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Found 7 papers, 0 papers with code
PreGSU-A Generalized Traffic Scene Understanding Model for Autonomous Driving based on Pre-trained Graph Attention Network
In this study, we propose PreGSU, a generalized pre-trained scene understanding model based on graph attention network to learn the universal interaction and reasoning of traffic scenes to support various downstream tasks.
UniLiDAR: Bridge the domain gap among different LiDARs for continual learning
To this end, this paper proposes UniLiDAR, an occupancy prediction pipeline that leverages geometric realignment and semantic label mapping to facilitate multiple datasets training and mitigate performance degradation during deployment on heterogeneous platforms.
A Survey on Datasets for Decision-making of Autonomous Vehicle
Autonomous vehicles (AV) are expected to reshape future transportation systems, and decision-making is one of the critical modules toward high-level automated driving.
4D Millimeter-Wave Radar in Autonomous Driving: A Survey
In an effort to bridge this gap and stimulate future research, this paper presents an exhaustive survey on the utilization of 4D mmWave radar in autonomous driving.
Driving-Policy Adaptive Safeguard for Autonomous Vehicles Using Reinforcement Learning
This paper proposes a driving-policy adaptive safeguard (DPAS) design, including a collision avoidance strategy and an activation function.
SUPER: A Novel Lane Detection System
AI-based lane detection algorithms were actively studied over the last few years.
Safe Reinforcement Learning for Autonomous Vehicles through Parallel Constrained Policy Optimization
The simulations of two scenarios for autonomous vehicles confirm we can ensure safety while achieving fast learning.
