Ardashir Bulsara
Papers
2
Total Citations
24
H-Index
2
About
Ardashir Bulsara is a researcher whose work centers on autonomous vehicle systems, with a particular focus on control algorithms, simulation frameworks, and real-world validation methodologies. His most cited contribution, "Obstacle Avoidance Using Model Predictive Control: An Implementation and Validation Study Using Scaled Vehicles" (2020, 15 citations), demonstrates his practical approach to advancing autonomous driving technology by implementing and validating model predictive control strategies for obstacle avoidance using scaled vehicle platforms — a cost-effective yet rigorous testing methodology. This work addresses critical challenges in adaptive cruise control, lane keeping, and autonomous navigation that have defined the field over the past decade. Complementing this, his paper on "Integration of Autonomous Vehicle Frameworks for Software-in-the-Loop Testing" (2020, 9 citations) highlights his commitment to robust software validation pipelines, specifically leveraging the open-source Autoware framework to enable reliable pre-deployment testing of autonomous driving systems. Together, these works reflect Bulsara's emphasis on bridging the gap between theoretical autonomous vehicle algorithms and practical, testable implementations. His research is particularly valuable for engineers and students seeking scalable, validated approaches to autonomous systems development, and his contributions have garnered growing attention within the automotive and robotics research communities.
Research Focus
Key Achievements
Top Papers
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