With the number of automated vehicles increasing on our roadways it is important to understand their potential impacts and how other road users will interact with them. In the future, there will be a more pronounced shared levels-of-automation transportation network, with fully manual, partially automated, and fully automated vehicles sharing the same Minnesota roads. While planners and engineers have a reasonable idea of how humans drive around other humans, what is not as well-known is human driving behavior around automated vehicles.
The Med City Mover is an ongoing MnDOT-led research project testing two low-speed, automated shuttles in Rochester, MN, to help MnDOT and local agencies plan for automated transportation in Minnesota. The objective of this study is to analyze pedestrian safety and driver behavior near automated vehicles, specifically the Med City Mover shuttle, particularly when the automated vehicle is coming to a stop and yielding to crossing pedestrians. This analysis will be accomplished via in field data collection in which the research team will act as pedestrians in the crosswalk and observe natural driver behavior. In addition to field data collection a driving simulator will be designed and implemented, and participants will undergo various driving scenarios related to yielding automated vehicles.
Prior research has observed that drivers may follow too close or engage in unsafe speeds around automated vehicles, and drivers have a higher risk of rear-end crashes with automated vehicles. This study will bolster the general understanding of how drivers interact with automated vehicles, particularly large-slower moving shuttles, thus aiding in the safety of drivers, pedestrians, and shuttle passengers.
This work addresses MnDOT’s strategic research priorities of safety, innovation, and future needs, as well as equity. As communities continue to build walkable communities, higher pedestrian volumes are expected and increasing conflict with automated vehicles must be addressed. Additionally, this work addresses the needs of the most vulnerable of our communities who disproportionately rely on walking and public transportation.
“I am very hopeful that this project will start the process of better understanding how human drivers interact with machine driving and identify which risky behaviors need to be addressed first,” said Cory Johnson, intelligent transportation systems manager, MnDOT Office of Connected and Automated Vehicles. “With this better understanding, I hope that technology companies will be able to build better driving systems for all types of drivers, machine and human.”
- Increase understanding of how drivers interact with automated vehicles
- Aide in the safety of drivers, pedestrians, and automated shuttle passengers
- Address the needs of the most vulnerable of our communities who disproportionately rely on walking and public transportation
- Estimated Start Date: 03/01/2022
- Estimated Completion Date: 01/31/2024
- Funding: $241,816
- Principal Investigator: Nichole L. Morris
- Co-Principal Investigators: Curtis M. Craig
Details of the research study work plan and timeline are subject to change.