DeepGame-TP: Integrating Dynamic Game Theory and Deep Learning for Trajectory Planning
Trajectory planning for automated vehicles in traffic has been a challenging task and a hot topic in recent research. The need for flexibility, transparency, interpretability and predictability poses challenges in deploying data-driven approaches in this safety-critical application. This paper propo...
Saved in:
Main Authors: | Giovanni Lucente, Mikkel Skov Maarssoe, Sanath Himasekhar Konthala, Anas Abulehia, Reza Dariani, Julian Schindler |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2024-01-01
|
Series: | IEEE Open Journal of Intelligent Transportation Systems |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10793110/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Computational Game Unit Balancing based on Game Theory
by: Emre Önal, et al.
Published: (2025-01-01) -
Analysis of DRM game control
by: Guo-jun MA, et al.
Published: (2012-09-01) -
Novel non-cooperative power control game algorithm for cognitive radio
by: Jun-hui ZHAO, et al.
Published: (2012-11-01) -
Game theory based forwarding control method for social network
by: Fangfang SHAN, et al.
Published: (2018-03-01) -
Gradient-Based Algorithms With Intermediate Observations in Static and Differential Games
by: Mohammad Safayet Hossain, et al.
Published: (2025-01-01)