Autonomous Driving

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Autonomous Driving

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Naturalistic Driving Data

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PillarDETR: YOLO-Backbone and RT-DETR Head for Real-Time 3D Object Detection
Jun 1, 2026Smit Kadvani, Shriya Gumber, Kriti Faujdar +13D Object Detection Light Detection And Ranging
Post-Deterministic Distributed Systems: A New Foundation for Trustworthy Autonomous Infrastructure
Jun 1, 2026Jun He, Deying YuDistributed Optimization Infrastructure
Crazyflow: An Accurate, GPU-Accelerated, Differentiable Drone Simulator in JAX
May 31, 2026Martin Schuck, Marcel P. Rath, Yufei Hua +3Drone Autonomous Driving Simulation
DeepIPCv3: Event-Aware Multi-Modal Sensor Fusion for Sudden Pedestrian Crossing Avoidance
May 31, 2026Oskar Natan, Andi Dharmawan, Aufaclav Zatu Kusuma Frisky +2Multi-Sensor Fusion Autonomous Driving
PairedGTA: Generating Driving Datasets for Controlled Photometric Shift Analysis
May 31, 2026Andrea Chianese, Giulio Rossolini, Alessandro Biondi +2Naturalistic Driving Data Autonomous Driving
Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trends
May 31, 2026Jiuming Liu, Chaojun Ni, Mengmeng Liu +7Video World Models World Models
From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction
May 30, 2026Xinyi Ning, Zilin Bian, Dachuan Zuo +2Trajectory Prediction Autonomous Driving
Eyes All Around: Design and Analysis of 360-Degree LiDAR Perception Using Equivariant Feature Learning in Unstructured Traffic
May 30, 2026Pranav Darshan, Raghuveer Narayanan Rajesh, M Uttara KumariAutonomous Driving Perception 3D Object Detection
DriveAnchor: Progressive Anchor-based Flow Learning for Autonomous Driving Planning
May 30, 2026Limin Yan, Haoyun Tang, Yutao Qiu +2Autonomous Driving Diffusion Planning
MUSCLE-NET: Predicted-Multiscale-Aware Network for Pedestrian Trajectory Forecasting
May 30, 2026Yu Liu, Ming Huang, Xiao Ren +3Pedestrian Trajectory Prediction Human Motion Prediction
4D Radar Meets LiDAR and Camera: Cooperative Perception under Adverse Weather
May 29, 2026Melih Yazgan, Iramm Hamdard, Qiyuan Wu +1Vision-Radar Fusion Sparse4D-Radar
Rethinking Amortized Neural Representations for High-Resolution Terrain Elevation Data
May 29, 2026Haoan Feng, Xin Xu, Leila De FlorianiImplicit Neural Representations Hyperbolic Learning
LFA: Layer Feature Attention for Run-Time Introspection of 2D Object Detectors in Automated Driving
May 29, 2026Mert Keser, Alois KnollObject Detection Introspection Adapters
nuReasoning: A Reasoning-Centric Dataset and Benchmark for Long-Tail Autonomous Driving
May 29, 2026Zhiyu Huang, Johnson Liu, Rui Song +13Naturalistic Driving Data Autonomous Driving
Safe2Drive: Evaluating Safe Driving Behaviors of E2E Autonomous Driving Models
May 29, 2026Nishad Sahu, Kalpana Panda, Congyuan Yu +3Driving Autonomous Driving
IDOL: Inverse-Dynamics-Guided Future Prediction for End-to-End Autonomous Driving
May 29, 2026Chenghao Zhang, Timin Li, Dongmei LiTrajectory Prediction Autonomous Driving
DriveMA: Driving Vision-Language-Action Models with verifiable Meta-Actions
May 29, 2026Weicheng Zheng, Yixin Huang, Qiao Sun +2Drives Vision-Language-Action Models
Before Parc Fermé: RL-Time Pruning for Efficient Embodied LLMs in Autonomous Driving
May 29, 2026Luca Benfenati, Ali Azimi, Matteo Risso +3Large Models Autonomous Driving
NTR: Neural Token Reconstruction for Scene Token Bottleneck in End-to-End Driving
May 29, 2026Jiahui Li, Jiawei Sun, Zixiang Ren +7Autonomous Driving Perception Concept Bottleneck Models
Does Visual Information Play a Decisive Role in Vision-Language-Action Model Driving Behavior?
