CTS has awarded seed funding to five new transportation-related projects that will explore a variety of topics, including smart cities, smart infrastructure, and the sharing economy, beginning in the spring of 2016.
The seed funding, awarded biennially, aims to help CTS Scholars develop expertise in emerging areas and foster strategic relationships that position researchers at the U of M for future funding opportunities. This year, the five projects will receive a total of $199,411 in funding from CTS.
Following are brief descriptions of the projects.
Algorithms for Networked Cooperative Navigation
Demoz Gebre-Egziabher, Associate Professor, Department of Aerospace Engineering and Mechanics
This project will focus on developing algorithms for networked and cooperative navigation—a term used to describe the process by which a group of users, through collaborative information exchange, form an estimate of their location. The new algorithms will allow vehicles to operate in environments where GPS is unavailable or unreliable, such as autonomous navigation and guidance in urban settings, personal navigation indoors and in urban canyons, and small unmanned aerial vehicles (drones) operating under bridges and in tunnels.
Collaborative Consumption in Peer-to-Peer Car Sharing: Models, Analysis, and Experiments
Saif Benjaafar, Professor, Department of Industrial and Systems Engineering; Guangwen (Crystal) Kong, Assistant Professor, Department of Industrial and Systems Engineering; Tony Cui, Associate Professor, Department of Marketing, Carlson School of Management; Alireza Khani, Assistant Professor, Department of Civil, Environmental, and Geo- Engineering
This project will develop an economic model that can be used to predict how the introduction of a peer-to-peer car sharing option will affect car ownership, car usage, and social welfare. The model will be calibrated to reflect different market sizes, mobility needs, and costs of ownership, and it will also include behavioral features. Ultimately, policymakers will be able to use the model both to assess when peer-to-peer car sharing leads to socially desirable outcomes and to understand which policy measures will support those outcomes.
Enriched Sensor Data for Enhanced Bridge Weigh-in-Motion (eBWIM) Applications
Arturo Schultz, Professor, Department of Civil, Environmental, and Geo- Engineering, and John Hourdos, Director, Minnesota Traffic Observatory
This project will examine sensor technologies that can help improve the performance of bridge weigh-in-motion (BWIM) systems by providing enriched data on vehicle locations, vehicle dimensions, number of axles, number of vehicles, instantaneous vehicle speeds, and more. The project will also formulate a long-range plan for establishing a testbed in Minnesota to investigate enhanced BWIM data processing techniques, validation, and calibration.
Full-Day Accessibility Evaluation of Transit Systems Using GPS-Based Location Data
Andrew Owen, Director, Accessibility Observatory, and Ying Song, Assistant Professor, Department of Geography, Environment and Science
Most transit system operators produce automatic vehicle location and automatic passenger counter datasets that are underutilized in research on how transit system performance affects users’ mobility and accessibility. By working with these datasets, this project will demonstrate how mobility and accessibility can be analyzed from a reliability perspective. Instead of assuming perfect schedule adherence every day, it will be possible to measure how much variation in mobility and accessibility users experience as a result of unpredictability in transit travel times.
Investigation of Compaction Process of Graphene Nano-Platelet-Modified Asphalt Mixtures
Jia-Liang Le, Assistant Professor, Department of Civil, Environmental, and Geo- Engineering; Kimberly Hill, Associate Professor, Department of Civil, Environmental, and Geo- Engineering; and Mihai Marasteanu, Professor, Department of Civil, Environmental, and Geo- Engineering
A new generation of high-efficiency, long-lasting pavement that incorporates graphene nano-platelets (GNP) into the asphalt binders has been developed at the University of Minnesota. One of the many benefits of GNP is that it substantially reduces the required compaction effort, and this project will investigate why and how this occurs. The project will include the development of a physics-based framework to predict how GNP-modified asphalt binders influence the compaction behavior, and it will use this framework to suggest protocols for improved compaction performance.