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Vehicle trajectory prediction is crucial for advancing autonomous driving and advanced driver assistance systems (ADAS).
Fast fourier transforms: a tutorial review and a state of the art
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U-net: Convolutional networks for biomedical image segmentation
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Improving deep neural networks using softplus units
Hao Zheng, Zhanlei Yang, Wenju Liu, Jizhong Liang, and Yanpeng Li · 2015
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An lstm network for highway trajectory prediction
Florent Altché and Arnaud de La Fortelle · 2017
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Gate-variants of gated recurrent unit (gru) neural networks
Rahul Dey and Fathi M Salem · 2017
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Convolutional neural network for trajectory prediction
Nishant Nikhil and Brendan Tran Morris · 2018
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Long-term prediction of vehicle trajectory using recurrent neural networks
Abdelmoudjib Benterki, Vincent Judalet, Maaoui Choubeila, and Moussa Boukhnifer · 2019
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Modeling vehicle interactions via modified lstm models for trajectory prediction
Shengzhe Dai, Li Li, and Zhiheng Li · 2019
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Vehicle trajectory prediction using intention-based conditional variational autoencoder
Xidong Feng, Zhepeng Cen, Jianming Hu, and Yi Zhang · 2019
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Multi-agent tensor fusion for contextual trajectory prediction
Tianyang Zhao, Yifei Xu, Mathew Monfort, Wongun Choi, Chris Baker, Yibiao Zhao, Yizhou Wang, and Ying Nian Wu · 2019
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Diverse sampling for normalizing flow based trajectory forecasting
Yecheng Jason Ma, Jeevana Priya Inala, Dinesh Jayaraman, and Osbert Bastani · 2020
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Interaction-aware trajectory prediction of connected vehicles using cnn-lstm networks
Xiaoyu Mo, Yang Xing, and Chen Lv · 2020
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Multi-vehicle collaborative learning for trajectory prediction with spatio-temporal tensor fusion
Yu Wang, Shengjie Zhao, Rongqing Zhang, Xiang Cheng, and Liuqing Yang · 2020
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Motion trajectory prediction based on a cnn-lstm sequential model
Guo Xie, Anqi Shangguan, Rong Fei, Wenjiang Ji, Weigang Ma, and Xinhong Hei · 2020
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Spatial-temporal graph neural network for interaction-aware vehicle trajectory prediction
Junan Chen, Yan Wang, Ruihan Wu, and Mark Campbell · 2021
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Dsa-gan: driving style attention generative adversarial network for vehicle trajectory prediction
Seungwon Choi, Nahyun Kweon, Chanuk Yang, Dongchan Kim, Hyukju Shon, Jaewoong Choi, and Kunsoo Huh · 2021
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Cross-attention is all you need: Adapting pretrained transformers for machine translation
Mozhdeh Gheini, Xiang Ren, and Jonathan May · 2021
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Driving style-based conditional variational autoencoder for prediction of ego vehicle trajectory
Dongchan Kim, Hyukju Shon, Nahyun Kweon, Seungwon Choi, Chanuk Yang, and Kunsoo Huh · 2021
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Graph and recurrent neural network-based vehicle trajectory prediction for highway driving
Xiaoyu Mo, Yang Xing, and Chen Lv · 2021
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Variational autoencoder-based vehicle trajectory prediction with an interpretable latent space
Marion Neumeier, Michael Botsch, Andreas Tollkühn, and Thomas Berberich · 2021
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Vehicles trajectory prediction using recurrent vae network
Miguel Ángel De Miguel, José María Armingol, and Fernando Garcia · 2022
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Stochastic trajectory prediction via motion indeterminacy diffusion
Tianpei Gu, Guangyi Chen, Junlong Li, Chunze Lin, Yongming Rao, Jie Zhou, and Jiwen Lu · 2022
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Motiondiffuser: Controllable multi-agent motion prediction using diffusion
Chiyu Jiang, Andre Cornman, Cheolho Park, Benjamin Sapp, Yin Zhou, Dragomir Anguelov, et al · 2023
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Large car-following data based on lyft level-5 open dataset: Following autonomous vehicles vs. human-driven vehicles
