# A Large Bridge Traffic Operation Status Impact Assessment Model Based on AHP-Delphi-SVD Method
## 1 Introduction  
China is a country with complex terrain and numerous mountains and rivers. In order to improve transportation efficiency and meet the needs of economic construction, China has built a large number of bridges in highway and railway construction projects. Bridges are indispensable infrastructure for road transportation, alleviating the difficulties caused by complex terrain in China's transportation development and ensuring the sustainable development of various industries and economies [1]. Significant achievements have been made in technology related to roads and bridges in our country, gradually moving towards maturity and promoting the continuous development of our social economy [2]. With the continuation of the operation of bridge facilities and factors such as environmental and climate changes, the status of these facilities will inevitably undergo certain changes, thereby affecting the operation status of transportation. Therefore, a real-time understanding of bridge status and an effective scientific evaluation of the impact of bridges on traffic during operation are of great significance for traffic safety and the economy. In some developed countries, the construction of road traffic networks has been effectively completed, and a relatively mature and complete analysis and evaluation system has been established for various components of highways. They use existing infrastructure to analyze and evaluate the operation status of highways, improve the quality and service level of high-speed highway operations, which is the direction of future transportation development. However, research into an evaluation system for traffic operation status inChina started relatively late. If the assessment of bridge traffic impact is not strengthened, more bridge traffic accidents will occur, causing incalculable impacts on traffic operation. With the deepening of people's understanding of transportation issues and the increasing emphasis on the role of bridges in traffic operations, a large amount of related research has also been conducted. In one study [3], a long-term oriented full bridge traffic load monitoring system was proposed for the long-term monitoring of the distribution of full bridge traffic load on large-span bridges. The authors of [4] proposed a stochastic traffic flow simulation method that considered the correlation between vehicle arrival order and axle load. The results show that the correlation of these traffic flow parameters has a significant impact on the response of large-span suspension bridges. The study carried out in [5] uses the generalized extreme value theory to predict and evaluate the extreme value effects of bridges under heavy load random traffic loads in Wuhan during different regression periods. The study carried out in [6] establishes a fitting relationship model for coordination of traffic operations on large-span bridge sections under crosswind action by analyzing the relationship between traffic accidents on bridges and the distribution pattern of crosswinds. In order to effectively determine and identify abnormal driving vehicles, the study carried out [7] has proposed a highway traffic safety estimation model based on vehicle operation status. In order to solve the problem of traffic congestion in the context of smart cities, the study carried out in [8] establishes a traffic ontology called \"TrafCsOnto\" using OWL language and the protege tool. The study carried out in [9] proposed an innovative model that utilizes Convolutional Neural Networks (CNNs), Bidirectional Long Short Term Memory (BiLSTM), and an Attention Mechanism (AM) to predict highway traffic flow with high accuracy and feasibility. The study carried out in [10] constructs a bridge digital twin system connected by measured traffic flow loads to evaluate the health status of bridge structures during operation.