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All Journal Control Systems and Optimization Letters
Alam, Shahin
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Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Review on the Safety and Sustainability of Autonomous Vehicles: Challenges and Future Directions Uzzaman, Asif; Adam, Md Ibrahim; Alam, Shahin; Basak, Pallab
Control Systems and Optimization Letters Vol 3, No 1 (2025)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v3i1.185

Abstract

Autonomous vehicles (AVs) represent a major advancement in transportation technology, offering significant benefits such as enhanced road safety, reduced traffic congestion, and improved mobility. However, the widespread deployment of AVs faces key obstacles, including sensor limitations under adverse weather conditions, ethical decision-making in complex scenarios, regulatory challenges, and data privacy concerns. This paper examines these challenges and proposes potential solutions. Key challenges include improving sensor fusion and AI algorithms to enhance perception and decision-making, developing standardized ethical guidelines for autonomous systems, and establishing consistent legal and regulatory standards across regions. Additionally, ensuring cybersecurity and addressing data privacy issues are critical for maintaining the safety and trust of AV users. The future of AVs also depends on advancements in infrastructure, such as the development of smart roads and Vehicle-to-Everything (V2X) communication systems, as well as reducing production costs to increase accessibility. Furthermore, raising public awareness and fostering acceptance through education and transparent communication about AV benefits is vital. The paper concludes that with ongoing research, innovation, and collaboration, AVs have the potential to revolutionize transportation, offering a safer, more efficient, and sustainable future for mobility.
Next-Generation 3D Vision and Robotic Integration Technologies for Commercial Vehicle Manufacturing Islam, Md Nazmul; Aihua, Ren; Isyaku, Muhammad; Boa, Benfor Nana; Alam, Shahin
Control Systems and Optimization Letters Vol 4, No 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v4i1.284

Abstract

This research project explores the development of 3D machine vision and robot integration technology tailored for commercial vehicle manufacturing and testing. As the industry increasingly demands higher efficiency and quality, the integration of advanced machine vision systems with robotic automation presents a transformative solution. Advanced robotics technologies involve the latest advances in robotics, including integrating sophisticated control systems, sensors, data fusion techniques, and machine learning algorithms. These innovations enable robots to adapt better and interact with their environment, ultimately increasing their accuracy. The main focus of this study is to cover the most common industrial robotic machining processes and to identify how specific advanced technologies can improve their performance. In most of the studied literature, the primary research objective across all operations is to enhance the stiffness of the robotic arm’s structure. This study investigates the implementation of 3D machine vision for precise component inspection, guided assembly, and real-time process adaptation. Key challenges, including high initial costs and complexity of integration, are addressed alongside potential benefits such as improved product quality and reduced operational costs. By leveraging cutting-edge technologies, this research aims to enhance manufacturing processes, ultimately contributing to the advancement of intelligent manufacturing in the commercial vehicle sector. The findings will provide valuable insights for manufacturers seeking to optimize their production capabilities and maintain competitiveness in a rapidly evolving market.
Co-Authors Adam, Md Ibrahim Aihua, Ren Basak, Pallab Boa, Benfor Nana Islam, MD Nazmul Isyaku, Muhammad Uzzaman, Asif