ME Alum Negar Mehr Wins 2020 IEEE ITS Best Dissertation Award
ME Alum Negar Mehr has won the 2020 IEEE ITS Best Dissertation Award. The IEEE ITS Best Dissertation Award is given annually for the best dissertation in any ITS area that is innovative and relevant to practice. This award is established to encourage doctoral research that combines theory and practice, makes in-depth technical contributions, or is interdisciplinary in nature, having the potential to contribute to the ITSS and broaden the ITS topic areas from either the methodological or application perspectives. The winners will receive a cash prize and invitation to be recognized and present their work at the ITSC conference. Awardees’ work will be featured in ITSS Transactions, ITS Magazine, and ITS Newsletter, when appropriate.
Negar received her Ph.D. in the summer of 2019, here in the Department of Mechanical Engineering at UC Berkeley. Her thesis is entitled “Smart Traffic Operation: from Human-Driven Cars to Mixed Vehicle Autonomy.” The first part of Negar’s dissertation tackles existing challenges in the smart operation of traffic networks that are solely transited by human–driven cars, by appropriate coordination and control of traffic signalization. The second part of Negar’s dissertation considers the very novel and important issue of how the increased adoption of smart vehicles, which are both connected and autonomously driven, will affect the overall efficiency of traffic network systems.
She first provides conditions that guarantee improved network mobility with increase adoption of smart vehicles, even under “selfish autonomy.” However, when these conditions do not hold, she shows that the expected mobility benefits of smart vehicles are not inexorable and proves that, if vehicles are allowed to choose their routes selfishly in order to decrease their own travel costs, increases in smart vehicle adoptions lead to inefficient overall social travel delays, unless the capacity improvements of all of the roadways in the network with increased vehicle autonomy is homogeneous. After showing the negative consequences of selfish autonomy, Negar develops a vehicle pricing mechanism that achieves the overall societal–scale efficiency of traffic networks with mixed vehicle autonomy. The last part of Negar’s dissertation discusses practical deployments of “altruistic autonomy,” where autonomous vehicles can plan their actions in favor of the overall good, by taking into account the decision making process of selfish humans.
Negar recently completed her postdoctoral research at Stanford, and has joined the Department of Aerospace Engineering at the University of Illinois, Urbana-Champaign as a faculty member. Congratulations, Negar!