Doctoral Candidate Name: 
Raghuveer Gouribhatla
Infrastructure and Environmental Systems

Driver errors are the leading cause and contribute to about 94% of traffic crashes. To mitigate this issue, improve mobility, and enhance safety, automobile manufacturers are striving to develop various types of advanced driver assistance systems (ADAS). These ADAS are designed to assist or in some cases take over certain driving maneuvers. On the other hand, the acceptance levels of ADAS among drivers are questionable. Many surveys determined that drivers are unaware of the applications and limitations of ADAS. While ADAS are designed to enhance safer driving, their indirect effects on driver behavior have been seldom ventured and widely debated.

The focus of this research is on developing different driving scenarios that replicate real-world driving conditions using a driving simulator. Selected participants were prompted to interact with traffic within the simulation environment through a setup equipped with warning (lane departure warning, blind-spot warning, and over speed warning) or automated (lane keep assist and adaptive cruise control) features. The responses of participants when driving a vehicle with warning features, advanced features, and without ADAS in the simulation were captured, analyzed, and compared to understand their effects. The findings are valuable insights to automobile manufacturers as well as policymakers to better design ADAS such that their applicability is streamlined from both safety and user perspective.

Defense Date and Time: 
Wednesday, April 13, 2022 - 2:00pm
Defense Location: 
EPIC 3344
Committee Chair's Name: 
Dr. Srinivas Pulugurtha
Committee Members: 
Dr. Martin Kane, Dr. Rajaram Janardhanam, Dr. Churlzu Lim, Dr. Ram Kumar