[HTML][HTML] Electric vehicles: Battery technologies, charging standards, AI communications, challenges, and future directions
Electric vehicles (EVs) have gained significant attention in recent years due to their potential
to reduce greenhouse gas emissions and improve energy efficiency. An EV's main source of …
to reduce greenhouse gas emissions and improve energy efficiency. An EV's main source of …
Drivelm: Driving with graph visual question answering
We study how vision-language models (VLMs) trained on web-scale data can be integrated
into end-to-end driving systems to boost generalization and enable interactivity with human …
into end-to-end driving systems to boost generalization and enable interactivity with human …
A survey on multimodal large language models for autonomous driving
With the emergence of Large Language Models (LLMs) and Vision Foundation Models
(VFMs), multimodal AI systems benefiting from large models have the potential to equally …
(VFMs), multimodal AI systems benefiting from large models have the potential to equally …
A Survey on Recent Advancements in Autonomous Driving Using Deep Reinforcement Learning: Applications, Challenges, and Solutions
R Zhao, Y Li, Y Fan, F Gao… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Autonomous driving (AD) endows vehicles with the capability to drive partly or entirely
without human intervention. AD agents generate driving policies based on online perception …
without human intervention. AD agents generate driving policies based on online perception …
Towards knowledge-driven autonomous driving
This paper explores the emerging knowledge-driven autonomous driving technologies. Our
investigation highlights the limitations of current autonomous driving systems, in particular …
investigation highlights the limitations of current autonomous driving systems, in particular …
Agentscodriver: Large language model empowered collaborative driving with lifelong learning
Connected and autonomous driving is developing rapidly in recent years. However, current
autonomous driving systems, which are primarily based on data-driven approaches, exhibit …
autonomous driving systems, which are primarily based on data-driven approaches, exhibit …
Radar odometry for autonomous ground vehicles: A survey of methods and datasets
NJ Abu-Alrub, NA Rawashdeh - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Radar odometry has been gaining attention in the last decade. It stands as one of the best
solutions for robotic state estimation in unfavorable conditions; conditions where other …
solutions for robotic state estimation in unfavorable conditions; conditions where other …
[HTML][HTML] Automating construction of road digital twin geometry using context and location aware segmentation
Abstract Geometric Digital Twins (GDT) represent a critical advancement in road
management, yet their practical implementation encounters a substantial obstacle due to …
management, yet their practical implementation encounters a substantial obstacle due to …
An IoT-based deep-learning architecture to secure automated electric vehicles against cyberattacks and data loss
In the realm of modern transportation, automated electric vehicles (AEVs) assume a seminal
role in realizing the vision of intelligent and electrified mobility. The advancement of AEVs …
role in realizing the vision of intelligent and electrified mobility. The advancement of AEVs …
RLFN-VRA: Reinforcement Learning-based Flexible Numerology V2V Resource Allocation for 5G NR V2X Networks
C Chen, W Wang, Z Liu, Z Wang, C Li… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
With the advancement of 5G technology, the second generation of New Radio Vehicle-to-
Everything (NR V2X) based on 5G NR has been developed. NR V2X incorporates the high …
Everything (NR V2X) based on 5G NR has been developed. NR V2X incorporates the high …