A2GO: Revolutionizing Autonomous Mobility in Ann Arbor
Technology Category
- Functional Applications - Fleet Management Systems (FMS)
- Infrastructure as a Service (IaaS) - Public Cloud
Applicable Industries
- Automotive
- Transportation
Applicable Functions
- Logistics & Transportation
Use Cases
- Autonomous Transport Systems
- Fleet Management
Services
- System Integration
About The Customer
The customers of A2GO are primarily the students and faculty of the University of Michigan, along with community members and visitors in Ann Arbor. These individuals require reliable and efficient transportation to navigate between the Kerrytown area, Downtown, and the University of Michigan’s campus. They also need to reach popular local destinations such as the U of M Museum of Art and the Ann Arbor Public Library, and connect to other forms of transit like the Ann Arbor Amtrak Station. The service is particularly beneficial for those who do not own a personal vehicle or prefer a shared, autonomous mode of transportation.
The Challenge
Ann Arbor, Michigan, was looking for a way to provide efficient and convenient transportation for the University of Michigan students and faculty, as well as community members and visitors. The city needed a solution that would connect the Kerrytown area with Downtown and the University of Michigan’s campus, including popular local destinations such as the U of M Museum of Art and the Ann Arbor Public Library. The solution also needed to provide connections to other forms of transit, such as the Ann Arbor Amtrak Station. The challenge was to implement a solution that would be free, autonomous, and shared, while also being able to account for live traffic and road conditions.
The Solution
The solution came in the form of A2GO, a free, autonomous, shared ride service launched in October 2021. The service was made possible through a partnership between Via, May Mobility, Mcity at the University of Michigan, Ann Arbor SPARK, 4M, and !Important, with funding from the Michigan Economic Development Corporation. May Mobility provided the autonomous vehicles (AVs) for A2GO, while Via powered the routing algorithms, transit software system, and customer-facing tools. This enabled the AVs to be booked on-demand and dynamically routed, while also ensuring a safe and convenient rider experience. Via’s routing algorithms took into account live traffic and road conditions in Ann Arbor to determine the optimal AV route and ride pooling mix. Via also built a custom rider app through which riders could book on-demand rides on any other May Mobility AV service in Michigan, track their ride status, and connect with customer support at any time.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Airport SCADA Systems Improve Service Levels
Modern airports are one of the busiest environments on Earth and rely on process automation equipment to ensure service operators achieve their KPIs. Increasingly airport SCADA systems are being used to control all aspects of the operation and associated facilities. This is because unplanned system downtime can cost dearly, both in terms of reduced revenues and the associated loss of customer satisfaction due to inevitable travel inconvenience and disruption.
Case Study
Integral Plant Maintenance
Mercedes-Benz and his partner GAZ chose Siemens to be its maintenance partner at a new engine plant in Yaroslavl, Russia. The new plant offers a capacity to manufacture diesel engines for the Russian market, for locally produced Sprinter Classic. In addition to engines for the local market, the Yaroslavl plant will also produce spare parts. Mercedes-Benz Russia and his partner needed a service partner in order to ensure the operation of these lines in a maintenance partnership arrangement. The challenges included coordinating the entire maintenance management operation, in particular inspections, corrective and predictive maintenance activities, and the optimizing spare parts management. Siemens developed a customized maintenance solution that includes all electronic and mechanical maintenance activities (Integral Plant Maintenance).
Case Study
IoT-based Fleet Intelligence Innovation
Speed to market is precious for DRVR, a rapidly growing start-up company. With a business model dependent on reliable mobile data, managers were spending their lives trying to negotiate data roaming deals with mobile network operators in different countries. And, even then, service quality was a constant concern.
Case Study
Digitize Railway with Deutsche Bahn
To reduce maintenance costs and delay-causing failures for Deutsche Bahn. They need manual measurements by a position measurement system based on custom-made MEMS sensor clusters, which allow autonomous and continuous monitoring with wireless data transmission and long battery. They were looking for data pre-processing solution in the sensor and machine learning algorithms in the cloud so as to detect critical wear.
Case Study
Cold Chain Transportation and Refrigerated Fleet Management System
1) Create a digital connected transportation solution to retrofit cold chain trailers with real-time tracking and controls. 2) Prevent multi-million dollar losses due to theft or spoilage. 3) Deliver a digital chain-of-custody solution for door to door load monitoring and security. 4) Provide a trusted multi-fleet solution in a single application with granular data and access controls.
