Organizations embarking on driverless shuttle deployments should set specific project goals, identify operating environment requirements, engage with stakeholders and regulators and establish data needs early for project success.
Case study documents University of Michigan’s experience in launching an on-campus driverless shuttle research project.
Made Public Date
02/13/2019

850

Ann Arbor
Michigan
United States
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Identifier
2019-00862

Mcity Driverless Shuttle: A Case Study

Background

In June 2018, Mcity, a public-private partnership at the University of Michigan (U-M), launched a driverless shuttle project in the United States focused on user behavior research. With two shuttles transporting students, faculty, and staff on the U-M campus, the project was designed to support data collection to understand vehicle performance, roadway interactions, and passenger attitudes. Mcity is studying how passengers and other road users react to and interact with the shuttles as a way to gauge consumer acceptance of the technology. The ultimate goal is long-term deployment of driverless shuttles in the real world.

The two Mcity shuttles are fully-automated, 11-seat, all-electric shuttles manufactured by NAVYA that transport students, faculty, and staff on a one-mile round trip route at the university’s North Campus Research Complex. The shuttles are equipped with on-board cameras, microphones, and Wi-Fi communications to capture data generated during operation. The Mcity shuttles currently operate at a maximum speed of 12 miles per hour. Safety conductors ride onboard to provide an extra layer of assurance for safe shuttle operation.

Lessons Learned

Mcity shared the following lessons learned to help other organizations who may be considering launching driverless shuttle services.

  • Set Specific Project Goals. The Mcity Driverless Shuttle was designed to achieve the project goal of understanding passenger and road user behavior while ensuring a safe deployment. This goal shaped project choices regarding route environment, data acquisition, and operational plan.
  • Engage Stakeholders Early. Identify key stakeholders early in the process and engage them throughout the project. Their insights are invaluable, and they can flag potential obstacles to progress.
  • Explore Legal, Regulatory, and Insurance Questions. To the extent possible, seek to engage federal, state, and local government authorities early, in the planning stages. View government regulators as collaborators as their advice is often invaluable. Connect with institutional and community stakeholders at the outset as preliminary planning and development may require significant lead times for insurance and risk managers, legal counsel, transportation authorities and others.
  • Identify Operational Environment Constraints. Careful consideration must be given to a variety of parameters, including weather, roadway and traffic conditions and construction, prior to launch. During operation, constantly monitor these dynamic parameters, as any changes could conflict with defined operating environment.
  • Conduct Your Own Testing. Conduct a separate evaluation either by your organization or a third party to evaluate the performance of the driverless shuttle in the operating environment.
  • Train Safety Conductors Thoroughly. Create a careful progression of training for on-board safety conductors. Beginning in a closed testing site allowed conductors to build confidence in a safe environment before moving into real traffic conditions.
  • Anticipate Challenges. Be prepared for problems that arise when operating in less-than-perfect conditions. You need to be responsive to a dynamic operating environment with robust procedures and communications in place to facilitate smooth operation for conductors, passengers and other road users.
  • Develop an Incident Response Plan. Exhaustive emergency preparation is essential when deploying driverless shuttles. All stakeholders must understand their role in an emergency through training and practice.
  • Establish Data Needs Early. Define desired data needs early and devise a data collection method that does not interact or interfere with the sensors used by the shuttle for perception and control. This must be done while preserving privacy.

Mcity Driverless Shuttle: A Case Study

Mcity Driverless Shuttle: A Case Study
Publication Sort Date
09/18/2018
Publisher
University of Michigan Transportation Institute

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Goal Areas

Focus Areas Taxonomy: