The current analysis analyzed the odds of casualties by road accidents. Hence, data were classified into tertiles for better research, and accident types were classified into five following the authority methodology: rollovers, crash, roadway departure, special accident, and car capsizing. Multi-logistic regression was employed for the data analysis. This research found that rollover was the most deadly accident, and the crash was the most probable to cause injuries.

Road accidents as a global challenge, imposing irreparable financial and human life losses in almost all countries, especially in developing countries, annually. According to world health organization (WHO), if this trend continues, road accidents will become the 7th cause of human death by 2030. Thus, road safety policy makers have been trying to use safety promotion and preventative actions. In this paper, the road safety performance of Iranian provinces is studied. To evaluate road safety efficiency scores, data envelopment analysis based on road safety (DEA-RS) method in two deterministic and non-deterministic situations is used. To consider the uncertainty in input and output data, this paper develops credibility DEA-RS (CreDEA-RS) model. In fact, the constraints of DEA-RS model are considered as credibility constraints and a counterpart credibility DEA-RS (CreDEA-RS) model is proposed for evaluating road safety of provinces of Iran. According to the results, provinces located in mountainous and forest areas such as Gilan had a much weaker performance than provinces in desert areas such as Yazd.

Cost benefit analysis (CBA) is a useful tool for investment decision-making from economic point of view. When the decision involves conflicting goals, the multi-attribute analysis approach is more capable; because there are some social and environmental criteria that cannot be valued or monetized by cost benefit analysis. The complex nature of decision-making in road safety normally makes it difficult to reach a single alternative solution that can satisfy all decision-making problems. Generally, the application of multi-attribute analysis in road sector is promising; however, the applications are in preliminary stage. Some multi-attribute analysis techniques, such as analytic hierarchy process (AHP) have been widely used in practice. This paper presents an integrated framework with CBA and AHP methods to select proper alternative in road safety projects. The proposed model of this paper is implemented for a case study of improving a road to reduce the accidents in Iran. The framework is used as an aid to cost benefit tool in road safety projects.