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.
To address this gap, this paper presents a lightweight and efficient 3D object understanding framework for real-life autonomous vehicles from scratch.
Engineering 5.5 · Research 7.0 · Business 5.5
To tackle these challenges, we propose CLS-3D (Content-wise LiDAR-Camera Fusion and Slot Reweighting Transformer for 3D Object Detection).
Engineering 5.5 · Research 8.0 · Business 5.0
Precise road object perception and localization are crucial for autonomous vehicle navigation, yet onboard sensors occasionally encounter challenges with occlusions and blind spots, particularly at intersections.
Engineering 5.5 · Research 8.0 · Business 5.5
To address these challenges, we propose a framework specifically designed for aerial-ground collaboration.
Engineering 6.5 · Research 7.0 · Business 5.0
Collaborative perception is essential for autonomous vehicles (AVs) to overcome individual sensing limitations in occluded or complex traffic environments.
Engineering 7.0 · Research 8.0 · Business 6.5
An autonomous driving research paper: A Review of the Development of BEV Perception Algorithms for Autonomous Driving Applications.
Engineering 5.0 · Research 7.0 · Business 6.0
In this paper, we design a full-dimensional programmability empowered self-driving 6G network architecture.
Engineering 5.0 · Research 7.0 · Business 5.0
In the adaptive fusion decoder, we introduce adaptive fusion modules to effectively merge the features of the encoder and the decoder together.
Engineering 5.5 · Research 7.0 · Business 5.0
Environmental perception is crucial for safe autonomous driving, enabling accurate analysis of the vehicle’s surroundings.
Engineering 5.0 · Research 7.0 · Business 5.0
To address this challenge, we propose a novel Dual-Stage Motion Pattern Tree (DS-MPT) algorithm.
Engineering 5.0 · Research 8.0 · Business 5.0
In this paper, we propose a monocular camera-based localization of a motorized wheeled robot using a 2D floor plan as a reference map.
Engineering 5.5 · Research 7.0 · Business 5.5
At present, traffic image detection technology represented by lane lines has emerged as a key area of research in the transportation.
Engineering 5.0 · Research 7.0 · Business 5.0
The convergence of sophisticated algorithms and evolving simulation platforms holds promise for advancements in autonomous driving.
Engineering 5.0 · Research 7.0 · Business 5.0
Drawing inspiration from recent advancements in inference computing, we propose OpenEMMA, an open-source end-to-end framework based on MLLMs.
Engineering 7.5 · Research 7.5 · Business 5.5
In autonomous racing, high-speed and accurate environmental perception is crucial.
Engineering 5.5 · Research 7.0 · Business 5.0
In this paper, we propose a world-model-based framework to exploit the scene evolution for perception.
Engineering 7.0 · Research 7.0 · Business 5.0
Depth estimation from images is fundamental for autonomous navigation of robots, vehicles, drones, and integrating navigation aid systems for people with visual impairments.
Engineering 5.0 · Research 8.0 · Business 5.0
In this paper, we explore a closed-loop framework for autonomous driving and propose a large Driving wOrld modEl (Doe-1) for unified perception, prediction, and planning.
Engineering 7.5 · Research 7.0 · Business 5.0
We introduce Bench2Drive-R, a generative framework that enables reactive closed-loop evaluation.
Engineering 6.5 · Research 8.0 · Business 5.5
To meet this challenge, we propose RT-BEV, the first frame-work designed to co-optimize message communication and object detection to improve real-time e2e BEV perception without sacrificing accuracy.
Engineering 6.0 · Research 7.0 · Business 5.0