BEV-ConvFusion: An Efficient 2D Fusion Framework for Real-Time Autonomous Perception
We propose BEV-ConvFusion, a novel 2D-domain fusion framework that overcomes this limitation.
Engineering 5.5 · Research 8.0 · Business 6.0
Autonomous Driving Papers with Code, Datasets and Engineering Notes
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.
RPFE-Net: RoI-guided pseudo-LiDAR point cloud feature enhancement network for multi-modal 3D object detection
An autonomous driving research paper: RPFE-Net: RoI-guided pseudo-LiDAR point cloud feature enhancement network for multi-modal 3D object detection.
Engineering 5.0 · Research 7.0 · Business 5.0
Autonomous Human Tracking Using Vision-LiDAR Fusion with Model Predictive Control-Based Trajectory Following
In this paper, a golf cart with improved autonomous driving capabilities has been used to construct a real-time human tracking application.
Engineering 5.0 · Research 7.0 · Business 5.0
Monocular Depth Estimation on an Edge Device Using MiDaS DPT Hybrid
In this paper, we present the design and implementation of an affordable and light-weight depth estimation system executed on a Raspberry Pi 5 platform.
Engineering 5.5 · Research 7.0 · Business 5.5
Adversarial Attacks and Defenses for Panoptic Perception Models in Autonomous Driving
Panoptic perception models in autonomous driving use deep learning models to interpret their surroundings and make real-time decisions.
Engineering 5.5 · Research 7.0 · Business 5.5
Progressive Gaussian Transformer with Anisotropy-aware Sampling for Open Vocabulary Occupancy Prediction
To address these limitations, we present PG-Occ, an innovative Progressive Gaussian Transformer Framework that enables open-vocabulary 3D occupancy prediction.
Engineering 7.0 · Research 8.0 · Business 5.5
Ground Segmentation Method Based on Polar Grid for 3D LiDAR Point Cloud
In this paper, we propose a realtime, CPU-based ground segmentation method that structures the point cloud into a polar grid and estimates the ground points based on the local features of the grid cells.
Engineering 5.0 · Research 7.0 · Business 5.0
HMambaOcc: Hierarchical Mamba for occupancy flow field prediction in autonomous driving under mixed traffic environments
An autonomous driving research paper: HMambaOcc: Hierarchical Mamba for occupancy flow field prediction in autonomous driving under mixed traffic environments.
Engineering 5.0 · Research 7.0 · Business 5.0
Low-latency and energy-efficient FPGA accelerator for sparse neural networks in edge LiDAR-based 3D object detection
An autonomous driving research paper: Low-latency and energy-efficient FPGA accelerator for sparse neural networks in edge LiDAR-based 3D object detection.
Engineering 5.0 · Research 7.0 · Business 5.0
V2V Cooperative Perception With Adaptive Communication Loss for Autonomous Driving
To alleviate these problems, we propose a multi-vehicle collaborative BEV perception network with adaptive communication loss, called AccBEV, based on conditional variational inference.
Engineering 6.0 · Research 8.0 · Business 5.5
Motion planning of quadrotors in cluttered environments using efficient mapping and spatial-temporal optimization
Specifically, the proposed method leverages a one-dimensional array with fixed memory size to facilitate large-scale autonomous flight without boundary constraints.
Engineering 5.5 · Research 7.0 · Business 5.5
DriveE2E: Closed-Loop Benchmark for End-to-End Autonomous Driving through Real-to-Simulation
To address these limitations, we introduce a simple yet challenging closed-loop evaluation framework that closely integrates real-world driving scenarios into the CARLA simulator with infrastructure cooperation.
Engineering 7.5 · Research 7.0 · Business 5.5
Path Planning Method for Autonomous Driving Vehicles Based on Deep Convolutional Neural Network
This paper proposes a dynamic adaptive convolutional path planning algorithm for path planning of autonomous vehicles.
Engineering 5.0 · Research 7.0 · Business 5.0
YOLOMP: Fast and Balanced Multi-Task Perception for Autonomous Driving
Autonomous driving demands real-time perception that balances accuracy across multiple visual tasks under tight computational budgets.
Engineering 5.5 · Research 7.0 · Business 6.5
AnchDrive: Bootstrapping Diffusion Policies with Hybrid Trajectory Anchors for End-to-End Driving
We propose AnchDrive, a framework for end-to-end driving that effectively bootstraps a diffusion policy to mitigate the high computational cost of traditional generative models.
Engineering 5.5 · Research 8.0 · Business 5.0
Digital Twin-based Cooperative Autonomous Driving in Smart Intersections: A Multi-Agent Reinforcement Learning Approach
In this paper, a digital twin (DT)-based cooperative driving system with roadside unit (RSU)-centric architecture is proposed for enhancing safety and efficiency at unsignalized intersections.
Engineering 5.5 · Research 7.0 · Business 6.5
Embedded Perception and Control System for an Autonomous Surface Vehicle using Visual-LiDAR Fusion and SLAM
The paper presents the design and implementation of a modular perception and control system for an autonomous surface vehicle (ASV), developed on a System-on-Module (SoM) embedded platform.
Engineering 5.0 · Research 7.0 · Business 5.0
UM-Depth : Uncertainty Masked Self-Supervised Monocular Depth Estimation with Visual Odometry
To address this, we introduce UM-Depth, a framework that combines motion- and uncertainty-aware refinement to enhance depth accuracy at dynamic object boundaries and in textureless regions.
Engineering 5.0 · Research 8.0 · Business 5.0
A lexicographic hierarchical planning framework using motion primitives for autonomous vehicles
An autonomous driving research paper: A lexicographic hierarchical planning framework using motion primitives for autonomous vehicles.
Engineering 5.0 · Research 7.0 · Business 5.0
Spatio-temporal Learning for Trajectory Prediction in Full Self-Driving Cars
Autonomous driving technology is advancing quickly.
Engineering 5.5 · Research 7.0 · Business 5.5