Cyber London Pathfinding: Bidirectional Dijkstra vs A* (A-Star) Light Up The Thames | 4K UHD

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A-Star Algorithm: https://researchdatapod.com/a-star-al...
Dijkstra's Algorithm: https://researchdatapod.com/dijkstras...

Exploring pathfinding algorithms navigating from Park Royal to Catford - a classic North to South London journey that every algorithm must solve: how to cross the Thames efficiently.

Distance vs Time Optimisation:
Distance optimisation finds the shortest path in miles/kilometres, often plunging straight through Central London. Time optimisation finds the fastest route using actual road speeds from OpenStreetMap. A route through Oxford Street might be 9 miles (15km) at 9 mph (15 km/h) taking 60 minutes, while the A406 North Circular to A205 South Circular could be 14 miles (22km) at 25 mph (40 km/h) taking just 33 minutes - making the longer route nearly twice as fast.

The Thames Challenge:
Watch how algorithms handle London's defining feature - the River Thames creates a natural bottleneck with limited crossing points. Distance-optimised paths beeline for central bridges like Westminster or Waterloo, while time-optimised routes often favour the less congested crossings or even the orbital motorways.

The A-Star Heuristic:
For distance, A-Star uses straight-line distance from Park Royal to Catford. For time, it estimates: time = distance ÷ 31 mph (50 km/h). This guides A-Star toward promising routes while Dijkstra exhaustively explores all possible roads.

Key metrics shown:

Algorithm type and optimisation
Path length (miles/km)
Total travel time
Nodes explored
Network coverage %

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