Summary
When sudden urban floods happen, people need to know which roads will still be safe to drive on when they actually get there, not just at the start of their trip. The authors created a routing tool that uses updated forecasts of flood depths every 15 minutes and plans around roads expected to flood for the type of vehicle traveling. They tested this in Hanoi and found that ignoring changing flood conditions sends nearly 8% of trips into flooded roads, while their method avoids most of these hazardous routes with only a small increase in travel time. This tool lets authorities set safety rules based on vehicle type and forecasted water levels to help plan safer trips.
What this means in practice
- •For navigation platform operators: Incorporate time-varying flood forecasts into route planning to reduce drivers being sent into flooded roads during urban storms.
- •For municipal traffic management teams: Use vehicle-specific flood depth limits and forecast updates to dynamically close roads and manage traffic during flash floods.
Tested on one dataset.
Authors
Mai Anh Tran, Vy Nguyen, Vova Nguyen, Minh Hoa Bui
Abstract
During urban flash floods, commuters and guiding agencies require awareness towards which roads remain passable when a vehicle actually arrives, rather than relying solely on which links appear open at initial departure. Most existing flood-routing tools apply a single static snapshot to each route; meaning that corridors that appear clear initially can become flooded before arrival. This paper presents a routing engine that ingests a two-hour water forecast, renewed every 15 minutes, and plans each journey around roads that the forecast closes for that specific vehicle class. Under this formulation, any road that closes mid-trip remains closed for that query, which keeps route calculation fast enough for live requests while operating inside a production GraphHopper routing server. Testing on a recorded storm in western Hanoi revealed that a router checking only departure conditions sent 7.8% of routes into roads flooded upon arrival. In comparable trips, the proposed rule produced longer routes in 3.95% of cases, requiring a median of only 9.2 s of additional travel time. Agencies and navigation platforms can employ this engine to schedule trips by vehicle type, allowing operators to establish depth limits and lookahead margins as policy parameters. However, several limitations must be noted, as the water depths originate from a hydrodynamic simulation that was not verified against measured water levels, the rainfall was replayed rather than forecast live, and depth cutoffs reflect policy settings rather than measured physical thresholds. Keywords: flood routing, time-dependent shortest path, sticky edge closure, forecast water depth, vehicle depth limit, Hanoi