A “semi-lazy” approach to probabilistic path prediction in dynamic environments
Jingbo Zhou, Anthony K. H. Tung, Wei Wu, Wee Siong Ng · 2013
Path prediction is useful in a wide range of applications. Most of the existing solutions, however, are based on eager learning methods where models and patterns are extracted from historical trajectories and then used for future prediction. Since such approaches are committed to a set of statistically significant models or patterns, problems can arise in dynamic environments where the underlying models change quickly or where the regions are not covered with statistically significant models or patterns.