May 29, 2026Jingtao He, Hongliang Lu, Xiaoyun Qiu +2Autonomous Driving Vision-Language-Action Models
Can BEV Perception Gracefully Degrade under Sensor Failures?
May 29, 2026Haifa Zhang, Yijing Wang, Haoyu Wang +2Multi-Sensor Fusion Bird'S-Eye View
IAF-Net: Illumination-Adaptive Fusion for Low-Light Urban Road Segmentation
May 29, 2026Bingtao Wang, Daojie Peng, Fulong Ma +2Dense Semantic Segmentation Autonomous Driving Perception
OrcaRouter: A Production-Oriented LLM Router with Hybrid Offline-Online Learning
May 29, 2026Zhenghua Bao, Fengya Tian, Chris Zhang +3Large Language Model Routing Large Language Model Serving
Uncertainty-Aware and Temporally Regulated Expert Advice in Reinforcement Learning for Autonomous Driving
May 28, 2026Ahmed Abouelazm, Felix Klingebiel, Philip Schörner +1Autonomous Driving Control System Operator Learning
FRUC: Feedforward Dynamic Scene Reconstruction from Uncalibrated Collaborative Driving Views
May 28, 2026Yihang Tao, Yu Guo, Zhengru Fang +2Dynamic Scene Reconstruction Collaborative Perception
CityGen: Structure-Guided City-Style Synthesis for Cross-City Autonomous Driving
May 28, 2026Zezhong Qian, Zhao Yang, Lu Tan +4Autonomous Driving Cross-Domain Generalization
Network Optimization Aspects of Autonomous Vehicles: Challenges and Future Directions
May 28, 2026Rudolf Krecht, Tamas Budai, Erno Horvath +3Autonomous Driving Collaborative Perception
V2XCrafter: Learning to Generate Driving Scene Across Agents
May 28, 2026Yihang Tao, Yu Guo, Senkang Hu +4Driving Scene Autonomous Driving Simulation
V2I Work Zone Geometry Reconstruction with Pose-Conditioned UWB Range Denoising
May 28, 2026Jiaxi Liu, Hangyu Li, Yang Cheng +7Geometric Reconstruction Ultra-Wideband
Multi-Resolution End-to-End Deep Neural Network for Optimizing Latency-Accuracy Tradeoff in Autonomous Driving
May 27, 2026Qitao Weng, Heechul YunAutonomous Driving Temporal Convolutional Networks
ReasonBreak: Probing Vulnerabilities in Reasoning-Enabled Vision-Language-Action Models for Autonomous Driving
May 27, 2026Mohammadreza Teymoorianfard, Jean-Philippe Monteuuis, Jonathan Petit +1Pretrained Vision-Language-Action Autonomous Driving
SARAD: LLM-Based Safety-Aware Hybrid Reinforcement Learning with Collision Prediction for Autonomous Driving
May 27, 2026Kangyu Wu, Peng Cui, Guoxi Chen +1Autonomous Driving Collision Prediction
Modeling Vehicle-Type-Specific Pedestrian Crash Avoidance Behavior in Safety-Critical Interactions Using Smooth-Mamba Deep Reinforcement Learning
May 27, 2026Qingwen Pu, Kun Xie, Hong Yang +2Pedestrian Autonomous Driving
DriveWAM: Video Generative Priors Enable Scalable World-Action Modeling for Autonomous Driving
May 27, 2026Chen Shi, Jinrui Xu, Shaoshuai Shi +3Video Pretraining Efficient World-Action Model
SAM-Enhanced Segmentation on Road Datasets: Balancing Critical Classes in Autonomous Driving
May 27, 2026Toomas Tahves, Mauro Bellone, Junyi Gu +1Dense Semantic Segmentation Naturalistic Driving Data
TPS-Drive: Task-Guided Representation Purification for VLM-based Autonomous Driving
May 26, 2026Jiaxiang Li, Yumao Liu, Ke MaAutonomous Driving Trajectory Prediction
Bridging Control with Neural Network Verifier alpha-beta-CROWN: A Tutorial
May 26, 2026Haoyu Li, Xiangru Zhong, Hao Cheng +2Neural Network Verification Neural Control
AnyScene: Towards Highly Controllable Driving Scene Generation at Anywhere and Beyond
May 25, 2026Haiming Zhang, Junfei Zhou, Feng Jiang +6Controllable Video Generation Autonomous Driving
A Pedestrian-Vehicle Interaction Benchmark and Annotation Framework for Unstructured Scenes via Uncalibrated Cameras
May 25, 2026Haoyang Peng, Qian Hu, Songan Zhang +1Naturalistic Driving Data Autonomous Driving
Decision-Making with Lightweight Confidence-Aware Language Model for Autonomous Driving
