Interactive Pathfinding Visualization for Smart Urban Navigation
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Authors
Yassine Kraiem
Issue Date
2026
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Language
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Abstract
We introduce IMPV, an interactive map pathfinding visualizer which integrates classical AI pathfinding algorithms within a customizable grid framework. Most elementary pathfinding visualizers highlight algorithmic mechanics but provide little connection to the real-world urban mobility challenges addressed by professional systems. This platform supports real-time interaction, obstacle placement, and parameter adjustment, enabling direct comparisons of efficiency and exploration behavior. By framing these algorithms in the context of smart city applications, the tool demonstrates how classical search methods can inform routing strategies, emergency response, and urban planning. Implemented in React and D3.js, the system is open source, extensible to real map data and live traffic feeds, and serves as both a pedagogical resource and a research springboard for AI-driven urban mobility.