Using a YOLO Deep Learning Algorithm to Improve the Accuracy of 3D Object Detection by Autonomous Vehicles DOI Creative Commons

Ramavhale Murendeni,

Alfred Mwanza, Ibidun Christiana Obagbuwa

et al.

World Electric Vehicle Journal, Journal Year: 2024, Volume and Issue: 16(1), P. 9 - 9

Published: Dec. 27, 2024

This study presents an adaptation of the YOLOv4 deep learning algorithm for 3D object detection, addressing a critical challenge in autonomous vehicle (AV) systems: accurate real-time perception surrounding environment three dimensions. Traditional 2D detection methods, while efficient, fall short providing depth and spatial information necessary safe navigation. research modifies architecture to predict bounding boxes, depth, orientation. Key contributions include introducing multi-task loss function that optimizes predictions integrating sensor fusion techniques combine RGB camera data with LIDAR point clouds improved estimation. The adapted model, tested on real-world datasets, demonstrates significant increase accuracy, achieving mean average precision (mAP) 85%, intersection over union (IoU) 78%, near performance at 93–97% detecting vehicles 75–91% people. approach balances high accuracy processing, making it highly suitable AV applications. advances field by showing how efficient detector can be extended meet complex demands driving scenarios without sacrificing computational efficiency.

Language: Английский

Sensor-Fusion Based Navigation for Autonomous Mobile Robot DOI Creative Commons
Vygantas Ušinskis, Michał Nowicki, Andrius Dzedzickis

et al.

Sensors, Journal Year: 2025, Volume and Issue: 25(4), P. 1248 - 1248

Published: Feb. 18, 2025

Navigation systems are developing rapidly; nevertheless, tasks becoming more complex, significantly increasing the number of challenges for robotic systems. can be separated into global and local navigation. While navigation works according to predefined data about environment, uses sensory dynamically react adjust trajectory. Tasks complex with addition dynamic obstacles, multiple robots, or, in some cases, inspection places that not physically reachable by humans. Cognitive require only detecting an object but also evaluating it without direct recognition. For this purpose, sensor fusion methods employed. However, sensors different physical nature sometimes cannot directly extract required information. As a result, AI increasingly popular acquired information controlling generating robot trajectories. In work, review mobile localization is presented comparing them listing advantages disadvantages their combinations. Also, integration path-planning looked into. Moreover, analyzed evaluated. Furthermore, concept channel navigation, designed based on research literature, presented. Lastly, discussion conclusions drawn.

Language: Английский

Citations

2
A systematic review and bibliometric analysis of electric cooking: evolution, emerging trends, and future research directions for sustainable development DOI Creative Commons
Flavio Odoi-Yorke

Sustainable Energy Research, Journal Year: 2024, Volume and Issue: 11(1)

Published: June 27, 2024

Abstract Many developing countries, particularly in Africa and Asia, still widely use traditional cooking methods that rely on solid fuels such as wood charcoal. These inefficient polluting practices have severe health impacts due to household air pollution, they contribute environmental degradation through deforestation black carbon emissions. This has driven growing interest cleaner more sustainable alternatives electric (e-cooking), improved biomass cookstoves, biogas systems, modern fuel stoves can reduce emissions consumption while providing a safer experience. E-cooking emerged promising option sustainability, benefits, energy efficiency, convenience, safety, potential for grid integration, making it alternative methods. study followed the PRISMA guidelines systematic reviews assess existing literature e-cooking from 1993 2023. In addition, biblioshiny package R software was used perform bibliometric analysis identify key trends evolutions. The results indicate United Kingdom, States, Japan, Australia, China are top five countries leading research. identified areas future research, optimising solar e-cookers using artificial intelligence techniques, integrating internet of things automation technologies e-cookers, appliances into smart examining effective behavioural change interventions, exploring innovative business models. findings highlight need interdisciplinary collaboration among researchers, engineers, social scientists, policymakers address technical, economic, socio-cultural, factors influencing transition e-cooking.

Language: Английский

Citations

13
Advanced Temporal Deep Learning Framework for Enhanced Predictive Modeling in Industrial Treatment Systems DOI Creative Commons

S Ramya,

S Srinath,

Pushpa Tuppad

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104158 - 104158

Published: Jan. 1, 2025

Language: Английский

Citations

1
Exploring the Unseen: A Survey of Multi-Sensor Fusion and the Role of Explainable AI (XAI) in Autonomous Vehicles DOI Creative Commons
De Jong Yeong, Krishna Panduru, J. L. Walsh

et al.