Guopeng Li, Yiru Jiao, Victor L Knoop, Simeon C Calvert, and JWC Van Lint · 2023
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Spatiotemporal capsule neural network for vehicle trajectory prediction
Yan Qin, Yong Liang Guan, and Chau Yuen · 2023
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Trajectory unified transformer for pedestrian trajectory prediction
Liushuai Shi, Le Wang, Sanping Zhou, and Gang Hua · 2023
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Vehicle position prediction using particle filtering based on 3d cnn-lstm model
Jiaqin Wang, Kai Liu, and Yi Gong · 2023
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End-to-end trajectory distribution prediction based on occupancy grid maps
Ke Guo, Wenxi Liu, and Jia Pan · 2022
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Muse-vae: Multi-scale vae for environment-aware long term trajectory prediction
Mihee Lee, Samuel S Sohn, Seonghyeon Moon, Sejong Yoon, Mubbasir Kapadia, and Vladimir Pavlovic · 2022
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Vehicle trajectory prediction in connected environments via heterogeneous context-aware graph convolutional networks
Yuhuan Lu, Wei Wang, Xiping Hu, Pengpeng Xu, Shengwei Zhou, and Ming Cai · 2022
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Crat-pred: Vehicle trajectory prediction with crystal graph convolutional neural networks and multi-head self-attention
Julian Schmidt, Julian Jordan, Franz Gritschneder, and Klaus Dietmayer · 2022
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Crat-pred: Vehicle trajectory prediction with crystal graph convolutional neural networks and multi-head self-attention
Julian Schmidt, Julian Jordan, Franz Gritschneder, and Klaus Dietmayer · 2022
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Graph-based spatial-temporal convolutional network for vehicle trajectory prediction in autonomous driving
Zihao Sheng, Yunwen Xu, Shibei Xue, and Dewei Li · 2022
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An integrated car-following and lane changing vehicle trajectory prediction algorithm based on a deep neural network
Kunsong Shi, Yuankai Wu, Haotian Shi, Yang Zhou, and Bin Ran · 2022
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Graph-based interaction-aware multimodal 2d vehicle trajectory prediction using diffusion graph convolutional networks
Keshu Wu, Yang Zhou, Haotian Shi, Xiaopeng Li, and Bin Ran · 2023
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Agnp: Network-wide short-term probabilistic traffic speed prediction and imputation
Meng Xu, Yining Di, Hongxing Ding, Zheng Zhu, Xiqun Chen, and Hai Yang · 2023
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Learnable diffusion-based amplitude feature augmentation for object tracking in intelligent vehicles
Zhibin Zhang, Wanli Xue, Qinghua Liu, Kaihua Zhang, and Shengyong Chen · 2023
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Mixed gaussian flow for diverse trajectory prediction
Jiahe Chen, Jinkun Cao, Dahua Lin, Kris Kitani, and Jiangmiao Pang · 2024
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Human as ai mentor: Enhanced human-in-the-loop reinforcement learning for safe and efficient autonomous driving
Zilin Huang, Zihao Sheng, Chengyuan Ma, and Sikai Chen · 2024
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Bat: Behavior-aware human-like trajectory prediction for autonomous driving
Haicheng Liao, Zhenning Li, Huanming Shen, Wenxuan Zeng, Dongping Liao, Guofa Li, and Chengzhong Xu · 2024
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A physics enhanced residual learning (perl) framework for vehicle trajectory prediction, 2024
Keke Long, Zihao Sheng, Haotian Shi, Xiaopeng Li, Sikai Chen, and Sue Ahn · 2024
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Dynamic spatio-temporal graph neural network for surrounding-aware trajectory prediction of autonomous vehicles
Hashmatullah Sadid and Constantinos Antoniou · 2024
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Traffic expertise meets residual rl: Knowledge-informed model-based residual reinforcement learning for cav trajectory control
Zihao Sheng, Zilin Huang, and Sikai Chen · 2024
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Diff-rntraj: A structure-aware diffusion model for road network-constrained trajectory generation
Tonglong Wei, Youfang Lin, Shengnan Guo, Yan Lin, Yiheng Huang, Chenyang Xiang, Yuqing Bai, and Huaiyu Wan · 2024
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Diffusion-based environment-aware trajectory prediction
Theodor Westny, Björn Olofsson, and Erik Frisk · 2024
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