Community-Safe Drone Routing with Risk-Aware Graph Optimization

Abstract

This article develops a weighted graph planner that jointly minimizes travel time, acoustic exposure near schools, and emergency landing scarcity. Using open municipal GIS layers and measured propeller signatures, the model reduced aggregate neighborhood disturbance by 24% relative to shortest-path baselines in a Boston test district. The student researcher also reports a transparent policy dashboard that helps civic reviewers inspect route trade-offs before approval.

Figure 3 overlays optimized trajectories on a district risk map that combines noise sensitivity, pedestrian density, and emergency landing coverage.