Relevant bibliographies by topics / AI-driven collision avoidance

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  1. Journal articles
  2. Book chapters
  3. Conference papers

Academic literature on the topic 'AI-driven collision avoidance'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "AI-driven collision avoidance"

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Sharma,, Siddharth. "Revolutionizing Sports Bikes with Artificial Intelligence: Safety, Performance, and Design Innovations." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem30618.

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This study examines how artificial intelligence (AI) is incorporated into sports bikes and examines the significant impacts this has on ride quality, user experience, and safety. Adaptive cruise control and collision avoidance systems, two AI-driven technologies that improve rider safety, and engine performance improvements and predictive maintenance algorithms that improve overall bike performance and dependability. Furthermore, bike design processes are revolutionized by AI-driven design techniques, which allow for quick iterations and customisation. This study offers insights into how artif
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Sharma1, Nikhil. "The Future of Computing: Microprocessor Advancements in 2024." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem30690.

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In 2024, the microprocessor landscape witnessed a revolutionary shift, marked by cutting-edge advancements and transformative trends across various industries. The relentless pursuit of Moore's Law drove innovation, leading to the creation of highly efficient processors through state-of-the-art fabrication technologies. Embracing sub-3nm processes, semiconductor manufacturers enhanced performance metrics while reducing power consumption. The rise of heterogeneous computing architectures and specialized edge processors tailored for decentralized environments further diversified the microprocess
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Pawan, Sahu, and Kore Sushma. "Enhancements in CSMA/CD and CSMA/CA for Collision Handling in Ethernet and Wi-Fi Networks." Journal of Network Security and Data Mining 8, no. 2 (2025): 24–30. https://doi.org/10.5281/zenodo.15356719.

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<em>Carrier Sense Multiple Access with Collision Detection (CSMA/CD) and Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) are fundamental access control mechanisms used in Ethernet and Wi-Fi networks, respectively. However, as network traffic grows and devices become more interconnected, traditional implementations of these protocols encounter inefficiencies, leading to increased collision rates, network congestion, and higher transmission delays. This paper explores recent advancements in CSMA/CD and CSMA/CA aimed at improving collision handling, reducing packet loss, and opti
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Needhi, Jeyadev. "Advanced Object Detection and Decision Making in Autonomous Medical Response Systems." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–13. http://dx.doi.org/10.55041/ijsrem35985.

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Abstract—This paper focuses on enhancing the object detection and decision-making capabilities of Autonomous Emergency Medical Response Systems (AEMRS). Using advanced sensors, Convolutional Neural Networks (CNN), and reinforcement learn- ing, we propose a model that processes environmental data to identify obstacles and make optimal navigation decisions. The integration of these technologies aims to minimize response time and improve the efficiency of emergency medical services. The perception system utilizes radar, LiDAR, and camera inputs to create a comprehensive understanding of the envir
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Dr. Yogesh Suryawanshi. "Motion Capture Autonomous Drone." Journal of Information Systems Engineering and Management 10, no. 29s (2025): 929–33. https://doi.org/10.52783/jisem.v10i29s.4605.

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Introduction: Motion capture technology is vital in industries like sports biomechanics, cinema, Robotics traditional system rely on fixed cameras limited flexibility in dynamic outdoor environments autonomous rule equipped with AI and computer vision of announced mobility, real time tracking of moving subject across diversity. Drones enable resize performing analysis in sports and dynamic film without need for complex setup all the challenges like environmental conditions and hardware limitation remains research in sensor fusion and optimization is improving reliability Drone represent a majo
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Mahmud, Md Sultan, Proches Nolasco Mkawe, and Vicent Opiyo Nyagilo. "A COMPREHENSIVE ANALYSIS OF NON-PLANAR TOOLPATH OPTIMIZATION IN MULTI-AXIS 3D PRINTING: EVALUATING THE EFFICIENCY OF CURVED LAYER SLICING STRATEGIES." Review of Applied Science and Technology 04, no. 02 (2025): 274–308. https://doi.org/10.63125/5fdxa722.

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Non-planar toolpath optimization has emerged as a pivotal advancement in multi-axis additive manufacturing, offering transformative potential for overcoming the limitations of traditional layer-by-layer 3D printing. This comprehensive analysis investigates the current state-of-the-art in non-planar toolpath generation and curved layer slicing strategies, focusing on their efficacy in enhancing surface finish, structural integrity, and overall print efficiency. In Asia, Japanese and South Korean industries have rapidly adopted 5-axis AM systems for high-precision mold and die fabrication, lever
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BOLAJI-ADETORO, D. F, IBRAHIM SHOLA ISMAIL, K. J. ADEDOTUN, and A. K. RAJI. "REAL-TIME OBJECT DETECTION AND COLLISION AVOIDANCE IN IOT-ENABLED AUTONOMOUS VEHICLES." Harvard International Journal of Engineering Research and Technology, March 31, 2025. https://doi.org/10.70382/hijert.v07i5.001.

