Jaydeep Radadiya, an undergraduate in the Mechanical and Industrial Engineering (MIE) Department, was one of two College of Engineering undergraduate students chosen to be “Rising Researchers,” as designated by the UMass website Research Next. The award recognizes exceptional accomplishments of UMass Amherst undergraduate students who excel in research, scholarship, and creative activity. The other Rising Researcher from engineering was Chemical Engineering major Joshua McGee, covered in a separate article.
According to Professor Anuj Pradhan, Radadiya’s faculty research advisor, “He has played a pivotal role in my research on the safety of automated vehicles, and he has undertaken significant efforts and displayed great leadership in examining vehicle automation systems to characterize functionality, capabilities, and limitations.”
As Radadiya told Research Next, he is an undergraduate research assistant with the Pradhan Research Group in the MIE department.
“In that role,” said Radadiya, “I conduct human factors research in the field of automated vehicles in the Human Performance Laboratory. Our research is aimed towards understanding driver safety and vehicle automation, specifically to help mitigate vehicle crashes and injuries while operating Advanced Driver Assistance Systems (ADAS).”
Radadiya noted that “I am involved in conducting this research analytically, using experimental methods, including a high-fidelity advanced driving simulator, and naturalistically by studying drivers on the real road.”
In his nomination letter for Radadiya, Pradhan explained that his student has surpassed expectations by displaying a natural intuition and understanding for scientific research.
As Pradhan said, “This included literature reviews; analytical approaches towards collating information; complex visualization; and categorizing edge cases and limitations. These are normally tasks conducted by graduate students, and thus I consider Mr. Radadiya’s capabilities and work ethic to be comparable to that of senior graduate-level students.”
Pradhan added that Radadiya is a rare undergraduate who has contributed significantly to research and to the preparation of manuscripts, as demonstrated by the fact that Radadiya co-authored three recently published peer-reviewed journal papers by collaborating with Pradhan and others.
In addition, said Pradhan, Radadiya was recently awarded the 2019 Undergraduate Excellence Award by the Safety Research Using Simulation (SAFER-SIM) Center, a Tier 1 University Transportation Center funded by the U.S. Department of Transportation. The award was based "upon accomplishments in three areas: technical merit and research capability, academic performance, and leadership."
In addition to the above, said Pradhan, “Mr. Radadiya is a high-achieving student with excellent academic achievements. He was on the Dean’s list for two consecutive terms and is a recipient of the Chancellor’s award. He holds a leadership position in the SAE Formula team and the Institute for Industrial and Systems Engineering Student Chapter.”
In describing his latest research, Radadiya said that “Currently I am involved in various research projects where we are trying to evaluate a driver’s mental model of ADAS and how does that affect the driver’s comprehension, trust, and use of the technologies, specifically with respect to vehicle automation and driving safety.”
Radadiya explained that “I am particularly interested in these questions given the promise that automated technologies might revolutionize human driving. However, I am also healthily skeptical and thus want to examine the potential for, and impact of, unintended negative consequences of this technology.”
Despite Radadiya’s status as an undergraduate research assistant, Pradhan has trusted him with many tasks normally allocated to senior graduate students.
According to Radadiya, “I have thus undertaken in-depth reviews of vehicle technology functionalities and helped the project team make significant progress by deconstructing these systems into state diagrams, identifying limitations and edge cases of these systems, and helping create a taxonomy of error types, including counting the plausibility of these error types and a categorization of mental-model states.” (March 2021)