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Efficient Map Path Finding with Realistic Conditions

Efficient Map Path Finding with Realistic Conditions. Third Quarter Version Olex Ponomarenko. Goals for the Project. Create a fairly abstract map path-finding program Add more complex heuristics to account for things such as traffic lights, stop signs, and different amounts of roads

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Efficient Map Path Finding with Realistic Conditions

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  1. Efficient Map Path Finding with Realistic Conditions Third Quarter Version Olex Ponomarenko

  2. Goals for the Project • Create a fairly abstract map path-finding program • Add more complex heuristics to account for things such as traffic lights, stop signs, and different amounts of roads • Create a random graph generator • Create a visual representation, perhaps using Java, to display the map

  3. Goals (but in one sentence) • Basically the idea is to create a method of searching for a path on an abstract map that would lead to simpler, more realistic results, and avoid passing through generally slow turns and intersections. (stop sign left turns onto a big street like Fairfax County Parkway)

  4. Specifics • The language used will be Python for the speed and ease of coding that it provides • Java will be used to create the visual, as Java graphics are easy to work with. • The maps and searches will be realistic, and the program overall will be efficient, allowing large-scale data sets

  5. First Quarter • A very basic version of the program was developed • Built upon the path finding program in the AI course • Text-only, basic coordinates, only one type of roads, and most importantly, no intersections.

  6. First Quarter To give you an idea of what the program did (since input / output are all just text) Only one type of road (no difference whether it’s a small driveway or I-95) represented One type of location Doesn’t account for delay at intersections

  7. Second Quarter • The RGG at this point was somewhat random – the following being a good example of the type of map it produces: Different road sizes No overlapping locations (none within 10 units of space between each other), all locations connected. BUT – Still no intersections Mostly random roads (note the only path to get to the purple one and the random 5-foot long interstate highway)

  8. Current Generator • This is what I’ve accomplished so far: Realistic road structure – coherent highways, not as spastic in terms of road placement, still some imperfections Intersections – A is a bridge with no exits, drivers on the small road (black) cannot get onto the interstate highway (red) ; at point B, drivers on the green (sort-of like Braddock) pass freely, but drivers on the small road have to go through a stop sign B A

  9. The Rest • I am focusing my research on average wait times on street lights and stop signs – actual data from a valid source on how long we spend at different types of intersections will be perfect. • If I have spare time left over after I finish my current goals, there are plenty of features I can add, a tutorial, more interface features, better heuristic.

  10. The Big Picture • My project will be expandable. Probably the best next step would be to add a learning algorithm, which will alter the heuristic based on results, in order to find the shortest path in the quickest way possible and make the search more efficient.

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