Interactive Simulation & Algorithm Demo
Dynamic real-world route planning and graph search visualizer on authentic Google Maps roads — type any two addresses or click anywhere on Earth to watch Dijkstra, A*, Bidirectional A*, Greedy, and BFS explore physical highways and streets in real time.
Enter any two addresses on Earth or click anywhere on the map. Watch search frontiers navigate physical highways, bridges, and city streets step by step with real-time algorithm comparisons.
| Rank | Algorithm | Nodes Explored | Frontier Size | Distance | ETA | Status |
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The San Francisco Bay Area provides a classic benchmark for graph search: water bodies act as natural topological barriers, forcing paths through narrow bridge chokepoints (the Bay Bridge, Golden Gate Bridge, San Mateo Bridge, and Dumbarton Bridge). Explore how each algorithm navigates these spatial constraints:
Guarantees the mathematically optimal shortest path by exploring outward in uniform cost contours without any directional heuristic guidance. Explores equally in all directions.
O((V + E) log V)O(V)Combines actual path cost g(n) with an admissible straight-line distance heuristic h(n). Pulls the exploration cone directly toward the destination, drastically reducing explored nodes.
O(E)O(V)Executes two concurrent A* searches: one forward from the start, and one backward from the destination. When their frontiers collide, the search space volume is reduced by up to an order of magnitude.
O(b^(d/2))O(b^(d/2))Evaluates only h(n), aggressively charging directly toward the target. In open terrain it is lightning fast, but around geographic obstacles (like the SF Bay) it can get trapped along shorelines before finding bridge ramps.
O(V + E)O(V)Traverses the graph layer by layer using a FIFO queue. Minimizes the total number of road segment hops, but ignores speed limits and physical mileage, illustrating why weighted search is essential for navigation.
O(V + E)O(V)Explores as deep as possible down each arterial branch before backtracking. Included for educational contrast to demonstrate why unguided depth search produces wild, circuitous paths across multiple counties.
O(V + E)O(V)