Vehicle Trajectory Prediction by Knowledge-Driven LSTM Network in Urban Environments
Joint Authors
Zhao, Pan
Wang, Shaobo
Yu, Biao
Huang, Weixin
Liang, Huawei
Source
Journal of Advanced Transportation
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-20, 20 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-07
Country of Publication
Egypt
No. of Pages
20
Main Subjects
Abstract EN
An accurate prediction of future trajectories of surrounding vehicles can ensure safe and reasonable interaction between intelligent vehicles and other types of vehicles.
Vehicle trajectories are not only constrained by a priori knowledge about road structure, traffic signs, and traffic rules but also affected by posterior knowledge about different driving styles of drivers.
The existing prediction models cannot fully combine the prior and posterior knowledge in the driving scene and perform well only in a specific traffic scenario.
This paper presents a long short-term memory (LSTM) neural network driven by knowledge.
First, a driving knowledge base is constructed to describe the prior knowledge about a driving scenario.
Then, the prediction reference baseline (PRB) based on driving knowledge base is determined by using the rule-based online reasoning system.
Finally, the future trajectory of the target vehicle is predicted by an LSTM neural network based on the prediction reference baseline, while the predicted trajectory considers both posterior and prior knowledge without increasing the computation complexity.
The experimental results show that the proposed trajectory prediction model can adapt to different driving scenarios and predict trajectories with high accuracy due to the unique combination of the prior and posterior knowledge in the driving scene.
American Psychological Association (APA)
Wang, Shaobo& Zhao, Pan& Yu, Biao& Huang, Weixin& Liang, Huawei. 2020. Vehicle Trajectory Prediction by Knowledge-Driven LSTM Network in Urban Environments. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-20.
https://search.emarefa.net/detail/BIM-1180946
Modern Language Association (MLA)
Wang, Shaobo…[et al.]. Vehicle Trajectory Prediction by Knowledge-Driven LSTM Network in Urban Environments. Journal of Advanced Transportation No. 2020 (2020), pp.1-20.
https://search.emarefa.net/detail/BIM-1180946
American Medical Association (AMA)
Wang, Shaobo& Zhao, Pan& Yu, Biao& Huang, Weixin& Liang, Huawei. Vehicle Trajectory Prediction by Knowledge-Driven LSTM Network in Urban Environments. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-20.
https://search.emarefa.net/detail/BIM-1180946
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1180946