Abstract
A simulation model is developed to evaluate the performance of incident management operations. The Washington, D.C. beltway network is used as the study highway due to the availability of real-world incident data. Five incident types are considered. Their severity degrees are assumed to be related to the incident characteristics, and a relationship between the severity degree and the allocation of necessary emergency units is derived from previous data in related studies. Three different periods can be minimized during an incident removal process: detection and verification time, response time, and clearance time. This study focuses on the variation of detection and response times for various deployment strategies of emergency response teams. The Arena simulation package is used to model and examine the effects of various incident management strategies. An example scenario is given, and possible strategies are compared based on the statistical values obtained from the simulation output analysis.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 69-82 |
| Number of pages | 14 |
| Journal | Simulation |
| Volume | 79 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 2003 |
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Keywords
- Arena
- Incident management
- Siman
- Simulation
ASJC Scopus subject areas
- Computational Theory and Mathematics
- Computer Graphics and Computer-Aided Design
- Computer Science Applications
- Software
- Safety, Risk, Reliability and Quality
Cite this
Incident management simulation. / Ozbay, Kaan; Bartin, Bekir.
In: Simulation, Vol. 79, No. 2, 02.2003, p. 69-82.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Incident management simulation
AU - Ozbay, Kaan
AU - Bartin, Bekir
PY - 2003/2
Y1 - 2003/2
N2 - A simulation model is developed to evaluate the performance of incident management operations. The Washington, D.C. beltway network is used as the study highway due to the availability of real-world incident data. Five incident types are considered. Their severity degrees are assumed to be related to the incident characteristics, and a relationship between the severity degree and the allocation of necessary emergency units is derived from previous data in related studies. Three different periods can be minimized during an incident removal process: detection and verification time, response time, and clearance time. This study focuses on the variation of detection and response times for various deployment strategies of emergency response teams. The Arena simulation package is used to model and examine the effects of various incident management strategies. An example scenario is given, and possible strategies are compared based on the statistical values obtained from the simulation output analysis.
AB - A simulation model is developed to evaluate the performance of incident management operations. The Washington, D.C. beltway network is used as the study highway due to the availability of real-world incident data. Five incident types are considered. Their severity degrees are assumed to be related to the incident characteristics, and a relationship between the severity degree and the allocation of necessary emergency units is derived from previous data in related studies. Three different periods can be minimized during an incident removal process: detection and verification time, response time, and clearance time. This study focuses on the variation of detection and response times for various deployment strategies of emergency response teams. The Arena simulation package is used to model and examine the effects of various incident management strategies. An example scenario is given, and possible strategies are compared based on the statistical values obtained from the simulation output analysis.
KW - Arena
KW - Incident management
KW - Siman
KW - Simulation
UR - http://www.scopus.com/inward/record.url?scp=0041841252&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0041841252&partnerID=8YFLogxK
U2 - 10.1177/0037549703253494
DO - 10.1177/0037549703253494
M3 - Article
AN - SCOPUS:0041841252
VL - 79
SP - 69
EP - 82
JO - Simulation
JF - Simulation
SN - 0037-5497
IS - 2
ER -