Browse curated autonomous driving papers on end-to-end driving, BEV perception, 3D object detection, motion prediction, path planning, ADAS, Tesla FSD, Waymo, and self-driving foundation models.
In this paper, a safe and reliable motion planning and control framework is proposed to handle the tracking errors caused by inaccurate tracking by coordinating the motion planning layer and controller.
Engineering 5.5 · Research 7.0 · Business 5.5
To begin with, we introduce the fundamental principles and technical features of 4D mmWave radar, delving into its comprehensive perception capabilities across distance, speed, angle, and time dimensions.
Engineering 5.0 · Research 7.0 · Business 5.0
The current three‐dimensional target detection algorithm for smart cars mainly uses three‐dimensional point cloud data collected by LiDAR.
Engineering 5.0 · Research 7.0 · Business 5.0
An autonomous driving research paper: Geometric information constraint 3D object detection from LiDAR point cloud for autonomous vehicles under adverse weather.
Engineering 5.0 · Research 7.0 · Business 5.0
In extreme off-road scenarios, autonomous driving technology holds strategic significance for enhancing emergency rescue capabilities, reducing labor intensity, and mitigating safety risks.
Engineering 5.0 · Research 7.5 · Business 5.0
In this paper, we introduce UniV2X, a pioneering cooperative autonomous driving framework that seamlessly integrates all key driving modules across diverse views into a unified network.
Engineering 6.0 · Research 7.0 · Business 5.5
To solve this problem, in this paper, we propose a non-parameterized key point projection method based on the attention mechanism, which significantly improves the computational speed of the algorithm.
Engineering 5.5 · Research 8.0 · Business 5.0
Our method uses less complex CNN architecture than existing ones.
Engineering 5.0 · Research 7.0 · Business 5.0
To address these previous issues, we develop EM-VLM4AD, an efficient, lightweight, multi-frame vision language model which performs Visual Question Answering for autonomous driving.
Engineering 7.0 · Research 7.5 · Business 5.0
In this regard, we propose a high-precision 3D object detection V2V cooperative perception algorithm.
Engineering 5.0 · Research 7.0 · Business 5.0
To overcome these limitations, we propose a transformer-based algorithm designed to fuse diverse representations from RGB-D cameras through knowledge distillation.
Engineering 7.0 · Research 7.0 · Business 5.0
To overcome these challenges, in this paper, we propose a Multi-Modal fusion transformer incorporating Driver Attention (M2DA) for autonomous driving.
Engineering 6.0 · Research 8.0 · Business 6.0
Advances in 3D object detection for autonomous driving primarily target identifying common entities like automobiles and pedestrians.
Engineering 5.5 · Research 7.0 · Business 5.5
In this paper, we introduce the first large-scale video prediction model in the autonomous driving discipline.
Engineering 5.5 · Research 8.0 · Business 5.5
Vision-based occupancy prediction, also known as 3D Semantic Scene Completion (SSC), presents a significant challenge in computer vision.
Engineering 6.5 · Research 8.0 · Business 5.0
In this paper, we introduce an approach that extracts features from front-view 2D camera images and LiDAR scans, then employs a sparse convolution network (Minkowski Engine), for 3D semantic occupancy prediction.
Engineering 5.5 · Research 7.0 · Business 5.0
In the paper, we introduce a novel framework with high performance, termed EFNet.
Engineering 5.5 · Research 8.0 · Business 5.0
In the fast-evolving world of Lidar technology, our study tackles the growing need for top-quality Lidar data.
Engineering 5.0 · Research 8.0 · Business 5.0
By leveraging features from local neighborhoods, and cross-instance attention score, we design a grouping module that further performs lane-wise clustering between neighboring and seeding points.
Engineering 5.5 · Research 8.0 · Business 5.5
To address these issues, we propose OccFusion, a depth estimation free multi-modal fusion framework.
Engineering 5.5 · Research 7.0 · Business 5.0