Abu Jafar Md Muzahid
Papers
1
Total Citations
17
H-Index
1
About
Abu Jafar Md Muzahid is a rising researcher in the field of autonomous vehicle safety, with a focused expertise in threat assessment and collision avoidance systems. His most cited work, "Learning-Based Conceptual Framework for Threat Assessment of Multiple Vehicle Collision in Autonomous Driving" (2020), has garnered 17 citations, establishing a foundation for intelligent safety protocols in self-driving technology. Muzahid’s major contribution lies in addressing the critical challenge of unexpected lane changes—a leading cause of traffic accidents—by developing a conceptual framework that leverages machine learning to evaluate collision risks in multi-vehicle scenarios. This work bridges the gap between theoretical safety models and practical autonomous driving systems, offering a proactive approach to accident prevention. His research underscores the growing importance of safety assurance as autonomous driving advances, and his framework provides a roadmap for integrating threat assessment into real-time decision-making. Muzahid’s achievements highlight his role in shaping safer, more reliable autonomous systems, making his work essential reading for students and researchers exploring the intersection of AI, vehicular safety, and intelligent transportation.
Research Focus
Key Achievements
Top Papers
- 1