Carnegie Mellon senses traffic using advanced vehicle-based sensor data
PITTSBURGH, PA (September 6, 2019) – Researchers from Carnegie Mellon University’s Department of Civil and Environmental Engineering collaborated with Uber Advanced Technologies Group (Uber ATG) to better understand how advanced vehicle-based sensor data can inform high resolution traffic flow measurements.
Henry Posner, Anne Molloy, and Robert and Christine Pietrandrea Associate Professor Sean Qian and research assistant Shuguan Yang, both members of Carnegie Mellon’s Mobility Data Analytics Center (MAC), co-authored a white paper informed by Uber Advanced Technologies Group’s Allison Plummer. For the purpose of this study, Uber provided MAC with access to select data, including vehicle travel speed and traffic density along two road segments in the Strip District.
The researchers created a case study showing how advanced vehicle-based sensors can provide information on traffic conditions in a given area. Using historical data, they chose instances where at least three sensor-equipped vehicles had passed through a given road segment. Information from the time the first and third vehicle passed a given point provided the input for their method, which was then able to output an accurate prediction of the traffic density between those times.
As indicated in the white paper, MAC demonstrates how sensor data being collected today, irrespective of the developer collecting it, could conceptually open new opportunities for traffic estimation and smart cities in general.
Qian, director of the MAC, and Yang plan to continue testing this approach over a greater road network using larger data sets. They are interested in comparing the efficacy of using data from vehicle-based floating sensors, versus more traditional fixed sensors.
For Carnegie Mellon University media inquiries please contact Dan Carroll at [email protected]
For Uber ATG media inquiries please contact Sarah Abboud at [email protected]
About the College of Engineering
The College of Engineering at Carnegie Mellon University is a top-ranked engineering college that is known for our intentional focus on cross-disciplinary collaboration in research. The College is well-known for working on problems of both scientific and practical importance. Our “maker” culture is ingrained in all that we do, leading to novel approaches and transformative results. Our acclaimed faculty have a focus on innovation management and engineering to yield transformative results that will drive the intellectual and economic vitality of our community, nation and world.
About Uber Advanced Technologies Group
Uber’s mission is to create opportunity through movement. We started in 2010 to solve a simple problem: how do you get access to a ride at the touch of a button? More than 10 billion trips later, we’re building products to get people closer to where they want to be. By changing how people, food, and things move through cities, Uber is a platform that opens up the world to new possibilities. Today, the team at Uber Advanced Technologies Group (ATG) is tackling another challenge: how do you build and deploy safe self-driving technology at scale? Uber ATG is comprised of world-class engineering talent dedicated to vehicle safety, self-driving software, mapping, and more. Uber is taking a holistic approach to bringing self-driving vehicles to market through a variety of partnerships, with the ultimate goal of creating autonomous ridesharing at scale.