Aeronáutica y espacio

ReactSim-Bench: Benchmarking Reactive Behavior World Model Simulation in Autonomous Driving

- Reactive capability is a key property of data-driven behavior world model simulators for autonomous driving simulation systems. With this capability, simulated world agents can respond feasibly to...

From Attacks to Curricula: Learnability-Guided Adversarial Training for Safe Autonomous Driving

- Closed-loop adversarial training improves autonomous driving safety by exposing policies to rare safety-critical scenarios. Standard pipelines first generate adversarial scenarios and then sample...

RT-VLA: Real-Time Vision-Language-Action Models via Knowledge Distillation

- Vision-Language-Action (VLA) models have shown strong potential for end-to-end autonomous driving by jointly modeling visual perception, language reasoning, explainability and action prediction....

Multi-Agent Embodied Autonomous Driving: From V2X Information Exchange to Shared World Models

- Autonomous driving is shifting from isolated vehicle intelligence toward multi-agent embodied systems that share perception, infer intent, and coordinate action under uncertainty. This survey...

QueryOcc: Query-based Self-Supervision for 3D Semantic Occupancy

- Learning 3D scene geometry and semantics from images is a core challenge in computer vision and a key capability for autonomous driving. Since large-scale 3D annotation is prohibitively expensive,...

Miniature Testbed for Validating Multi-Agent Cooperative Autonomous Driving

- Cooperative autonomous driving, which extends vehicle autonomy by enabling real-time collaboration between vehicles and smart roadside infrastructure, remains a challenging yet essential problem....

VISA: VLM-Guided Instance Semantic Auditing for 3D Occupancy World Models

- Semantic 3D occupancy provides a voxelized world state for autonomous driving and robot decision making, but object and rare-class errors can affect free-space interpretation, collision checking, and...

DIMOS: Disentangling Instance-level Moving Object Segmentation

- Moving instance segmentation (MIS) attracts increasing attention due to its broad applications in traffic surveillance, autonomous driving, and animal tracking. Event cameras record asynchronous...

Agentic MPC for Semantic Control System Resynthesis

- While MPC effectively handles structured, diverse, and low-level specifications, it lacks the capability to dynamically incorporate high-level contextual information such as social norms, user...

A Tutorial on World Models and Physical AI

- World modeling is emerging as a central principle for building intelligent systems capable of prediction, reasoning, and decision making. A central distinction can be drawn between explicit world...

VLADriveBench: Evaluating CoT-Action Relationship in VLA for Autonomous Driving

- Vision-language-action (VLA) models generate chain-of-thought (CoT) reasoning alongside driving trajectories, but existing benchmarks evaluate only trajectory quality and do not assess whether the...

Context-Aware Feature-Fusion for Co-occurring Object Detection in Autonomous Driving

- Object detection in autonomous driving requires precise localization and an inherent understanding of the relational context between co-occurring objects. In extremely complex heterogeneous...

From Imitation to Alignment: Human-Preference Flow Policies for Long-Horizon Sidewalk Navigation

- Autonomous long-horizon sidewalk navigation is essential for micro-mobility applications such as robotic food delivery and assistive electronic wheelchairs. Unlike autonomous driving on the road,...

VLGA: Vision-Language-Geometry-Action Models for Autonomous Driving

- Vision-language-action (VLA) models can describe scenes and reason about them in language, yet still struggle to ground their actions in the dense 3D world around them. Existing approaches either...

DrivingAgent: Design and Scheduling Agents for Autonomous Driving Systems

- Many autonomous driving systems are increasingly incorporating foundation models to improve generalization and handle long-tail scenarios. However, this trend introduces two key challenges: (i) the...

Intelligent Automation for Embodied Benchmark Construction: Pipelines, Embodiments, Simulators, and Trends

- Embodied intelligence now spans navigation, household assistance, manipulation, autonomous driving, aerial agents, and multimodal large-model control. This expansion has made benchmark construction a...

Performance Analysis of YOLOv11 and YOLOv8 for Mixed Traffic Object Detection under Adverse Weather Conditions in Developing Countries

- In modern vehicular systems, robust performance under harsh conditions has become a critical problem of autonomous driving. Our study delivers a comprehensive evaluation of the newest iteration of...

AutoMine Solution for AV2 2026 Scenario Mining Challenge

- With the development of autonomous driving systems, mining high-value, safety-critical, and planning-relevant scenarios from large-scale driving logs has become essential for data-driven evaluation....

Task-Aligned Stability Analysis of Vision-Language Models for Autonomous Driving Hazard Detection

- Vision-language models (VLMs) are increasingly used for scene understanding in autonomous driving, but robustness analysis often relies on task-agnostic embedding stability alone. We study whether...

Systematic Cybersecurity Risk Analysis of European Rail Traffic Management System

- European Rail Traffic Management System (ERTMS) is a widely adopted standard unifying train management in the EU. While the standard allows for use cases like fully autonomous driving, cybersecurity...

ConsistencyPlanner: Real-time Planning with Fast-Sampling Consistency Models

- Closed-loop planning in complex, real-world driving scenarios presents a critical challenge for autonomous driving systems. While traditional rule-based methods are interpretable, their predefined...