MIDAS-supported researchers recently published a paper on the potential for incorporating ridesourcing services with public transit.
The Big Data in Transportation and Mobility symposium held June 22-23, 2017, in Ann Arbor, MI brought together more than 150 data science practitioners from academia, industry and government to explore emerging issues in this expanding field.
Sponsored by the NSF-supported Midwest Big Data Hub (MBDH) and the Michigan Institute for Data Science (MIDAS), the symposium featured lightning talks from transportation research programs around the Midwest; tutorials and breakout sessions on specific issues and methods; a poster session; and a keynote address from two representatives of the Smart Columbus project: Chris Stewart, Ohio State University Associate Professor of Computer Science and Engineering, and Shoreh Elhami, GIS Manager for the city of Columbus.
Speakers and attendees came from a number of organizations from across the midwest including the University of Michigan, University of Illinois, University of Nebraska, University of North Dakota, North Dakota State University, Ohio State University, Purdue University, Denso International America, Fiat Chrysler, Ford Motor Company, General Motors, IAV Automotive Engineering and Yottabyte.
“This was an extremely valuable opportunity to share information and ideas,” said Carol Flannagan, one of the organizers of the symposium and a researcher at MIDAS and the U-M Transportation Research Institute. “Cross-discipline and cross-institutional collaboration is crucial to the success of Big Data applications, and we took a significant step forward in that vein during this symposium.”
Topics addressed in talks, breakouts, and tutorials included:
- New Analytic Tools for Designing and Managing Transportation Systems
- New Mobility Options for Small and Mid-sized Cities in the Midwest
- Automated and Connected Vehicles
- Transforming Transportation Operations using High Performance Computing
- On-Demand Transit
- Using Big Data for Monitoring Bridges
At the closing session, participants outlined some areas that could be fruitful to focus on going forward, including increasing data-science literacy in the general public; diversity and workforce development in data science; public data-sharing platforms and partners; and privacy issues.
The Midwest Big Data Hub
“Big Data for Transportation and Mobility”
The NSF supported Midwest Big Data Hub has made data for transportation a priority. Its goal is to bring together experts in the increasingly powerful tools of Big Data (including visualization, machine learning, statistical models, integration of heterogeneous data, data scrubbing, privacy and security) with domain experts. The Midwest has been a center of innovation in transportation for generations and data-related research has become a major focus of interest for corporate, academic, and governmental organizations. This conference includes a series of presentations providing an overview of research underway in the Midwest hat will help us understand the scope of this work, encourage cross-fertilization, and possibly nucleate future collaborations.
One of the highlights of the meeting will be a series of talks by faculty from the schools that are the core of the Midwest Big Data Hub. Additional activities include tours of research sites on the Ann Arbor Campus, short tutorials and breakout sessions on pertinent topics.
Students are especially welcome and a poster session, part of the conference reception on June 22, will provide an opportunity for them to share their research. There is some limited travel and hosting funding available for students; restrictions apply and requests for travel/ hosting support should be submitted while registering.
The Midwest Big Data Hub is supported by the National Science Foundation through award #1550320.
This symposium will bring together leaders from the public and private sectors and academia to meet the challenges posed by deployment of transformational transportation technologies. MIDAS affiliated faculty members Carol Flannagan, Al Hero and Pascal Van Hentenryck will be speaking.
For more information, visit the event website.
The Transportation Research Board (TRB) of the National Academies of Science, Engineering, and Medicine is sponsoring the “Partners in Research Symposium: Transformational Technologies” on October 31-November 1, 2016, in Detroit, Michigan.
Additional details can be found under the “Program” tab in the symposium website.
New technologies have the potential to transform transportation as we know it. Public agencies are being challenged to facilitate the deployment of these technologies in a manner and timeframe that will lead to improved safety, reduced congestion, enhanced sustainability, and economic development. This TRB symposium will bring leaders from the public and private sectors and academia together to help generate research and innovations to enable agencies to meet this challenge. The symposium will lay the foundation for research roadmaps and partnerships.
Technologies that are expected to be addressed include connected and automated vehicles, shared-use mobility services, smart cities and the internet-of-things, unmanned aircraft systems, NextGen, big data and cybersecurity, and alternative fueled vehicles.
Research on connected and automated vehicles which recently received funding under the Michigan Institute for Data Science (MIDAS) Challenge Initiative was featured in “The Urban Transportation Monitor.” The projects featured are led by Pascal Van Hentenryck (Industrial and Operations Engineering) and Carol Flannagan (U-M Transportation Research Institute).
The article, available for download, begins on page 6.
The Urban Transportation Monitor (now in its 30th year) reports on the latest developments in urban transportation. Its circulation reaches thousands of readers across the U.S. as well as 30 countries worldwide. Subscribers include the most prominent organizations active in urban transportation. For more information, see www.urban-transportation-monitor.com/.
The Xconomy.com website has featured transportation data science projects awarded funding under the first round of the MIDAS Challenge Initiatives.
College of Engineering Prof. Pascal Van Hentenryck and Carol Flannagan of the U-M Transportation Research Institute were awarded $1.25 million each for projects that will apply data science methodologies to transportation. U-M Dearborn is contributing another $120,000 to each project, and co-PIs are involved from the School of Information, Medical School, Architecture and Urban Planning, Computer Science, School of Public Health, and the Institute for Social Research, among others.
Please see the Xconomy article for more.
Toyota Materials Handling North America is accepting proposals for sponsored research under its University Research Program, which aims to “drive the next generation of technology for the entire supply chain, logistics and material handling industry.”
According to the company’s description, “The mission is to encourage professors and researchers to apply their knowledge of engineering and technical fields, drawing synergies and collaboration between collegiate research and Toyota Material Handling North America.”
Visit http://www.universityresearchprogram.com/ for more information and submission instructions.
Four research projects — two each in transportation and learning analytics — have been awarded funding in the first round of the Michigan Institute for Data Science Challenge Initiatives program.
The projects will each receive $1.25 million dollars from MIDAS as part of the Data Science Initiative announced in fall 2015.
U-M Dearborn also will contribute $120,000 to each of the two transportation-related projects.
The goal of the multiyear MIDAS Challenge Initiatives program is to foster data science projects that have the potential to prompt new partnerships between U-M, federal research agencies and industry. The challenges are focused on four areas: transportation, learning analytics, social science and health science.
Abstract: Traditionally traffic signal systems are designed in such a way that different time slots are allocated to conflicting traffic streams in order to ensure vehicle safety. In the future, such design constraints may be relaxed with connected and automated vehicle (CAV) streams because crash avoidance can be achieved through distributed control of vehicle trajectories, therefore traditional traffic signals may no longer be needed.
In this talk, we will discuss the opportunities and challenges for traffic control systems with varying percentages of connected and automated vehicles. In particular, we will present our findings using the massive data set collected from the Safety Pilot Model Deployment project and Ann Arbor Connected Vehicle Test Environment, both supported by USDOT.
Bio: Henry Liu, PhD, is a Research Professor at the U-M Transportation Research Institute (UMTRI) and a Professor in the U-M Department of Civil and Environmental Engineering.