Title :
Travel Time Prediction Using Floating Car Data Applied to Logistics Planning
Author :
Simroth, Axel ; Zähle, Henryk
Author_Institution :
Fraunhofer Inst. for Transp. & Infrastruc ture Syst. IVI, Dresden, Germany
fDate :
3/1/2011 12:00:00 AM
Abstract :
Travel time information plays an important role in transportation and logistics. Much research has been done in the field of travel time prediction in local areas, aiming at accurate short-term predictions based on the current traffic situation and historical data of the area. In contrast, literature on prediction methods for long-range trips in large areas is rare, although it is highly relevant for logistics companies to manage their fleet of vehicles. In this paper, we present a new algorithm for predicting the remaining travel times of long-range trips. It makes use of nonparametric distribution-free regression models, which are applicable only in the presence of a sufficiently large database. Since, in contrast to local areas, such a base is visionary for large areas, we bring into play a dynamic data preparation to artificially enlarge the database. The algorithm also takes into account that routes of long-range trips are not completely given in advance but are rather unknown and subject to change. We illustrate our algorithm by means of simulations and a real-life case study at a German logistics company. The latter shows that, by our algorithm, the average relative error can be halved compared with conventional methods.
Keywords :
logistics; regression analysis; transportation; floating car data; logistics planning; long-range trips; nonparametric regression model; traffic information systems; transportation; travel time prediction; Floating car data (FCD); nonparametric regression; travel time prediction;
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
DOI :
10.1109/TITS.2010.2090521