May 25, 2026Ruoyu Yao, Ruiguo Zhong, Pei Liu +3Autonomous Driving Efficient Vision-Language-Action Models
Physics-Aware 3D Gaussian Editing for Driving Scene Generation
May 25, 2026Feng Zhou, Jian Zhang, Yuhang Sun +5Driving Scene Feed-Forward 3D Gaussian Reconstruction
Neuromorphic LiDAR-based Bird's Eye View Object Detection using Energy-efficient Spiking Neural Networks
May 24, 2026Sambit Mohapatra, Senthil Yogamani, Heinrich Gotzig +1Neuromorphic Hardware 3D Object Detection
Semantics-Guided Multimodal Masked Autoencoder Pretraining for 3D BEV Object Detection
May 24, 2026Prabuddhi Wariyapperuma, Rajitha de Silva, Marc Hanheide +23D Object Detection Bird'S-Eye View
RECTOR: Priority-Aware Rule-Based Reranking for Compliance-Aware Autonomous Driving Trajectory Selection
May 24, 2026Hadi Hajieghrary, Benedikt Walter, Chaitanya Shinde +2Autonomous Driving Waymo Open Motion Dataset
ParkingWorld: End-to-End Autonomous Parking Reinforcement Learning from Corrective Experience in 3DGS Simulation
May 24, 2026Zhengcheng Yu, Changze Li, Haoran Liu +1Autonomous Driving Advanced Jet Trainer
ARCANE-PedSynth: Synthetic Multi-Pedestrian Datasets with Behavioural Crossing Annotations
May 24, 2026Muhammad Naveed Riaz, Maciej Wielgosz, Antonio M. López PeñaNaturalistic Driving Data Pedestrian Trajectory Prediction
When Does Adaptive Guidance Help? Belief-Aware Privileged Distillation for Autonomous Driving Under Partial Observability
May 24, 2026Mehmet HaklidirAutonomous Driving Partial Observability
DBPnet: Damper Characteristics-Based Bayesian Physics-Informed Neural Network for Wheel Load Estimation
May 24, 2026Tianyi Wang, Tianyi Zeng, Zimo Zeng +8Conventional Physics-Informed Neural Networks Vehicle Dynamics
MR-LiDAR: A Multi-Resolution Roadside LiDAR Benchmark for Perception Diagnostics and Deployment Guidance
May 23, 2026Shunlai Cui, Peng Cao, Yuan Zhu +5Lidar Light Detection And Ranging
NudgeVAD: Language-Nudged End-to-End Driving via FiLM Residuals
May 23, 2026Chieh-Chi Yang, Yu-Hsiang Chen, Yi-Ting ChenAutonomous Driving
SparseWorld: Enhancing End-to-End Autonomous Driving via World Models with Sparse Scene Representation
May 23, 2026Ruoyu Wang, Jingke Wang, Yukai Ma +5Autonomous Driving Trajectory Prediction
Detecting Drunk Driving Using Off-the-Shelf Smartwatches
May 22, 2026Robin Deuber, Lanlan Yang, Michal Bechny +9Wearable Devices Driving
CBANet: A Compact Attention-Based CNN-BiLSTM Network for Aggressive Driving Event Detection
May 22, 2026Hanadi Alhamdan, Ghadah Alosaimi, Amir Atapour-Abarghouei +1Naturalistic Driving Data Driving
RS2AD-LiDAR: End-to-End Autonomous Driving LiDAR Data Generation from Roadside Sensor Observations
May 22, 2026Runyi Huang, Ni Ding, Ruidan Xing +3Lidar Light Detection And Ranging
GFSR: Geometric Fidelity and Spatial Refinement for Reliable Lane Detection
May 22, 2026Tiancheng Wang, Zhaolu Ding, Richeng Xu +5Autonomous Driving Confidence Estimation
ChainFlow-VLA: Causal Flow Planning with Vision-Language Models
May 22, 2026Xiyang Wang, Xinlin Wang, Tingguang Zhou +7Diffusion Planning Autonomous Driving
Lipschitz Optimization for Formal Verification of Homographies
May 22, 2026Jean-Guillaume Durand, Panagiotis Kouvaros, Maxime Gariel +1Lipschitz Constant Formal Verification
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving
May 22, 2026Hao Vo, Khoa Vo, Phu Loc Nguyen +10Autonomous Driving Large Vision Language Models
Fast-dDrive: Efficient Block-Diffusion VLM for Autonomous Driving
May 22, 2026Kewei Zhang, Jin Wang, Sensen Gao +9Autonomous Driving Efficient Vision-Language-Action Models
Scene Reconstruction as Mapping Priors for 3D Detection
May 21, 2026Yang Fu, Yuliang Zou, Hao Xiang +83D Object Detection Autonomous Driving Perception

