Adaptive Probabilistic Vehicle Trajectory Prediction Through Physically
Feasible Bayesian Recurrent Neural Network

Adaptive Probabilistic Vehicle Trajectory Prediction Through Physically Feasible Bayesian Recurrent Neural Network

11 November 2019

Chen Tang

Masayoshi Tomizuka

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Papers citing "Adaptive Probabilistic Vehicle Trajectory Prediction Through Physically Feasible Bayesian Recurrent Neural Network"

6 / 6 papers shown

Title
Risk-aware Vehicle Motion Planning Using Bayesian LSTM-Based Model Predictive Control Yufei Huang Mohsen Jafari 46 5 0 15 Jan 2023
Physics Embedded Neural Network Vehicle Model and Applications in Risk-Aware Autonomous Driving Using Latent Features Taekyung Kim Ho-Woon Lee Wonsuk Lee 67 20 0 16 Jul 2022
Continual Learning for Real-World Autonomous Systems: Algorithms, Challenges and Frameworks Khadija Shaheen Muhammad Abdullah Hanif Osman Hasan Mohamed Bennai CLL 84 93 0 26 May 2021
Temporally-Continuous Probabilistic Prediction using Polynomial Trajectory Parameterization Zhaoen Su Chao Wang Henggang Cui Nemanja Djuric Carlos Vallespi-Gonzalez David Bradley 159 7 0 01 Nov 2020
Deep Learning for Vision-based Prediction: A Survey Amir Rasouli 104 42 0 30 Jun 2020
End-to-end Autonomous Driving Perception with Sequential Latent Representation Learning Jianyu Chen Zhuo Xu Masayoshi Tomizuka BDL 77 13 0 21 Mar 2020