Traj-llm: A new exploration for empowering trajectory prediction with pre-trained large language models
Predicting the future trajectories of dynamic traffic actors is a cornerstone task in
autonomous driving. Though existing notable efforts have resulted in impressive …
autonomous driving. Though existing notable efforts have resulted in impressive …
PlanAgent: A Multi-modal Large Language Agent for Closed-loop Vehicle Motion Planning
Vehicle motion planning is an essential component of autonomous driving technology.
Current rule-based vehicle motion planning methods perform satisfactorily in common …
Current rule-based vehicle motion planning methods perform satisfactorily in common …
基于场景上下文信息的长时多车轨迹预测
杨秋宇， 缐凯， 郭继孚， 朱重远， 焦建彬 - 中国科学院大学学报, 2024 - journal.ucas.ac.cn
精准地感知周围车辆的未来行动对自动驾驶的安全性保障有着至关重要的作用,
本文主要关注于多车长时间轨迹预测这一复杂问题. 已有的轨迹预测方法可以大致分为联合预测 …
本文主要关注于多车长时间轨迹预测这一复杂问题. 已有的轨迹预测方法可以大致分为联合预测 …
A Graph Neural Network-Based Multi-agent Joint Motion Prediction Method for Motion Trajectory Prediction
H Gao, Z Huang, J Zhou, S Cheng, Q Wang… - … Conference on Intelligent …, 2024 - Springer
Autonomous driving is a revolutionary automotive technology that can greatly improve
driving safety and reduce traffic congestion. Multi-agent trajectory prediction plays an …
driving safety and reduce traffic congestion. Multi-agent trajectory prediction plays an …
Long-term multi-vehicle trajectory prediction with scene contextual information
Y Qiuyu, X Kai, GUO Jifu… - Journal of University …, 2024 - journal.ucas.ac.cn
Precisely perceiving the future actions of surrounding traffic agents is critical for ensuring the
safety of autonomous vehicle. This paper mainly focuses on the complicated problem of long …
safety of autonomous vehicle. This paper mainly focuses on the complicated problem of long …