Urban network travel time prediction via online multi-output Gaussian process regression

2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC) ◽

10.1109/itsc.2017.8317796 ◽

2017 ◽

Author(s):

Hector Rodriguez-Deniz ◽

Erik Jenelius ◽

Mattias Villani

Keyword(s):

Gaussian Process ◽

Travel Time ◽

Gaussian Process Regression ◽

Travel Time Prediction ◽

Urban Network ◽

Time Prediction

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Travel-Time Prediction using Gaussian Process Regression: A Trajectory-Based Approach

Proceedings of the 2009 SIAM International Conference on Data Mining ◽

10.1137/1.9781611972795.101 ◽

2009 ◽

Author(s):

Tsuyoshi Idé ◽

Sei Kato

Keyword(s):

Gaussian Process ◽

Travel Time ◽

Gaussian Process Regression ◽

Travel Time Prediction ◽

Time Prediction

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A Gaussian process regression method for urban road travel time prediction

2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) ◽

10.1109/fskd.2017.8393394 ◽

2017 ◽

Author(s):

Dong Wang ◽

Yage Wu ◽

Zhu Xiao

Keyword(s):

Gaussian Process ◽

Travel Time ◽

Gaussian Process Regression ◽

Regression Method ◽

Travel Time Prediction ◽

Time Prediction

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Integrated framework for real-time urban network travel time prediction on sparse probe data

IET Intelligent Transport Systems ◽

10.1049/iet-its.2017.0113 ◽

2018 ◽

Vol 12 (1) ◽

pp. 66-74 ◽

Author(s):

Matej Cebecauer ◽

Erik Jenelius ◽

Wilco Burghout

Keyword(s):

Travel Time ◽

Real Time ◽

Travel Time Prediction ◽

Urban Network ◽

Integrated Framework ◽

Time Prediction

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Urban Network Travel Time Prediction Based on a Probabilistic Principal Component Analysis Model of Probe Data

IEEE Transactions on Intelligent Transportation Systems ◽

10.1109/tits.2017.2703652 ◽

2018 ◽

Vol 19 (2) ◽

pp. 436-445 ◽

Author(s):

Erik Jenelius ◽

Haris N. Koutsopoulos

Keyword(s):

Principal Component Analysis ◽

Travel Time ◽

Principal Component ◽

Component Analysis ◽

Analysis Model ◽

Principal Component Analysis Model ◽

Travel Time Prediction ◽

Urban Network ◽

Time Prediction ◽

Probabilistic Principal Component Analysis

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Travel time prediction for Origin-Destination pairs without route specification in urban network

17th International IEEE Conference on Intelligent Transportation Systems (ITSC) ◽

10.1109/itsc.2014.6957940 ◽

2014 ◽

Author(s):

Sehyun Tak ◽

Sunghoon Kim ◽

Hwasoo Yeo

Keyword(s):

Travel Time ◽

Travel Time Prediction ◽

Urban Network ◽

Time Prediction

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Link and Route Travel Time Prediction Including the Corresponding Reliability in an Urban Network Based on Taxi Floating Car Data

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2442-15 ◽

2014 ◽

Vol 2442 (1) ◽

pp. 140-149 ◽

Author(s):

Mirsad Tulic ◽

Dietmar Bauer ◽

Wolfgang Scherrer

Keyword(s):

Travel Time ◽

Travel Time Prediction ◽

Urban Network ◽

Floating Car Data ◽

Time Prediction

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A knowledge based real-time travel time prediction system for urban network

Expert Systems with Applications ◽

10.1016/j.eswa.2008.03.018 ◽

2009 ◽

Vol 36 (3) ◽

pp. 4239-4247 ◽

Author(s):

Wei-Hsun Lee ◽

Shian-Shyong Tseng ◽

Sheng-Han Tsai

Keyword(s):

Travel Time ◽

Real Time ◽

Time Travel ◽

Prediction System ◽

Travel Time Prediction ◽

Urban Network ◽

Time Prediction ◽

Knowledge Based

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New Model of Travel-Time Prediction Considering Weather Conditions: Case Study of Urban Expressway

Journal of Transportation Engineering Part A Systems ◽

10.1061/jtepbs.0000491 ◽

2021 ◽

Vol 147 (3) ◽

pp. 04020161

Author(s):

Huamin Li ◽

Qingqing Wang ◽

Weixin Xiong

Keyword(s):

Travel Time ◽

Weather Conditions ◽

Travel Time Prediction ◽

New Model ◽

Time Prediction ◽

Urban Expressway

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A Study on the Travel Time Prediction for Improving the Reliability of Train Timetable Using Artificial Intelligence

Journal of The Korean Society For Urban Railway ◽

10.24284/jkosur.2019.9.7.3.381 ◽

2019 ◽

Vol 7 (3) ◽

pp. 381-389

Author(s):

Ahram Kang ◽

Jun-Seop Shin ◽

Kwang-Ho Shin ◽

Jee-won Park ◽

Jin Ahn

Keyword(s):

Artificial Intelligence ◽

Travel Time ◽

Travel Time Prediction ◽

Train Timetable ◽

Time Prediction

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Traffic congestion and travel time prediction based on historical congestion maps and identification of consensual days

Transportation Research Part C Emerging Technologies ◽

10.1016/j.trc.2020.102920 ◽

2021 ◽

Vol 124 ◽

pp. 102920

Author(s):

Nicolas Chiabaut ◽

Rémi Faitout

Keyword(s):

Travel Time ◽

Traffic Congestion ◽

Travel Time Prediction ◽

Time Prediction

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