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.
Autonomous Vehicles (AVs) lack considerable reliability in unstructured contexts with road surface deterioration, particularly potholes.
Engineering 5.5 · Research 7.0 · Business 5.0
In this paper, we introduce a trajectory optimization framework that natively incorporates the complex and nonlinear effects of friction uncertainty into the planning process to improve both the performance and robustness of maneuvering at high accelerations.
Engineering 5.0 · Research 7.0 · Business 5.0
Sensors play a fundamental role in sensing the environment for autonomous vehicle perception, providing accurate and reliable data essential for understanding and navigating the surroundings.
Engineering 5.0 · Research 7.0 · Business 5.0
3D object detection plays a crucial role in autonomous driving, with Bird’s Eye View (BEV) becoming increasingly popular for its rich contextual information, ease of multi-modal fusion, and scalability.
Engineering 6.0 · Research 7.5 · Business 5.5
The need for high-quality simulation scenarios to verify the safety of autonomous driving systems is growing, but there are still obstacles to overcome, like the high cost and low efficiency of creating scenario files that satisfy simulation platform standards.
Engineering 5.5 · Research 7.5 · Business 6.0
With the rapid development of autonomous driving technology, environmental perception, as its core module, has attracted much attention.
Engineering 5.5 · Research 7.0 · Business 5.0
In this paper, we give a brief look at the sensors and how they work together in autonomous vehicles.
Engineering 5.0 · Research 7.0 · Business 5.0
To address these limitations, we propose HiPro-AD, a proposal-centric sparse E2E planning framework that fundamentally diverges from dense BEV paradigms.
Engineering 5.5 · Research 8.0 · Business 5.0
In this paper, we introduce PointMapNet, a novel framework for the construction of high-definition (HD) maps that shifts from traditional dense Bird's Eye View (BEV) feature reliance to a point feature-based approach.
Engineering 6.5 · Research 8.0 · Business 5.0
We propose Foresee, a technique that identifies near misses using a misbehavior forecaster that computes possible future states of the ego-vehicle under test.
Engineering 6.0 · Research 8.0 · Business 6.0
To address this gap, we propose IndiVNet, a semantic segmentation architecture tailored for unstructured Indian driving environments.
Engineering 5.0 · Research 7.0 · Business 5.0
We propose Nano and Veracity Detection Transformer (NV-DETR), a lightweight, highperformance detection framework built on RT-DETR.
Engineering 5.5 · Research 7.0 · Business 5.0
To enhance the perception accuracy and robustness of unmanned vehicle formations in complex dynamic environments, this paper proposes an environmental perception method based on LiDAR-visual fusion and a multi-scale attention mechanism (MSA).
Engineering 5.0 · Research 7.0 · Business 5.0
A new approach, LaneGuardMapper, is suggested in this paper to detect and track lanes in real time, no matter the driving circumstances.
Engineering 5.0 · Research 7.0 · Business 5.0
This paper presents an AI-based framework that integrates image quality assessment (IQA) and lens defect analysis to enhance the robustness of camera-based perception systems in autonomous vehicles.
Engineering 5.5 · Research 7.0 · Business 5.5
In this work, we propose LADY, the first fully linear attention-based generative model for end-to-end autonomous driving.
Engineering 6.0 · Research 8.0 · Business 6.0
In this paper, we propose DrivePI, a novel spatial-aware 4D MLLM that serves as a unified Vision-Language-Action (VLA) framework that is also compatible with vision-action (VA) models.
Engineering 7.5 · Research 8.5 · Business 5.0
This paper presents a novel integrated control framework that combines Distracted Driving Detection (DDD) with adaptive Vehicle Platooning (VP) to enhance both road safety and platooning performance.
Engineering 5.5 · Research 8.0 · Business 6.0
We proposed a trajectory optimization method for curvy road environments containing irregular embedded obstacles.
Engineering 5.0 · Research 8.0 · Business 5.0
In this paper, we propose SparseCoop, a fully sparse cooperative perception framework for 3D detection and tracking that completely discards intermediate BEV representations.
Engineering 5.5 · Research 8.0 · Business 5.5