Transformer-based multi-modal feature fusion for end-to-end autonomous driving
An autonomous driving research paper: Transformer-based multi-modal feature fusion for end-to-end autonomous driving.
Engineering 5.5 · Research 7.0 · Business 5.0
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.
NavDrive: Safety-Enhanced End-to-End Autonomous Driving With Navigation-Guided Diffusion Policy
To address these challenges, we propose NavDrive, a safety-enhanced end-to-end autonomous driving framework that formulates planning as a multi-modal generative process.Specifically, NavDrive integrates navigation-based guidance into a diffusion policy.
Engineering 7.5 · Research 8.0 · Business 5.0
FOR: Point Cloud Outlier Removal Based on Fuzzy Theory and Informativeness and Its Application to 3D Object Detection
To overcome this limitation, this paper proposes a fuzzy outlier removal (FOR) method based on fuzzy theory and informativeness.
Engineering 5.5 · Research 7.0 · Business 5.0
Enhancing BEV Perception Through Vehicle-Road Cooperative Systems: An Attention-Based Cross-View Fusion Approach
This paper presents a novel vehicle-to-infrastructure (V2I) cooperative perception framework to address inherent limitations of bird's eye view (BEV) systems in autonomous driving.
Engineering 5.0 · Research 8.0 · Business 5.0
An Autonomous Driving System with CARLA using Reinforcement Learning
Developing systems capable of driving autonomously demands not only robust perception of the surrounding environment but also reliable decision-making under real-world uncertainty.
Engineering 6.0 · Research 7.0 · Business 6.5
Adversarial Flow Matching for Imperceptible Attacks on End-to-End Autonomous Driving
In this paper, we propose Adversarial Flow Matching (AFM), a novel gray-box attack framework that exploits Transformer structural vulnerabilities in E2E AD models.
Engineering 5.5 · Research 8.0 · Business 5.0
Multi-Objective Trajectory Optimization for Autonomous Vehicles Based on an Improved Driving Risk Field
To address these challenges, this paper proposes an Improved Driving Risk Field-based Multi-objective Trajectory Optimization (IDRF-MTO) method.
Engineering 5.0 · Research 7.0 · Business 5.0
CooperDrive: Enhancing Driving Decisions Through Cooperative Perception
We propose CooperDrive, a cooperative perception framework that augments situational awareness and enables earlier, safer driving decisions.
Engineering 6.0 · Research 7.0 · Business 5.5
Long-SCOPE: Fully Sparse Long-Range Cooperative 3D Perception
To overcome these limitations, we introduce Long-SCOPE, a fully sparse framework designed for robust long-distance cooperative 3D perception.
Engineering 5.5 · Research 8.0 · Business 6.0
DVGT-2: Vision-Geometry-Action Model for Autonomous Driving at Scale
In this paper, we propose an alternative Vision-Geometry-Action (VGA) paradigm that advocates dense 3D geometry as the critical cue for autonomous driving.
Engineering 6.0 · Research 7.0 · Business 5.0
BEVDrive-E2E: Imitation With Bird's Eye View Perception for Interpretable End-to-End Autonomous Driving
To address this issue, we propose the BEVDrive-E2E to explore the interpretability of the end-to-end model by using visual abstractions in bird's eye view (BEV).
Engineering 5.5 · Research 8.0 · Business 5.0
Class-Distribution Guided Active Learning for 3D Occupancy Prediction in Autonomous Driving
To address these challenges, we propose a class-distribution guided active learning framework for selecting training samples to annotate in autonomous driving datasets.
Engineering 5.5 · Research 7.0 · Business 5.0
An Instance-Centric Panoptic Occupancy Prediction Benchmark for Autonomous Driving
To address these challenges, this paper presents an instance-centric benchmark for the 3D panoptic occupancy prediction task.
Engineering 5.0 · Research 7.0 · Business 5.0
Latent-WAM: Latent World Action Modeling for End-to-End Autonomous Driving
We introduce Latent-WAM, an efficient end-to-end autonomous driving framework that achieves strong trajectory planning through spatially-aware and dynamics-informed latent world representations.
Engineering 5.5 · Research 8.5 · Business 5.0
Weather-aware Autonomous Driving with Road Condition Analysis using CARLA
An autonomous driving research paper: Weather-aware Autonomous Driving with Road Condition Analysis using CARLA.
Engineering 5.0 · Research 7.0 · Business 5.0
AutoMoT: A Unified Vision-Language-Action Model with Asynchronous Mixture-of-Transformers for End-to-End Autonomous Driving
To address these challenges, we propose AutoMoT in this work, an end-to-end AD framework that unifies reasoning and action generation within a single vision-language-action (VLA) model.
Engineering 7.0 · Research 8.0 · Business 5.0
Multimodal Coarse-to-Local Transformer for End-to-End Autonomous Driving (Student Abstract)
Therefore, we propose a multimodal coarse-to-local transformer (MC2L-Transformer), which is composed of a hierarchical transformer architecture.
Engineering 5.5 · Research 7.0 · Business 5.0
Diverse Human Driving Vehicle Simulation in Background Traffic for Autonomous Driving Tests
In this work, we design a smart human driving vehicle simulator HDSim which is empowered by cognitively inspired modeling and AI models.
Engineering 5.0 · Research 8.0 · Business 5.0
SPSC: Sparse and Scalable Multi-Modal 3D Occupancy Prediction for Autonomous Driving
This paper presents a framework leveraging SParse representation and SCalable feature interaction to address the aforementioned challenges, called SPSC.
Engineering 5.5 · Research 8.0 · Business 5.0
Computer Vision-Driven Navigation and Decision Making in Autonomous Industrial Vehicles
The use of autonomous systems to increase productivity, lessen reliance on manual labor, and reduce operational errors in material handling has increased due to the quick development of industrial automation.
Engineering 5.0 · Research 7.0 · Business 5.0