Jun 1, 2026 · cs.CVJ/K move · Enter open · S save

PillarDETR: YOLO-Backbone and RT-DETR Head for Real-Time 3D Object Detection

Smit Kadvani, Shriya Gumber, Kriti Faujdar, Harsh Dave

Real-time 3D object detection is a critical component for the safe operation of autonomous driving systems and robotics. While LiDAR point clouds provide accurate spatial information, processing them efficiently remains a significant challenge. Traditional methods rely on complex 3D convolutions or anchor-based paradigms that struggle to balance detection accuracy with inference speed. In this paper, we propose PillarDETR, a novel end-to-end 3D object detection architecture that combines the efficiency of pillar-based LiDAR encoding with the representational power of modern 2D vision models. Specifically, PillarDETR replaces standard convolutional backbones with a Cross Stage Partial (CSP) network derived from YOLOv8, enabling richer feature extraction from pseudoimages. Furthermore, we discard conventional anchor-based or center-based detection heads in favor of a Real-Time Detection Transformer (RT-DETR) decoder. This hybrid design allows the network to capture global context and directly predict 3D bounding boxes without relying on non-maximum suppression (NMS). Extensive experiments on the KITTI and nuScenes benchmarks demonstrate that PillarDETR achieves a compelling trade-off between mean Average Precision (mAP) and inference latency. Our ablation studies confirm that integrating the YOLOv8 backbone and RT-DETR head yields substantial improvements over the PointPillars baseline, establishing PillarDETR as a highly effective solution for real-time 3D perception.

3D Object Detection Light Detection And Ranging Autonomous Driving

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