Neil Sawant
Papers
1
Total Citations
5
H-Index
1
About
Neil Sawant is a researcher in intelligent transportation systems, with a focus on enhancing the reliability and safety of automated vehicles. His work centers on fault detection algorithms, using real experimental data to identify unstable conditions that could compromise autonomous driving. Sawant’s most cited paper, “A framework of fault detection algorithm for intelligent vehicle by using real experimental data” (2011), proposes a systematic approach to diagnosing system failures, contributing to the broader goal of making self-driving cars more robust and trustworthy. With 5 citations, this study has informed subsequent research on vehicle safety and control systems. While his citation count reflects a niche but impactful contribution, Sawant’s work is notable for bridging theoretical fault detection with practical, data-driven validation. His research underscores the critical need for high reliability in automated vehicles to unlock their potential for safer, more efficient transportation. For students and researchers in autonomous systems, Sawant’s framework offers a foundational step toward building resilient intelligent vehicles.
Research Focus
Key Achievements
Top Papers
- 1