Towards an Efficient Robotaxi Deployment

Towards an Efficient Robotaxi Deployment

Headshot of Sina Bahrami. The link directs to their profile page on the CCAT website.
Sina Bahrami
Headshot of Marco Nie. The link directs to their profile page on the CCAT website.
Marco Nie
Siqian Shen Headshot. The link directs to their profile page on the CCAT website.
Siqian Shen
Headshot of Yafeng Yin. The link directs to their profile page on the CCAT website.
Yafeng Yin
The University of Michigan Logo. The link directs to the funded research led by this institution.
Northwestern University Logo. The link directs to the funded research led by this institution.

Principal Investigator(s):

Sina Bahrami, Assistant Research Scientist in the Department of Civil and Environmental Engineering – The University of Michigan
Siqian Shen, Associate Professor of Industrial and Operations Engineering – The University of Michigan
Associate Director – Michigan Institute of Computational Discovery & Engineering (MICDE)
Marco Nie, Professor of Civil and Environmental Engineering – Northwestern University
Yafeng Yin, Donald Cleveland Collegiate Professor Of Engineering – The University of Michigan
Donald Malloure Department Chair Of Civil And Environmental Engineering – The University of Michigan

Project Abstract:
The commercial deployment of automated vehicles (AVs) for on-demand mobility services, referred to as robotaxis, has advanced significantly in recent years. Given the drastic changes that robotaxis might set in motion in the near future, there is a crucial need to prepare guidelines for their efficient deployment. Our collaborative project aims to facilitate this effort by developing modeling tools to understand the complex interactions between the various stakeholders involved in the robotaxi’s deployment phase, including regulators, transit agencies, robotaxi operators, TNC drivers, private AV owners, and regular travelers.

Institution(s): University of Michigan – Ann Arbor
Northwestern University

Award Year: 2025

Research Focus: Safety, Cybersecurity, Mobility, Fairness

Project Form(s):

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