Sensors, Journal Year: 2025, Volume and Issue: 25(3), P. 856 - 856

Published: Jan. 31, 2025

Autonomous vehicles (AVs) rely heavily on multi-sensor fusion to perceive their environment and make critical, real-time decisions by integrating data from various sensors such as radar, cameras, Lidar, GPS. However, the complexity of these systems often leads a lack transparency, posing challenges in terms safety, accountability, public trust. This review investigates intersection explainable artificial intelligence (XAI), aiming address implementing accurate interpretable AV systems. We systematically cutting-edge techniques, along with explainability approaches, context While technologies have achieved significant advancement improving perception, transparency autonomous decision-making remains primary challenge. Our findings underscore necessity balanced approach XAI driving applications, acknowledging trade-offs between performance explainability. The key identified span range technical, social, ethical, regulatory aspects. conclude underscoring importance developing techniques that ensure explainability, specifically high-stakes stakeholders without compromising safety accuracy, well outlining future research directions aimed at bridging gap high-performance trustworthy

Language: Английский

Citations

1
Overview of emerging electronics technologies for artificial intelligence: A review DOI Creative Commons
Peng Gao, Muhammad Adnan

Materials Today Electronics, Journal Year: 2025, Volume and Issue: unknown, P. 100136 - 100136

Published: Jan. 1, 2025

Language: Английский

Citations

0
Cognitive strategies for UAV trajectory optimization: Ensuring safety and energy efficiency in real-world scenarios DOI Creative Commons
Muhammad Umer Mushtaq, Hein S. Venter, Muhammad Owais

et al.

Ain Shams Engineering Journal, Journal Year: 2025, Volume and Issue: 16(3), P. 103301 - 103301

Published: Feb. 6, 2025

Language: Английский

Citations

0
Influencing Factors on Drivers’ Satisfaction Towards Automated Vehicle with Different Levels of Automation: Incorporating Intentions to Repurchase and Recommend DOI
Jingyu Li, Weihua Zhang,

Zhongxiang Feng

et al.

International Journal of Human-Computer Interaction, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 15

Published: March 27, 2025

Language: Английский

Citations

0
A Review of Off-Road Datasets, Sensor Technologies and Terrain Traversability Analysis DOI

Hannah Musau,

Denis Ruganuza,

Debbie Indah

et al.

SAE technical papers on CD-ROM/SAE technical paper series, Journal Year: 2025, Volume and Issue: 1

Published: April 1, 2025

<div class="section abstract"><div class="htmlview paragraph">Autonomous ground navigation has advanced significantly in urban and structured environments, supported by the availability of comprehensive datasets. However, navigating complex off-road terrains remains challenging due to limited datasets, diverse terrain types, adverse environmental conditions, sensor limitations affecting vehicle perception. This study presents a review integrating their applications with technologies traversability analysis methods. It identifies critical gaps, including class imbalances, performance under existing estimation approaches. Key contributions include novel classification datasets based on annotation methods, providing insights into scalability applicability across terrains. The also evaluates conditions proposes strategies for incorporating event-based hyperspectral cameras enhance perception systems. Additionally, we address lack unified evaluation metrics introducing qualifiers assessing perception, planning, control Finally, comparison geometry-based, learning-based, probabilistic methods navigability prediction highlights importance multi-sensor data integration improved decision-making. These actionable recommendations aim guide development adaptive robust autonomous systems, advancing real-world environments.</div></div>

Language: Английский

Citations

0
Research Status and Thinking of Intelligent Level Evaluation of Unmanned Equipment DOI
Hongbo Tang, Yu Jiang

Lecture notes in electrical engineering, Journal Year: 2025, Volume and Issue: unknown, P. 160 - 169

Published: Jan. 1, 2025

Language: Английский

Citations

0
LiDAR Innovations: Insights from a Patent and Scientometric Analysis DOI Creative Commons
Raj Bridgelall

Designs, Journal Year: 2025, Volume and Issue: 9(2), P. 47 - 47

Published: April 11, 2025

Light detection and ranging (LiDAR) sensors are critical for autonomous vehicles that require unparalleled depth sensing. However, traditional LiDAR designs face significant challenges, including high costs bulky configurations, limiting scalability mass-market adoption. By uniquely combining patent scientometric analysis, this study screened 188 recent patents from a dataset of more than two million patents, uncovering strategies to enhance capability reduce production costs. The key findings highlight the growing emphasis on solid-state architectures, modular designs, integrated manufacturing processes as pathways scalable efficient solutions. These insights bridge gap between scientific advancements practical implementation, providing stakeholders with clear understanding technological landscape emerging trends. identifying future directions actionable opportunities, work supports development next-generation systems, fostering innovation enabling broader adoption across other sectors.

Language: Английский

Citations

0