TY - GEN
T1 - Modeling of Incident-Induced Capacity Loss for Hurricane Evacuation Simulation
AU - Zhu, Yuan
AU - Ozbay, Kaan
AU - Xie, Kun
AU - Yang, Hong
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - Modeling and simulation of hurricane evacuation is an important task in emergency planning and management. One typically ignored factor that affects the development of a reliable evacuation model is the uncertainty caused by the incident-induced capacity loss. Lately, the impact of incidents on evacuation has drawn increasingly attention among researchers and practitioners, but few of them thoroughly investigated it using the real data in the modeling and simulation context. This study aims to investigate the impact of various types of incidents on modeling and simulation of hurricane evacuation. Particularly, the incidents that occurred under actual hurricane conditions are examined and their impact on the capacity loss is modeled. The developed incident frequency and duration models are incorporated into the network assignment model to study traffic conditions under hurricane Sandy in New York. Results show that the consideration of incident-induced capacity loss can greatly change the outcome of the evacuation model. Our findings suggest the need to include a well calibrated and validated traffic incident generation module for modeling and simulating hurricane evacuation.
AB - Modeling and simulation of hurricane evacuation is an important task in emergency planning and management. One typically ignored factor that affects the development of a reliable evacuation model is the uncertainty caused by the incident-induced capacity loss. Lately, the impact of incidents on evacuation has drawn increasingly attention among researchers and practitioners, but few of them thoroughly investigated it using the real data in the modeling and simulation context. This study aims to investigate the impact of various types of incidents on modeling and simulation of hurricane evacuation. Particularly, the incidents that occurred under actual hurricane conditions are examined and their impact on the capacity loss is modeled. The developed incident frequency and duration models are incorporated into the network assignment model to study traffic conditions under hurricane Sandy in New York. Results show that the consideration of incident-induced capacity loss can greatly change the outcome of the evacuation model. Our findings suggest the need to include a well calibrated and validated traffic incident generation module for modeling and simulating hurricane evacuation.
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U2 - 10.1109/ITSC.2019.8917250
DO - 10.1109/ITSC.2019.8917250
M3 - Conference contribution
T3 - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
SP - 613
EP - 618
BT - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
Y2 - 27 October 2019 through 30 October 2019
ER -