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An LSTM-Based Autonomous Driving Model Using Waymo Open Dataset

An LSTM-Based Autonomous Driving Model Using Waymo Open Dataset

14 February 2020
Zhicheng Li
Zhihao Li
Xuan Di
Rongye Shi
ArXivPDFHTML

Papers citing "An LSTM-Based Autonomous Driving Model Using Waymo Open Dataset"

8 / 8 papers shown
Title
Evaluating Driver Readiness in Conditionally Automated Vehicles from
  Eye-Tracking Data and Head Pose
Evaluating Driver Readiness in Conditionally Automated Vehicles from Eye-Tracking Data and Head Pose
Mostafa Kazemi
Mahdi Rezaei
Mohsen Azarmi
31
0
0
20 Jan 2024
LaksNet: an end-to-end deep learning model for self-driving cars in
  Udacity simulator
LaksNet: an end-to-end deep learning model for self-driving cars in Udacity simulator
Lakshmikar R. Polamreddy
Youshan Zhang
20
3
0
24 Oct 2023
A context-aware pedestrian trajectory prediction framework for automated
  vehicles
A context-aware pedestrian trajectory prediction framework for automated vehicles
Arash Kalatian
Bilal Farooq
19
46
0
16 Apr 2021
A Physics-Informed Deep Learning Paradigm for Car-Following Models
A Physics-Informed Deep Learning Paradigm for Car-Following Models
Zhaobin Mo
Xuan Di
Rongye Shi
PINN
AI4CE
30
132
0
24 Dec 2020
A Survey on Autonomous Vehicle Control in the Era of Mixed-Autonomy:
  From Physics-Based to AI-Guided Driving Policy Learning
A Survey on Autonomous Vehicle Control in the Era of Mixed-Autonomy: From Physics-Based to AI-Guided Driving Policy Learning
Xuan Di
Rongye Shi
29
174
0
10 Jul 2020
Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial
  Imitation Learning
Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial Imitation Learning
Lionel Blondé
Pablo Strasser
Alexandros Kalousis
33
22
0
28 Jun 2020
Liability Design for Autonomous Vehicles and Human-Driven Vehicles: A
  Hierarchical Game-Theoretic Approach
Liability Design for Autonomous Vehicles and Human-Driven Vehicles: A Hierarchical Game-Theoretic Approach
Xuan Di
Xu Chen
E. Talley
16
23
0
05 Nov 2019
Review of Learning-based Longitudinal Motion Planning for Autonomous
  Vehicles: Research Gaps between Self-driving and Traffic Congestion
Review of Learning-based Longitudinal Motion Planning for Autonomous Vehicles: Research Gaps between Self-driving and Traffic Congestion
Hao Zhou
Jorge A. Laval
Anye Zhou
Yu Wang
W. Wu
Zhuo Qing
S. Peeta
18
37
0
02 Oct 2019
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