Authors: Armita Kar*, , Thomas J. Cova, Professor, Department of Geography, University of Utah
Topics: Hazards, Risks, and Disasters, Transportation Geography
Keywords: Safe Route Modelling, Urban Flooding, Dijkstra’s Algorithm, Pareto Optimality, Time-Safety Trade-off
Session Type: Paper
Start / End Time: 3:05 PM / 4:20 PM
Room: Virtual Track 10
Presentation Link: Open in New Window
Ensuring the safety of urban residents traveling through flood events can be challenging. The goal of this research is to develop a method for identifying relatively safe travel routes during storms and floods. The method considers four environmental factors: elevation, flood zones, rainfall, and flood level as indicators of safety. The safest and fastest route use a weighted composite score of safety factors and travel time as impedance values, respectively. The balanced routes integrate both travel time and safety. The method incorporates turn penalties to ensure the resulting routes are simple and easy to communicate. The City of Friendswood, Texas in the Houston metropolitan area is used as a case study, as it was inundated during 2017 Hurricane Harvey. The study found variation in routes with different impedance factors and a Pareto efficient relationship among the safest, balanced, and fastest route for any origin-destination pair in the study area. Application of this method in route planning can provide information to drivers about the relative safety of urban travel routes to minimize losses, injuries, and rescue costs.