The Risk Models And Their Application For Hazmat Transportation

Activities involving transportation of hazardous materials (hazmat) are becoming more and more frequent due to the increasing use of such materials in the advancement of economy. The primary difference between the transportation of hazmat and that of normal goods lies in the risk associated during the process, which cannot be ignored in any decision making problem related to hazmat. Therefore, a reasonable model to measure the transportation risk is the key to route selection and other related issues for hazmat transportation. Researchers have designed a number of models to measure transportation risk. These models have played important roles in solving some problems of hazmat transportation, but there are some drawbacks, namely, (1) the majority of the models employ approximate calculation in various degrees, introducing calculation errors in the end result; no detailed analysis have been performed to determine if the result would be invalidated by such errors. (2) Newer risk models can be much more accurate than ever before, thanks to the continuous improvement in the dataset related to hazmat transportation. Thus there is an urgent need for more accurate risk models. (3) In general, the preferences of decision makers have huge impact on the outcome of design making, and design making for hazmat transportation can be no exception. Hence it is an interesting research area to design risk models that reflect the such preferences. (4) from the perspective of the application of risk models, most models focus on route selection, while there are much more decision-making issues associated with hazmat transportation. Therefore it is a new research topic to incorporate those related concerns.In this paper we try to address the issues mentioned above. Our work includes:·We systematically reviewed related literature and research results and analyzed several typical risk measurement models and their satisfiability for axioms. We investigated the impact of three factors (approximate calculation, estimation of accident consequences, and discrete processing) on the calculated result in the application of models. We discovered and verified that the precise form of the IP model can satisfy the relevant axioms.·We introduced classification of accidents to improve eight risk measurement models and verified the reliability of the refined models using relevant axioms. We discovered that certain models, namely TR model, can be improved in this way to effectively overcome the measurement error and reduce transportation risk on the path without breaking axioms, while others are less suitable for such refinement.·We took time dependency of decision makers and its impact on results of risk assessment into account and established the risk indifference curve. With the help of the curve we transformed risk value over several periods of time into a single period to calculate the total risk for route selection. We also gave the relevant axioms that the risk indifference curve should satisfy, the fundamental natures of the bundle of risk indifference curves, and the basic steps of risk measurement.·We established three functions to depict the relationship (1) between the number of travels and the possibility of accidents, and (2) between the number of travels and transportation risk, and (3) between the number of travels and transportation to study the behaviors of decision makers under three different criterions, namely, minimizing the possibility of accidents along the route, minimizing transportation risk, and minimizing transportation risk and cost. We performed an empirical analysis on the application of models using the data from www.ersi.com. The result confirmed the conclusions of this paper.