TY  - JOUR
PY  - 2023//
TI  - Traffic resilience modeling for post-earthquake emergency medical response and planning considering disrupted infrastructure and dislocated residents
JO  - International journal of disaster risk reduction
A1  - Wu, Yangyang
A1  - Chen, Suren
SP  - e103754
EP  - e103754
VL  - 93
IS  - 
N2  - Quick access to hospitals is essential for severely injured people during post-earthquake emergency medical response. In addition to emergency medical vehicles, most injured residents are often transported to hospitals by private vehicles. Unlike emergency vehicles, private vehicles carrying injured people don't have the driving privilege and therefore become part of regular traffic. Meanwhile, there is usually considerable traffic from dislocated people subjected to various levels of road disruptions following earthquakes. A realistic and efficient assessment of the resilience performance of the disrupted transportation network during the emergency medical response is crucial to saving as many lives as possible through optimal emergency response planning. This study proposes a new methodology to quantify the resilience of disrupted transportation networks during the emergency response stage considering private-vehicle-based injury transport and evacuation traffic. The proposed methodology simulates the traffic during the emergency medical service using the dynamic traffic assignment method by considering various road disruptions. A resilience index is proposed based on the traffic efficiency of the hospitalization trips and uncertainties in earthquakes and infrastructure vulnerability. Finally, the reasonable number of EMS vehicles is investigated from the optimal emergency medical transportation perspective.<p />  <p>Language: en</p>
LA  - en
SN  - 2212-4209
UR  - http://dx.doi.org/10.1016/j.ijdrr.2023.103754
ID  - ref1
ER  -