Decision tree based bridge restoration models for extreme event performance assessment of regional road networks

Abstract

Bridge restoration models are essential for assessing the functionality of bridges after extreme events, emergency response planning, and evaluating resilience and indirect losses. Most of the existing restoration models lack explicit evaluation of anticipated bridge functionality in terms of traffic restrictions on bridges, which is necessary for realistic road network modeling. Therefore, this paper proposes a decision tree based approach to determine potential traffic restrictions and their durations using empirical and expert opinion survey data on restrictions imposed on bridges after extreme events. The proposed methodology is applied in this paper to obtain seismic restoration models for bridges. Herein, three separate decision trees are developed to determine various traffic restrictions, anticipated for different levels of damage to bridge components, including bridge closure, lane closure, and speed/load restriction. Corresponding to each of the three traffic restriction decision trees, another decision tree is developed which determines the duration of the traffic restriction. The probabilistic seismic performance of a regional highway network in Memphis, Tennessee, is studied using the proposed decision trees. Additionally, HAZUS bridge restoration functions are also applied and the differences in the time evolving bridge level functionality estimates and their impacts on network performance are highlighted.