Analyzing the Impact of Autonomous Maintenance Technology to Transportation Infrastructure Capacity for Condition Monitoring and Performance Management
Dr. Xianbiao (XB) Hu
Missouri University of Science & Technology
The Autonomous Maintenance Technology (AMT) is a quickly emerging autonomous-vehicle-based technology for improving transportation infrastructure maintenance by removing drivers from risk. This project will develop models and algorithms to reveal its fundamental operating mechanism, and analyze its impact to transportation capacity for infrastructure condition monitoring and performance management. Newell car following model and moving-bottleneck-based traffic flow theory will be utilized to mathematically derive the roadway capacity under different scenarios. Multiple sensors, including high resolution Global Positioning System (GPS), Light Detection and Ranging (LiDAR), Radar, high definition camera, accelerometer and gyroscope installed on the AMT vehicles will collect real data from the field for model validations.
Dr. XB Hu is currently an Assistant Professor at Missouri University of Science and Technology. He received his Ph.D. from the University of Arizona in 2013 and was a founding team member and the Director of R&D at Metropia Inc. in Tucson AZ. His research focuses on smart transportation systems, transportation big data analytics, and traffic flow and system modeling.