Travel time prediction by weighted fusion of probing vehicles and vehicle detectors data sources

Kevin P. Hwang, Wei Hsun Lee, Wen Bin Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Travel time information plays an important role in ITS, especially in advanced traveler information system (ATIS). Traditionally, travel time is predicted by a single data source, such as vehicle detectors (VD) or probing vehicles (PV). In this paper, we try to predict travel time by integrating these two data sources by a dynamic weighted fusion scheme. The weights of the data sources are dynamically determined by the distance weight scheme to enhance the prediction precision. The proposed TTP model is applied to a small traffic network located in the east and north district of Tainan City, Taiwan. VD data is provided by traffic bureau of Tainan city government and probing vehicles raw data is collected from a Taxi dispatching system. The experiment results show that dynamic weighted combination of these two data sources can enhance the precision of the TTP, and the prediction stability of the proposed model is better than both the single source TTP models (VD or PV).

Original languageEnglish
Title of host publication2012 12th International Conference on ITS Telecommunications, ITST 2012
Pages476-481
Number of pages6
DOIs
Publication statusPublished - 2012
Event2012 12th International Conference on ITS Telecommunications, ITST 2012 - Taipei, Taiwan
Duration: 2012 Nov 52012 Nov 8

Publication series

Name2012 12th International Conference on ITS Telecommunications, ITST 2012

Other

Other2012 12th International Conference on ITS Telecommunications, ITST 2012
Country/TerritoryTaiwan
CityTaipei
Period12-11-0512-11-08

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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