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Learning a Deep Cascaded Neural Network for Multiple Motion Commands Prediction in Autonomous Driving

  • Published:2021-12 Issue:12 Volume:22 Page:7585-7596
  • ISSN:1524-9050
  • Container-title:IEEE Transactions on Intelligent Transportation Systems
  • language:
  • Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Hu XueminORCID,Tang BoORCID,Chen LongORCID,Song Sheng,Tong Xiuchi

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hubei Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

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1. Anti-rollover Artificial Potential Field Motion Planning Method of an Autonomous Heavy Truck Optimised by Game Theory;Chinese Journal of Mechanical Engineering;2024-08-23

2. Robust autonomous driving control using deep hybrid-learning network under rainy/snown conditions;Multimedia Tools and Applications;2024-06-13

3. Navigating Complexity: A Deep Learning Approach to Lane Change Decisions in Autonomous Vehicles;2024 5th International Conference on Computer Engineering and Application (ICCEA);2024-04-12

4. High-Precision Positioning, Perception and Safe Navigation for Automated Heavy-Duty Mining Trucks;IEEE Transactions on Intelligent Vehicles;2024-04

5. Autonomous Driving in Unity Simulated Environments Using End-to-End CNN Approach;2024 7th International Conference on Advanced Algorithms and Control Engineering (ICAACE);2024-03-01
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