We propose a data structure that stores previously observed vehicle paths in a given area in order to predict the forward trajectory of an observed vehicle at any stage. Incomplete vehicle trajectories are conditioned against in a  Past Tree , to predict future trajectories in another tree structure - a  Future Tree . Many use cases in transportation simulation benefit from higher validity by considering historical paths in determining how to route vehicle entities. Instead of assigning static and independent turn probabilities at intersections, the storage and retrieval of historical path information can give a more accurate picture of future traffic trends and enhance the capabilities of real-time simulations to, say, inform mobile phone users of expected traffic jams along certain segments, direct the search efforts of law enforcement personnel, or allow more effective synchronization of traffic signals.
['Philip Pecher', 'Michael Hunter', 'Richard M. Fujimoto']
Past and future trees: structures for predicting vehicle trajectories in real-time