Injecting knowledge in data-driven vehicle trajectory predictors-Reference-Cited by-同舟云学术

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Injecting knowledge in data-driven vehicle trajectory predictors

Published:2021-07 Issue: Volume:128 Page:103010
ISSN:0968-090X
Container-title:Transportation Research Part C: Emerging Technologies
language:en
Short-container-title:Transportation Research Part C: Emerging Technologies

Author:

Bahari Mohammadhossein,Nejjar Ismail,Alahi Alexandre

Funder

Horizon 2020 Marie Skłodowska-Curie Actions

Publisher

Elsevier BV

Subject

Computer Science Applications,Transportation,Automotive Engineering,Civil and Structural Engineering

Reference60 articles.

1. Alahi, A., Goel, K., Ramanathan, V., Robicquet, A., Fei-Fei, L., Savarese, S., June 2017. Social lstm: Human trajectory prediction in crowded spaces. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

2. Learning to Predict Human Behavior in Crowded Scenes;Alahi,2017

3. Space–time analysis: Concepts, quantitative methods, and future directions;An;Ann. Assoc. Am. Geogr.,2015

4. Bae, S., Saxena, D., Nakhaei, A., Choi, C., Fujimura, K., Moura, S.J., 2019. Cooperation-aware lane change maneuver in dense traffic based on model predictive control with recurrent neural network. arXiv abs/1909.05665.

5. Bansal, M., Krizhevsky, A., Ogale, A.S., 2019. Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst. In: Robotics: Science and Systems XV. vol. 15.

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