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 Create a random graph generator Create a visual representation, perhaps using Java, to display the map

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)

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

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.

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

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) Second Quarter The RGG at this point was somewhat random – the following being a good example of the type of map it produces:

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

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.

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.