highD
Emerging4papers using it
2024first seen
The 'highD' dataset is a benchmark that contains high-definition trajectory data of vehicles in complex driving scenarios, used to evaluate trajectory prediction models in autonomous driving systems.
Papers using highD (4)
- Hybrid Action Based Reinforcement Learning for Multi-Objective Compatible Autonomous DrivingMulti-Timescale Hierarchical Reinforcement Learning for Unified Behavior and Control of Autonomous DrivingMAVEN-T: Multi-Agent enVironment-aware Enhanced Neural Trajectory predictor with Reinforcement LearningCAV-AHDV-CAV: Mitigating Traffic Oscillations for CAVs through a Novel
Car-Following Structure and Reinforcement Learning