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.
This paper presents an emotion-based autonomous driving control system that integrates real-time physiological monitoring with autonomous vehicle technology to enhance driving safety and personalization.
Engineering 5.0 · Research 7.0 · Business 5.0
Abstract Ride-hailing services, characterized by convenience, flexibility, and on-demand availability, have substantially reshaped urban mobility patterns, posing uncertain impacts on subway ridership.
Engineering 5.0 · Research 7.0 · Business 5.0
This study conducted a systematic self-review of 30 studies published by the author between 2004 and 2025 on Arabic–English language dynamics.
Engineering 5.0 · Research 7.0 · Business 5.0
Artificial Intelligence (AI) and Machine Learning (ML) are transforming learning environments by enabling personalized, adaptive, and intelligent educational systems.
Engineering 5.0 · Research 7.0 · Business 5.0
This study investigates the integrated application of Bluetooth smart speakers within the Internet of Things (IoT) and cross-border e-commerce, alongside strategies to optimize consumer experiences.
Engineering 5.0 · Research 7.0 · Business 5.0
There has been emerging empirical evidence supporting the role of artificial intelligence (AI) knowledge in public support for AI.
Engineering 5.0 · Research 7.0 · Business 5.0
An autonomous driving research paper: Federated deep reinforcement learning for privacy-preserving offloading in vehicular edge computing.
Engineering 5.0 · Research 8.0 · Business 5.0
We demonstrate that our model explains a wide range of empirical findings on human collision avoidance behavior.
Engineering 5.0 · Research 7.0 · Business 5.0
An autonomous driving research paper: Seeing is Deceiving: Systematic Vulnerability Analysis of LiDAR-Based Autonomous Driving to Mirror-Induced Perception Failures.
Engineering 5.0 · Research 7.0 · Business 5.0
Level-4+ autonomous driving systems (ADS) must run dozens of heterogeneous deep neural networks (DNNs) as end-to-end (E2E) pipelines under a strict latency constraint (<=100 ms), even as execution time varies by up to 3.3x.
Engineering 5.5 · Research 7.0 · Business 5.0
Mining hard, safety-critical scenes from driving logs is bottlenecked by the absence of difficulty labels, and no single proxy, collision risk, trajectory ambiguity, or semantic rarity suffices to find such scenes on its own.
Engineering 6.5 · Research 7.0 · Business 5.0
While end-to-end (E2E) autonomous driving has become the dominant research direction, production vehicles continue to rely on modular multi-NN pipelines for a non-trivial transitional period.
Engineering 5.5 · Research 7.0 · Business 6.0
Mimicking the human eye's ability to autonomously adapt to diverse and mixed illumination conditions remains a fundamental challenge in artificial vision systems.
Engineering 5.0 · Research 7.0 · Business 5.0
Here, we introduce the Neighborhood Errand Task (NET), a novel navigation paradigm designed to approximate memory and information processing during wayfinding within disordered neighborhood contexts.
Engineering 5.0 · Research 8.0 · Business 5.0
This chapter confronts the alluring promise of Artificial Intelligence (AI) in geographical Work-Integrated Learning (WIL) with the stark reality of its potential to perpetuate and deepen existing socio-spatial inequalities.
Engineering 5.0 · Research 7.0 · Business 5.0
This paper presents a systematic synthesis of the multi-dimensional barriers inhibiting the universal diffusion of Electric Vehicles (EVs).
Engineering 5.0 · Research 7.0 · Business 5.0
Multimodal 3D object detection based on LiDAR and cameras has demonstrated excellent performance in ground-vehicle scenarios, but has not been explored for Unmanned Aerial Vehicle (UAV) platforms.
Engineering 5.0 · Research 7.0 · Business 5.0
In this paper, we introduce SyVLA, a robust VLA model trained with diversified experiences.
Engineering 7.0 · Research 7.0 · Business 6.5
Within this framework, we propose three efficient minimal solvers specifically designed for autonomous vehicles.
Engineering 5.0 · Research 8.0 · Business 5.0
To bridge this gap, we introduce \textbf{MAVIS}, a novel multi-agent framework that rethinks retrieval as cooperative reasoning rather than brute-force search.
Engineering 5.0 · Research 8.0 · Business 5.0