Contextual Recurrent Predictive Model for Long-Term Intent Prediction of Vulnerable Road Users

Saleh, Khaled, Hossny, Mohammed and Nahavandi, Saeid 2020, Contextual Recurrent Predictive Model for Long-Term Intent Prediction of Vulnerable Road Users, IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 8, pp. 3398-3408, doi: 10.1109/tits.2019.2927770.

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Title Contextual Recurrent Predictive Model for Long-Term Intent Prediction of Vulnerable Road Users
Author(s) Saleh, Khaled
Hossny, MohammedORCID iD for Hossny, Mohammed orcid.org/0000-0002-1593-6296
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Journal name IEEE Transactions on Intelligent Transportation Systems
Volume number 21
Issue number 8
Start page 3398
End page 3408
Total pages 11
Publisher IEEE
Place of publication Piscataway, NJ
Publication date 2020-08
ISSN 1524-9050
1558-0016
Keyword(s) Trajectory
Predictive models
Roads
Reinforcement learning
Recurrent neural networks
Forecasting
Kalman filters
Intent prediction
vulnerable road users (VRU)
autonomous vehicles
motion trajectory forecasting
reinforcement learning (IRL)
Science & Technology
Technology
Engineering, Civil
Engineering, Electrical & Electronic
Transportation Science & Technology
Engineering
Transportation
Language eng
DOI 10.1109/tits.2019.2927770
Indigenous content off
Field of Research 0801 Artificial Intelligence and Image Processing
0905 Civil Engineering
1507 Transportation and Freight Services
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2019, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30142030

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