Route Prediction from Trip Observations

Document Number: 2008-01-0201

Date Published: April 2008

Author(s):
Jon Froehlich - University of Washington
John Krumm - Microsoft Corp.

Abstract:
This paper develops and tests algorithms for predicting the end-to-end route of a vehicle based on GPS observations of the vehicle's past trips. We show that a large portion of a typical driver's trips are repeated. Our algorithms exploit this fact for prediction by matching the first part of a driver's current trip with one of the set of previously observed trips. Rather than predicting upcoming road segments, our focus is on making long-term predictions of the route. We evaluate our algorithms using a large corpus of real-world GPS driving data acquired from observing over 250 drivers for an average of 15.1 days per subject. Our results show how often and how accurately we can predict a driver's route as a function of the distance already driven.

Product Status: In Stock

Included in: SP-2193

See other papers presented at SAE World Congress & Exhibition, April 2008, Detroit, MI, USA, Session: Intelligent Vehicle Initiative (IVI) Technology Advanced Controls and Navigation Systems (Part 1 of 2)

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