Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Abstract
Autonomous vehicles (AVs) are revolutionizing artificial intelligence, robotics, and transportation engineering. Able to understand their environment, make decisions, and navigate autonomously, these driver-less vehicles have the potential to revolutionize transportation by improving safety, reducing traffic accidents, and increasing accessibility for all groups. This research explores the underlying technologies that power driving, including computer vision, sensor fusion, machine learning, and complex navigation systems. It provides an in-depth review of simultaneous space and image reconstruction (SLAM), additive learning for adaptive decision making, and deep learning for object detection, showing how the technology works to achieve high levels of autonomy. The paper also explores the multilayered processes of AV systems, which include sensing, planning, and control of products. Each layer is defined by its function, relationship, and problems. The role of technologies such as lidar, radar, cameras, and ultrasonic sensors in providing better environmental perception is also examined. Innovations in maples navigation and flight planning are reviewed, highlighting advances in algorithms designed to manage complex urban environments. It also discusses the importance of vehicle-to-everything (V2X) communication in improving situational awareness of autonomous vehicles and supporting collaborative decision-making. Business issues such as the reliability of weather sensors, the limitations of real-time data processing, and vulnerabilities in cyber security are explored. The article also addresses social issues such as ethics, governance issues, and public acceptance. It examines the ethical implications of decision-making algorithms in situations involving unavoidable events, emphasizing the need for transparent and explanatory AI. This article also explores the challenges of establishing international standards and ensuring coordination of AV systems. From reducing deaths and emissions to changing the urban environment, the positive impact of energy-efficient vehicles is undeniable.
However, it will also include disruptions in transportation operations and changes in individual vehicle ownership. This study presents effective strategies such as rehabilitation and policies to ensure equitable access to AV technology to address these issues. It discusses emerging trends such as the use of quantum computing for optimization, faster decision-making, and the discovery of bio-inspired algorithms for navigation. Collaboration between government, academia, and the private sector is crucial to overcome current challenges and realize the full potential of AVs. Electric vehicles can solve social, ethical, and societal issues, leading to safer, more efficient, and more effective transportation.
Keywords:
Autonomous Vehicles (AVs) Cost-Effective Navigation Route Optimization Machine Learning (ML) Sensor Fusion Real-Time Data Processing Smart Mobility Path Planning Algorithms Edge Computing Low-Cost Sensors Traffic Prediction Visual SLAM AI in Transportation GPS-IMU Integration Intelligent Transportation Systems (ITS)
Cite Article:
"Autonomous Vehicle", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.c63-c72, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504231.pdf
Downloads:
000442
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator