This paper shows that separately training a strategic lane and speed planner and a low-level vehicle controller enables a highway-driving agent to overtake slow vehicles and earn higher long-term reward than a single-level reinforcement learning baseline.
A multiple- goal reinforcement learning method for complex vehicle overtak- ing maneuvers
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Extensive Exploration in Complex Traffic Scenarios using Hierarchical Reinforcement Learning
This paper shows that separately training a strategic lane and speed planner and a low-level vehicle controller enables a highway-driving agent to overtake slow vehicles and earn higher long-term reward than a single-level reinforcement learning baseline.