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The growing demand for autonomous vehicles (AVs) has fueled extensive research in real-time object detection and collision avoidance, with IoT-enabled technologies playing a vital role in ensuring safe navigation. This study examines the integration of IoT-based sensor networks, artificial intelligence (AI), and edge computing to enhance AV perception and decision-making in dynamic environments. Key sensor technologies, including LiDAR, radar, ultrasonic sensors, and cameras, are analyzed for their effectiveness in detecting and classifying pedestrians, vehicles, and obstacles in real time. AI
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Medany, Mahmoud, Lorenzo Piglia, Liam Achenbach, S. Karthik Mukkavilli, and Daniel Ahmed. "Model-based reinforcement learning for ultrasound-driven autonomous microrobots." Nature Machine Intelligence, June 26, 2025. https://doi.org/10.1038/s42256-025-01054-2.

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Abstract Reinforcement learning is emerging as a powerful tool for microrobots control, as it enables autonomous navigation in environments where classical control approaches fall short. However, applying reinforcement learning to microrobotics is difficult due to the need for large training datasets, the slow convergence in physical systems and poor generalizability across environments. These challenges are amplified in ultrasound-actuated microrobots, which require rapid, precise adjustments in high-dimensional action space, which are often too complex for human operators. Addressing these c
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Book chapters on the topic "AI-driven collision avoidance"

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Krishnamurthy, Vignesh, Paramesh G, and Shinu Abhi. "Fuel Efficient Self-Driven Vehicle using CNN with V2V Communication." In Applied Intelligence and Computing. Soft Computing Research Society, 2024. https://doi.org/10.56155/978-81-955020-9-7-22.

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In today’s Artificial Intelligence (AI) -driven era, transportation is being revolutionized through AI and computer vision technologies, utilizing cameras, ultrasonic sensors for detecting obstacles, GPS for pinpointing locations, and ADXL345 for directional guidance. The objective is to improve vehicle safety and fuel economy by applying Machine Learning (ML) techniques, using resources like the Carla Driving Simulator’s Lane Detection data and Vehicle-to-Vehicle (V2V) communication. Raspberry Pi and Arduino are employed for computational tasks, allowing for AI-based forecasts using models su
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Conference papers on the topic "AI-driven collision avoidance"

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Ghosh, Prof Ankush. "AI driven Sustainability for Autonomous Driving." In 3rd World Conference on Engineering, Technology and Applied Science. Eurasia Conferences, 2024. https://doi.org/10.62422/978-81-974314-7-0-002.

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Self-driving technology is poised to revolutionize transportation infrastructure globally, offering a unique opportunity to enhance the quality of life. As urban areas face challenges such as rapid growth, avoidable collisions, vehicle emissions, and congestion from single-occupant commuters, autonomous vehicles promise to transform transportation systems by delivering significant environmental, social, and economic benefits. However, autonomous ground vehicles (AGVs) must overcome various challenges to navigate safely from origin to destination. In this lecture, we will explore these challeng
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Solus, Jacob, Maureen Rakotondraibe, Xinrui Yu, Won-Jae Yi, Mikhail Gromov, and Jafar Saniie. "IoT-Enabled Smart Bike Helmet with an AI-Driven Collision Avoidance System." In 2023 IEEE International Conference on Electro Information Technology (eIT). IEEE, 2023. http://dx.doi.org/10.1109/eit57321.2023.10187299.

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Rohini, M., T. Praneeth, T. Sivareddy, and A. Tamilselvan. "A Novel Approach to Vehicular Safety: Raspberry Pi-based Collision Avoidance and Connectivity in Smart Automobiles Leveraging AI-driven Sensor Fusion." In 2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS). IEEE, 2023. http://dx.doi.org/10.1109/icacrs58579.2023.10404175.

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Ziakkas, Dimitrios, and Debra Henneberry. "The Role of Human Factors in the Certification of eVTOLs in the Artificial Intelligence (AI) Era." In 16th International Conference on Applied Human Factors and Ergonomics (AHFE 2025). AHFE International, 2025. https://doi.org/10.54941/ahfe1006504.

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The emergence of electric Vertical Take-Off and Landing (eVTOL) aircraft represents a paradigm shift in urban air mobility, promising safer, more efficient, and environmentally sustainable transportation. As the eVTOL industry progresses toward commercial deployment, certification processes have become a critical bottleneck, especially as they integrate advanced technologies such as Artificial Intelligence (AI). While the focus often lies on the technical and operational aspects of eVTOL certification, human factors play an equally vital role in ensuring safety, reliability, and public accepta
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