This research was funded by the National Institute for Transportation and Communities, with additional support from Pima County Public Works Administration and the Utah Department of Transportation
Transportation -- Planning, Traffic safety, Transportation -- Data processing, Traffic monitoring, Travel time (Traffic engineering)
How can we use a variety of data-driven speed management strategies to make transportation safer and more efficient for all modes–whether you’re driving, walking or taking transit? The project was led by Yao Jan Wu, director of the Smart Transportation Lab at the University of Arizona. Co-investigators were Xianfeng Terry Yang of the University of Utah, who researches traffic operations and modeling along with connected automated vehicles, and Sirisha Kothuri of Portland State University, whose research has focused on improving signal timing to better serve pedestrians. “We want to improve mobility for all users, be it pedestrians, vehicle drivers or transit riders, and there are different strategies to do this. How do we harness data to drive us to these strategies?” Kothuri said. This multi-university collaboration addressed the question from three angles. Wu and his students in Arizona looked at the impact of speed management strategies on conventional roadways. Yang and his team examined the effects of speed management strategies on connected corridors, coordinating with transit signal priority (TSP) systems. Kothuri and her PSU team came up with an approach to estimate pedestrian delay at signalized intersections.
Wu, Y., Yang, X., Kothuri, S. Applying Data-Driven Multimodal Speed Management Strategies for Safe, Efficient Transportation. NITC-RR-1298. Portland, OR: Transportation Research and Education Center (TREC), 2021.