4DLidarOpen is a new open dataset providing synchronized 4D FMCW Lidar velocity measurements, multi-Lidar and camera data, and 3D bounding-box annotations with track IDs to support benchmarks on 3D detection, BEV segmentation, flow prediction, and motion forecasting.
hub
Carla: An open urban driving simulator
14 Pith papers cite this work. Polarity classification is still indexing.
14
Pith papers citing it
hub tools
citation-role summary
background 1
method 1
citation-polarity summary
representative citing papers
The SNG framework and SNG-VLA model enable end-to-end driving systems to better incorporate global navigation for state-of-the-art route following without auxiliary perception losses.
NeuroLiDAR adaptively boosts LiDAR frame rates to 27.8-66 Hz via event-camera fusion and cuts depth RMSE by 29% on a new ELiDAR dataset.
Real2Sim reconstructs editable dynamic driving scenes as temporally continuous Gaussians integrated with a differentiable MPM physics solver for high-fidelity simulation of interactions and collisions.
VRS generates annotated roadside LiDAR data from vehicle observations via novel view synthesis with geometry completion and occupancy constraints, improving 3D object detection generalization.
AdvAD produces physical-world adversarial patches with improved transferability to unseen object detectors by multi-model optimization, adaptive balancing, and physical variation robustness.
ParkingScenes is a new multimodal dataset of 704 structured reverse and parallel parking episodes generated in CARLA with Hybrid A* and MPC trajectories, showing better model performance than unstructured simulation data.
A platform using flow matching for real-world image generation and an adversarial policy creates challenging corner cases to evaluate end-to-end autonomous driving models like UniAD and VAD, showing performance degradation.
A real-time hybrid digital twin platform couples high-fidelity CARLA-SUMO co-simulation with a physical CAV test site via V2X for closed-loop control and multi-scenario verification.
REAP trains an end-to-end SAC policy with behavior cloning and collision penalties inside a 3DGS Real2Sim simulator and transfers it to physical vehicles, succeeding in narrow mechanical parking slots.
A systematic review proposes a generic two-layer architecture for Freight Signal Priority systems that links sensing modalities to reliable priority decisions while accounting for detection and communication uncertainties.
A simulation pipeline reconstructs real vehicle-e-scooter interactions and extends them to higher-risk scenarios using a Social Force Model to validate autonomous vehicle collision avoidance.
The paper introduces a safety framework for datasets in autonomous driving that uses the AI Data Flywheel and lifecycle processes to identify hazards and ensure compliance with ISO/PAS 8800.
citing papers explorer
-
4DLidarOpen: An Open 4D FMCW Lidar Dataset for Motion-Aware Autonomous Driving
4DLidarOpen is a new open dataset providing synchronized 4D FMCW Lidar velocity measurements, multi-Lidar and camera data, and 3D bounding-box annotations with track IDs to support benchmarks on 3D detection, BEV segmentation, flow prediction, and motion forecasting.
-
Unveiling the Surprising Efficacy of Navigation Understanding in End-to-End Autonomous Driving
The SNG framework and SNG-VLA model enable end-to-end driving systems to better incorporate global navigation for state-of-the-art route following without auxiliary perception losses.
-
NeuroLiDAR: Adaptive Frame Rate Depth Sensing via Neuromorphic Event-LiDAR Fusion
NeuroLiDAR adaptively boosts LiDAR frame rates to 27.8-66 Hz via event-camera fusion and cuts depth RMSE by 29% on a new ELiDAR dataset.
-
Real2Sim: A Physics-driven and Editable Gaussian Splatting Framework for Autonomous Driving Scenes
Real2Sim reconstructs editable dynamic driving scenes as temporally continuous Gaussians integrated with a differentiable MPM physics solver for high-fidelity simulation of interactions and collisions.
-
Generating Roadside LiDAR Datasets from Vehicle-Side Datasets via Novel View Synthesis
VRS generates annotated roadside LiDAR data from vehicle observations via novel view synthesis with geometry completion and occupancy constraints, improving 3D object detection generalization.
-
Transferable Physical-World Adversarial Patches Against Object Detection in Autonomous Driving
AdvAD produces physical-world adversarial patches with improved transferability to unseen object detectors by multi-model optimization, adaptive balancing, and physical variation robustness.
-
ParkingScenes: A Structured Dataset for End-to-End Autonomous Parking in Simulation Scenes
ParkingScenes is a new multimodal dataset of 704 structured reverse and parallel parking episodes generated in CARLA with Hybrid A* and MPC trajectories, showing better model performance than unstructured simulation data.
-
Driving in Corner Case: A Real-World Adversarial Closed-Loop Evaluation Platform for End-to-End Autonomous Driving
A platform using flow matching for real-world image generation and an adversarial policy creates challenging corner cases to evaluate end-to-end autonomous driving models like UniAD and VAD, showing performance degradation.
-
Closed-Loop Hybrid Digital Twin Platform for Connected and Automated Vehicle Validation
A real-time hybrid digital twin platform couples high-fidelity CARLA-SUMO co-simulation with a physical CAV test site via V2X for closed-loop control and multi-scenario verification.
-
REAP: Reinforcement-Learning End-to-End Autonomous Parking with Gaussian Splatting Simulator for Real2Sim2Real Transfer
REAP trains an end-to-end SAC policy with behavior cloning and collision penalties inside a 3DGS Real2Sim simulator and transfers it to physical vehicles, succeeding in narrow mechanical parking slots.
-
From Sensing to Decision: A Generic Architecture for Freight Signal Priority Systems
A systematic review proposes a generic two-layer architecture for Freight Signal Priority systems that links sensing modalities to reliable priority decisions while accounting for detection and communication uncertainties.
-
Dynamic Risk Generation for Autonomous Driving: Naturalistic Reconstruction of Vehicle-E-Scooter Interactions
A simulation pipeline reconstructs real vehicle-e-scooter interactions and extends them to higher-risk scenarios using a Social Force Model to validate autonomous vehicle collision avoidance.
-
Dataset Safety in Autonomous Driving: Requirements, Risks, and Assurance
The paper introduces a safety framework for datasets in autonomous driving that uses the AI Data Flywheel and lifecycle processes to identify hazards and ensure compliance with ISO/PAS 8800.
- VaN3Twin: the Multi-Technology V2X Digital Twin with Ray-Tracing in the Loop