Self-Driving Shuttles
What is an ADS?
According to the National Highway Transportation Safety Administration (NHTSA), an Automated Driving System (ADS) is a vehicle capable of driving itself including steering, acceleration, and braking.
See more details about the ADS grant here on the USDOT website!
What is a pilot?
A pilot is a short-term deployment of a product to prove viability and help introduce new tools. These new tools can then be demonstrated at a controlled scale that is then scaled up for real-world solutions.
What is our project?
Our project aims to provide an ADS shuttle service for older adults and people with disabilities, helping residents get to critical locations such as doctor's appointments, grocery store, and more.
The shuttle service will be deployed in a concentrated area of Detroit with the potential to expand after the pilot concludes.
We will pilot our shuttle in a neighborhood throughout the city that is yet is be determined.
Learnings from the pilot will help us improve and expand the service throughout Detroit.
We received a federal grant to fund this innovation. Learn more about the Project Narrative.
An Opportunity for an Innovative Solution
Older adults and people with disabilities (PwD) in Detroit lack adequate transportation solutions that can increase opportunities, access, and independence.
This potential solution is proudly crafted for Detroiters by Detroiters.
Safety
Our team will demonstrate how an ADS increases safety for pedestrians, passengers, and other vulnerable road users in an urban transportation setting. The video below shows how we are putting the vehicle through rigorous testing before it hits the streets:
The Safe AI Framework for Trustworthy Edge Scenario Tests, or SAFE TEST, was developed by the Center for Connected and Automated Transportation (CCAT) to maximize autonomous vehicle testing efficiency while ensuring testing accuracy. In this video, six driving scenarios are presented using virtual vehicles that are fed to the vehicle under test. These scenarios are deployed in a naturalistic and adversarial driving environment (NADE) to execute adversarial maneuvers against the real-world, test vehicle.
Data
Develop public framework that increases availability and usability of ADS data to inform safety analysis and rulemaking
Collaboration
Increase collaboration amongst government entities, private organizations, and residents by promoting transparent communication, understanding community needs, and providing ADS education opportunities.
Mobility Equity
Increase the mobility of older adults and people with disabilities to provide improved quality of life to City of Detroit residents.