Effects of Data Resolution and Human Behavior on Large Scale Evacuation Simulations
Wei Lu

TL;DR
This paper investigates how data resolution and human behavior influence large-scale evacuation simulations, proposing new models and frameworks to improve accuracy and operational planning using high-resolution demographic data.
Contribution
It introduces a novel agent-based evacuation framework utilizing LandScan data and defines the MSNDSP problem for better evacuation assignment accuracy.
Findings
Higher resolution data improves evacuation performance estimates.
Different network configurations significantly affect evacuation efficiency.
Traveler compliance levels impact overall evacuation outcomes.
Abstract
Traffic Analysis Zones (TAZ) based macroscopic simulation studies are mostly applied in evacuation planning and operation areas. The large size in TAZ and aggregated information of macroscopic simulation underestimate the real evacuation performance. To take advantage of the high resolution demographic data LandScan USA (the zone size is much smaller than TAZ) and agent-based microscopic traffic simulation models, many new problems appeared and novel solutions are needed. A series of studies are conducted using LandScan USA Population Cells (LPC) data for evacuation assignments with different network configurations, travel demand models, and travelers compliance behavior. First, a new Multiple Source Nearest Destination Shortest Path (MSNDSP) problem is defined for generating Origin Destination matrix in evacuation assignments when using LandScan dataset. Second, a new agent-based…
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Taxonomy
TopicsEvacuation and Crowd Dynamics · Traffic control and management · Transportation Planning and Optimization
