Research On Road Network Failure Evalution Method Considering Extreme Climate Disasters

The intensification of climate change and frequent extreme climate disasters has caused enormous casualties and property damage in recent years. With the rapid development of urbanization and the increasing trend of aggregation degree of population and eco nomies, the road network, which is the lifeline engineering in cities, has become an important guarantee for national development, the quality of human life and social security. However, exposing in environment, the road network is vulnerable to extreme climate disasters, such as snowstorm and rainstorm, which can cause a large area of disruption or even overall network failure. Because of the indetermination (like fuzziness and imperfection) of acquiring information and the limitation of human cognitive capacity and evaluation models under extreme weather, decision makers always confront the problems of underestimation of road network failure evaluation and insufficient of emergency response, and thus can lead to huge economic loss and confusion of society. The existing research achievements indicate that quantitative risk assessments of road network failure evaluation play an important role in the control of total road network under extreme climate disasters. Therefore, considering the characteristics of exposure of the road network under extreme climate disasters, this paper explores models and methods of road network failure quantitative evaluation, which will improve the effectiveness of traffic management and aid decision making for emergency.Based on the summarization of the current research in and outside the country, this paper undertakes research on the basis of the relative studies on disaster system engineering theory, fault tree analysis, scenario theory, knowledge element theory and evidence theory. Start by analyzing extreme climate disaster, impact factors of road network, the concepts of scenario and knowledge element, this paper adopts the methodology of information science, uncertainties processing, and the combination of quantitative and qualitative analysis, and then establishes a framework of road network failure evaluation under extreme climate disasters. Studies involve the representation model of road network, knowledge expression model considering uncertainty, knowledge reasoning model based on belief rule and knowledge fusion method based on logical relationship and semantics decomposition.In order to evaluate road network failure, this paper first studies the abstracted representation of road network. After the recognition of macroscopic affection factors of road network failure, this research adopts the fault tree model to describe logical relation between these factors for the representation of macroscopic road network flow. And then, this paper analyzes the impacts of extreme climate disasters on road network. Research shows that these impacts are mainly reflect the severe jitter of related factors'attribute state in road network under extreme climate disasters. And sometimes the jitters is beyond the range that road network can bear, which causes uncertainty (including information ambiguity and knowledge imperfection) during road network failure evaluation and references unavailable of precise mathematical model and historical experience.In view of the limitation of existing evaluation methods, a new knowledge acquisition evaluation method is proposed based on improved belief rules. This research is based on the framework of evidence theory, and combines the belief structure and scenario to represent the uncertainty of evaluated information, and then uses the belief structure and knowledge units to modeling. On this basis, an improved OWA operator method is proposed to computing the weights of semantic decomposition in road network failure's fault tree. And then, this paper takes the weight parameters into the improved evidence algorithm to calculate the road network failure iteratively. The case study shows that, this method can deal with the uncertainty problem during the evaluation of road network failure effectively. At the meantime, it can take both compensation effect and inhibiting effect between factors which are considered in road network evaluation into consideration. It is relatively good in accordance with the mode of human reasoning.