested the concurrent effect of these factors on crashes. This study has dealt with indirect investigation of the effect of variables including demographic characteristics, insomnia, and working conditions of drivers on inattention-related error and expression of anger in driving (as mediation model). Next, the effect of these two variables on the probability of incidence of road crashes has been assessed among truck drivers. For this purpose, 780 Iranian truck drivers were interviewed by validated questionnaires including insomnia severity index (ISI), attention related driving errors scale (ARDES), and driving anger expression (DAX). To confirm the validity of these questionnaires, confirmatory factor analysis (CFA) was used. Next, structural equation modeling (SEM) was employed for investigating the relationships between these latent variables and truck drivers' demographic characteristics, working conditions and their crash involvement. SEM results indicated that as the severity of insomnia among drivers increased, they committed more inattention-related errors, and also expressed more anger during driving. Generally, the results of this study indicated that with increase in the extent of experience and safety knowledge of drivers and improvement in their working conditions and their sleep status, it is possible to reduce inattention-related error and expression of anger during driving among heavy vehicle drivers.     

An investigation of tour generation models combining two waves of household travel surveys through pooled models

This paper presents a study that examines two waves of travel survey data through a pooled model structure. The pooled model structure provides a means to take advantage of multiple data sources which will lead to a better estimate and understanding of travel behavior. In particular, it accounts for the difference in data variance and therefore allows for the comparison of the true impacts of the model parameters on travelers’ tour-making behavior. Larger variance is found in the 1998 data than in the 2010 data. Comparison between model parameters reveals significant behavioral changes among several socio-economic and demographic groups. In terms of common variables, the magnitude of the coefficient values has generally decreased, which conforms to the overall decreasing trend in traveling. Overall, the model equality tests indicate that the models developed based on the two data sources do not have equal taste parameters, thus the transferability hypothesis is rejected. The results of this study are expected to have implications for the application of models based on cross-sectional data, especially over long time periods.