Energetic Path Finding Across Massive Terrain Data

Abstract

Energetic Path Finding Across Massive Terrain Data Andrew TsuiBefore there were airplanes, cars, trains, boats, or bicycles, the primary means of transportation was on foot. Unfortunately, many of the trails used by ancient travelers have long since been abandoned. We present a software tool which can help visualize and predict where these forgotten trails might lie through the use of a human-centered cost metric. By comparing the paths generated by our software with known historical trails, we demonstrate how the tool can indicate likely trails used by ancient travelers. In addition, this new tool provides novel visualizations to better help the user understand alternate paths, effect of terrain, and nearby areas of interest. Such a tool could be used by archaeologists and historians to better visualize and understand the terrain and paths around sites of historical interest.This thesis is a continuation of previous work, with emphasis on the ability to generate paths which traverse several thousand kilometers. To accomplish this, various graph simplification and path approximation algorithms are explored to construct a real-time path finding algorithm. To this end, we show that it is possible to restrict the search space for a path finding algorithm while not disrupting accuracy. Combined with a multi-threaded variant of Dijkstra's shortest path algorithm, we present a tool capable of traversing the contiguous US, a dataset containing over 19 billion datapoints, in under three hours on a 2.5 Ghz dual core processor. The tool is demonstrated on several examples which show the potential archaeological and historical applicability, and provide avenues for future improvements.iv