Development of crash frequency models for safety promotion of urban collector streets

The merits for development and application of crash frequency prediction models for safety promotion on any road type, with a focus on urban collector streets, are presented in this article. The city of Yazd, a medium-sized city in the middle of Iran, was selected as a case study and the data required for modelling crash frequencies along five collector streets comprising 31 street sections were collected. Six models including Poisson and negative binomial models and their deviations along with a hybrid artificial neural networks (ANN) model were developed to predict crash frequency along each street section. The overfitting problem was addressed using appropriate sensitivity analysis methods which were also used to identify the input variables with significant impact on the model performance. The results indicated that the developed hybrid ANN model provided the best performance in terms of accuracy and the number of input variables. The application of hybrid ANN model to evaluate the safety impacts of four different strategies, each resembled by one of the input variables of this model, indicated that these models can successfully be used for this purpose.     

A dynamic hazard-based system of equations of vehicle ownership with endogenous long-term decision factors incorporating group decision making

The transportation system affects all aspects of our daily lives including relatively long-term decisions on work and home location choice and automobile ownership decisions. The interdependency existing among these three decisions jointly influences household mobility and overall travel patterns. Therefore, a dynamic modeling framework that can account for the effects of interdependencies between vehicle transaction behavior and residential and job location choices is highly desirable. These decisions are made in the household level while individuals’ decisions influence the overall outcome; therefore, it is also important to incorporate a group decision making process within such modeling frameworks.This study introduces a dynamic model for vehicle ownership, residential mobility, and employment relocation timing decisions. These decisions are modeled at the individual level and then sequentially aggregated to the household level if it is required. A hazard-based system of equations is formulated and applied in which work location and residential location changes are included as endogenous variables in the vehicle transaction model while other important factors such as land-use and built environment variables, household dynamics, and individuals’ socio-demographics are also considered.     

A study of the effect of OHSAS 18001 on the occupational injury rate in Iran

The occupational health and safety management system (OHSMS) has been a widely used approach for managing occupational health and safety more effectively worldwide. Despite the interest of organizations in implementing OHSMS in recent decades, few studies have examined the effectiveness of these interventions. This study presents an empirical investigation of the effect of occupational health and safety assessment series (OHSAS) 18001 as a worldwide-accepted OHSMS on the occupational injury rate (OIR) in Iran. This study was carried out in six companies: three OHSAS 18001-certified, and three non-certified, including 998 occupational injuries for 15,842 person-months. A before–after analysis showed a positive safety performance change in one out of the three certified companies. For all 66 study years in the six companies, a negative binomial regression did not indicate a lower occupational injury during the certified years and a repeated measures analysis of variance (ANOVA) did not confirm the effect of certification. The results of this study indicated that the implementation of OHSAS 18001 is not a guarantee of improved safety.