01557098

Component

Bushfire is an important public health and safety issue in Australia and in the world. Late evacuation has been identified as a key issue in emergency evacuation management, which has the potential to increase the risk of injury or death. For example, in the Australian Black Saturday 2009 bushfire, a large number of evacuees could not be evacuated on within the restricted time window of 10 minutes, which has resulted in the death of 119 people – 68 per cent of the total number of fatalities. Late evacuation is the most crucial stage in the emergency response because of the hard constraint of limited time window, uncertainty in the trajectory of bushfire and the resulted road disruptions, and evacuation of relatively vulnerable segments of the community. The paper developed a multi-objective optimization model to improve the decision-making process to evaluate late evacuees from assembly points to shelters. Scenarios were generated to incorporate different constraints such as the time-window, road disruptions, and capacity constraints. The model is solved by Ɛ-constraint approach. Several hypothetical bushfire scenarios in two different case studies are provided to evaluate the model. Objective functions were simultaneously optimized to enable maximizing the total number of people evacuated and optimizing the assignment of available resources as the number of rescue vehicles and shelters. The model also calculates the number of people who could not be evacuated given the time and resources available to do so. The authors argue that this model provides a scenario-based evidence for effective decision-making, which helps minimizing resource utilization and maximizing coverage of late evacuees.

This paper was sponsored by TRB committee ANB80 Emergency Evacuation.

01550057

15-3839

English

16p

2015

Transportation Research Board 94th Annual Meeting

Digital/other

Figures; References; Tables

Case studies; Decision making; Emergency management; Emergency response time; Evacuation; Fires; Optimization; Resource allocation

Australia

Planning and Forecasting; Security and Emergencies; Transportation (General); I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2015 Paper #15-3839

PRP, TRIS, TRB, ATRI

Dec 30 2014 1:15PM