This work was supported in part by the Intel Science and Technology Center for Big Data and a Maseeh Professorship.
Decision making -- Statistical methods, Transportation -- Planning -- Oregon -- Portland, Data mining
Urban transportation professionals are under increasing pressure to perform data-driven decision making and to provide data-driven performance metrics. This pressure comes from sources including the federal government and is driven, in part, by the increased volume and variety of transportation data available. This sudden increase of data is partially a result of improved technology for sensors and mobile devices as well as reduced device and storage costs. However, using this proliferation of data for decisions and performance metrics is proving to be difficult. In this paper, we describe a proposed structure for a system to support data-driven decision making. A primary goal of this system is improving the use of human time, effort and attention with side benefits of improved consistency and documentation.
Tufte, Kristin A.; Elazzabi, Basem; Hall, Nathan; Harvey, Morgan; Knobe, Kath; Maier, David; and Megler, Veronika Margaret, "Guiding Data-Driven Transportation Decisions" (2014). Computer Science Faculty Publications and Presentations. 128.