Mobility

Adapt. Engineer. Prevail.

AutoDrive Challenge is a nationwide competition to achieve SAE Level IV autonomy with teams of students integrating sensors and controls.

Autonomy begins with sensing reality. Merging sensor data in real-time to identify roadways, signs, and hazards requires extensive coding and research on environmental impacts, such as scattering from snow.

From secure and decentralized swarms of subsurface gliders to the Marine Autonomy Research Site (MARS), our researchers advance the capabilities of marine and subsurface autonomous craft.

Students utilize a combustion chamber, run engine tests on dynamometers, test propulsion system components and full
vehicle test cells. They analyze data from a fleet of electric vehicles in a vehicle-to-vehicle and vehicle-to-infrastructure arrangement.

We develop leaders and technologies for 21st century rail transportation through field visits, integrated coursework, and industry-sponsored projects.

With an eye on the next frontier, research is being conducted across campus to demonstrate satellite performance and promote human space exploration.

  • $1.2M
    from U.S. DOE to fund the DRIFT model of intermodal logistics
  • $520K
    NSF CAREER Award to Hassan Masoud for aquatic robot research
  • 1000
    frames to teach AI what snowy roads look like
Kuilin Zhang

Getting Goods to Market: MTU Awarded Department of Energy Grant to Strengthen, Improve and Decarbonize Intermodal Freight

Michigan Technological University has received $1.2 million from the U.S. Department of Energy (DOE) to develop a practical tool that will help shipping, rail and trucking companies develop cohesive logistics for both predictive planning and real-time decisions that save time, energy and money.

Led by Kuilin Zhang, an associate professor in the Department of Civil, Environmental, and Geospatial Engineering, the Michigan Tech project is titled “A Decarbonized and Resilient Intermodal Freight Transportation (DRIFT) Modeling Platform for Intermodal Logistical Decisions Under Uncertainty.”