[轨迹预测]What-If Motion Prediction for Autonomous Driving 来源Arxiv 2020 https://arxiv.org/abs/2008.10587开源代码https://github.com/wqi/WIMP摘要预测道路参与者的长期未来运动是部署安全自动驾驶汽车(AV)的核心挑战。可行的解决方案必须考虑… Sakura 3D Object Detection for Autonomous Driving: A Survey(...
这篇论文提出了统一自动驾驶(UniAD)框架,用于解决自动驾驶系统中的规划问题。具体来说, 感知模块:UniAD包含四个基于Transformer解码器的感知和预测模块,分别用于跟踪和映射、运动预测和占用预测。每个模块都通过查询接口与其他模块连接,形成一个统一的节点。 跟踪和映射:TrackFormer模块通过多目标跟踪(MOT)进行检测和跟踪...
Planning 将turn left, turn right and keep forward等运动编码为指令query(command embeddings),将planning query输入BEV特征使得运动规划过程能考虑到周围环境信息。Loss方面一方面需要让预测的指令接近GT轨迹,另一方面需要指令对应的运动轨迹远离被占据的栅格(利用occupancy predictoin信息)。 Experiment 实验训练分为两步,...
🚘 Planning-oriented philosophy: UniAD is a Unified Autonomous Driving algorithm framework following a planning-oriented philosophy. Instead of standalone modular design and multi-task learning, we cast a series of tasks, including perception, prediction and planning tasks hierarchically. 🏆 SOTA ...
CVPR 2023 的最佳论文「Planning-oriented Autonomous Driving(以路径规划为导向的自动驾驶)」,由上海人工智能实验室、武汉大学及商汤科技联合完成。 这篇论文首次提出了感知决策一体化的自动驾驶通用大模型—...
🚘 Planning-oriented philosophy: UniAD is a Unified Autonomous Driving algorithm framework following a planning-oriented philosophy. Instead of standalone modular design and multi-task learning, we cast a series of tasks, including perception, prediction and planning tasks hierarchically. 🏆 SOTA ...
可行的解决方案必须考虑… Sakura VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning 码出名企路发表于端到端自动... Generative AI for Autonomous Driving!前沿与机遇~ 自动驾驶之...发表于自动驾驶之...打开知乎App 在「我的页」右上角打开扫一扫 其他扫码方式:微信 下载知乎App ...
Bench2DriveBench2DriveUniAD-BaseDriving Score45.81# 8 Compare Bench2DriveBench2DriveUniAD-TinyDriving Score40.73# 10 Compare Trajectory PlanningnuScenesUniADCollision-3s0.71# 3 Compare L2-3s1.65# 3 Compare L2-1s0.48# 2 Compare L2-2s0.96# 2 ...
A novel driving-behavior-oriented method is proposed in this paper for improving trajectory planning performance of autonomous vehicle driving on urban structural road. Differ from the irregularity and unpredictability of escaping a maze or travelling on off-road, the driving on road emphasizes more ...
Modern autonomous driving system is characterized as modular tasks in sequential order, i.e., perception, prediction, and planning. In order to perform a wide diversity of tasks and achieve advanced-level intelligence, contemporary approaches either deploy standalone models for individual tasks, or ...