Princeton University

School of Engineering & Applied Science

Towards Socially-Aware Autonomy for Mobility-Efficient Smart Cities

Negar Mehr, University of California, Berkeley
B205 Engineering Quadrangle
Thursday, March 7, 2019 - 4:30pm

As cities grow everywhere, and urban roadways become overburdened, efficient strategies are required for improving mobility. With the prevalence of smart sensing and Internet of Things (IoT) devices, such as smart phones and smart intersections, the physical infrastructures of our cities are being connected to the cyber world. As a result, cities are becoming smart. Moreover, with the emergence of new and inevitable technologies, such as autonomous and connected vehicles, mobility on demand systems, and electric vehicles, smart cities are rapidly evolving. As we experience the arrival of such technologies, there is an opportunity to reclaim urban mobility. However, a blind utilization of these technologies may deflect us from reaching this goal. In my research, I leverage the connectivity that is inherent in smart cities as well as the opportunities that new technologies such as autonomous and connected vehicles provide, to study the efficient operation of smart cities via management strategies that can guarantee overall societal benefits.
In this talk, I will focus on the societal-scale mobility implications of the increased deployment of autonomous and connected vehicles in mixed-autonomy traffic networks, where both human-driven and autonomous vehicles will coexist on the roads. I will first talk about the mobility implications of selfish autonomy, in which autonomous cars are not aware of their overall impact and simply attempt to optimize their own travel benefits. In this context, I will introduce conditions under which an increase in the fraction of autonomous vehicles on a traffic network, even when operating selfishly, results in increased societal mobility benefits. Conversely, I will show that if these conditions do not hold, overall network mobility may degrade as the fraction of autonomous vehicles increases. Having shown the negative consequences that the increased deployment of autonomous and connected vehicles may have on the operation of traffic networks, I will further discuss the use of traffic management strategies, such as pricing, which can guarantee the overall societal-scale efficiency of traffic networks with mixed vehicle autonomy.

Negar Mehr is a PhD candidate in the Department of Mechanical Engineering at UC Berkeley. She received her B.Sc. in Mechanical Engineering from Sharif University of Technology, Tehran, Iran, in 2013. Her research interests lie in the intersection of control theory, game theory, and intelligent transportation systems. Specifically, she works on developing reliable and efficient solutions that can ensure efficient operation of societal-scale infrastructures such as transportation systems. Negar was the corecipient of the first prize for the best student paper award at the International Conference on Intelligent Transportation Systems, 2016. She was also the graduate winner of the 2017 WTS-OC (Women Transportation Seminars-Orange County Chapter) scholarship. She is the recipient of several departmental fellowships including the Chang-Lin Tien graduate fellowship, the Oakley & Barratt Family graduate fellowship, the Graduate Division Block Grant award, and the Eltoukhy East-West Gateway fellowship. Negar was recognized as a rising star in EECS, Aeronautics & Astronautics, and Civil and Environmental Engineering.