[HTML][HTML] Autonomous driving architectures: insights of machine learning and deep learning algorithms

MR Bachute, JM Subhedar - Machine Learning with Applications, 2021 - Elsevier
Abstract Research in Autonomous Driving is taking momentum due to the inherent
advantages of autonomous driving systems. The main advantage being the disassociation …

Deep reinforcement learning techniques for vehicular networks: Recent advances and future trends towards 6G

A Mekrache, A Bradai, E Moulay, S Dawaliby - Vehicular Communications, 2022 - Elsevier
Employing machine learning into 6G vehicular networks to support vehicular application
services is being widely studied and a hot topic for the latest research works in the literature …

A measurement scheduling method for multi-vehicle cooperative localization considering state correlation

H Min, Y Li, X Wu, W Wang, L Chen, X Zhao - Vehicular Communications, 2023 - Elsevier
Accurate and robust localization is a fundamental requirement for safe autonomous driving.
Currently, most vehicles rely on single-vehicle localization (SVL) using the global navigation …

[HTML][HTML] Metaverse integration alternatives of connected autonomous vehicles with self-powered sensors using fuzzy decision making model

I Gokasar, D Pamucar, M Deveci, BB Gupta… - Information …, 2023 - Elsevier
Using self-powered sensors, traffic data may be collected continuously, efficiently, and
sustainably once connected autonomous vehicles (CAVs) are a part of metaverse …

Social network multiple-criteria decision-making approach for evaluating unmanned ground delivery vehicles under the Pythagorean fuzzy environment

S Zeng, N Zhang, C Zhang, W Su, LA Carlos - … Forecasting and Social …, 2022 - Elsevier
With the rapid development of instant delivery, the shrinking labor population and prevailing
contact-free economy, companies have launched unmanned ground delivery vehicles …

Stability and safety evaluation of mixed traffic flow with connected automated vehicles on expressways

Z Yao, R Hu, Y Jiang, T Xu - Journal of Safety Research, 2020 - Elsevier
Abstract Introduction: Connected automated vehicles (CAVs) technology has deeply
integrated advanced technologies in various fields, providing an effective way to improve …

Integrity monitoring of GNSS/INS based positioning systems for autonomous vehicles: State-of-the-art and open challenges

H **g, Y Gao, S Shahbeigi… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Positioning and navigation are critical functions of automated driving functions, which help
autonomous vehicles determine their absolute and relative positions in the environment that …

[HTML][HTML] State of data platforms for connected vehicles and infrastructures

KL Lim, J Whitehead, D Jia, Z Zheng - Communications in transportation …, 2021 - Elsevier
The continuing expansion of connected and electro-mobility products and services has led
to their ability to rapidly generate very large amounts of data, leading to a demand for …

GNSS vulnerabilities and existing solutions: A review of the literature

J Zidan, EI Adegoke, E Kampert, SA Birrell… - IEEE …, 2020 - ieeexplore.ieee.org
This literature review paper focuses on existing vulnerabilities associated with global
navigation satellite systems (GNSSs). With respect to the civilian/non encrypted GNSSs, they …

A systematic literature review of the factors influencing the adoption of autonomous driving

M Alawadhi, J Almazrouie, M Kamil… - International Journal of …, 2020 - Springer
Autonomous vehicles (AVs) are the latest trend in the automobile industry. Although the
concept has existed since the beginning of the last century, recent technological …