The Department of Energy's Argonne National Laboratory is leading a project to examine traffic data sets from across the Los Angeles region to develop new strategies to reduce traffic congestion.
Big data continues to drive transportation planning and analysis as researchers crunch traffic counts from across one of the nation’s most car-centric metro regions. The efforts are helping to not only predict where problems may arise, but test mitigation measures.
The U.S. Department of Energy’s Argonne National Laboratory is examining traffic data from across the Los Angeles metro region in order to develop strategies to reduce traffic congestion.
“We want to look at this problem more from a system level,” explained Prasanna Balaprakash, a computer scientist with the Argonne National Laboratory.
“We want to think of traffic as a complex system, and we are interacting with that system and how we can model that. How we can develop predictive models to optimize the various aspects of this complex system,” he added.
The project is a partnership among institutions like DOE’s Lawrence Berkeley National Laboratory (LBNL) and the Argonne National Laboratory to develop large-scale simulation modeling.
Super computers at the Argonne Laboratory are able to take a year’s worth of traffic data gathered from some 11,160 sensors across southern California, as well as movement data from mobile devices, to build forecasting models. They can then be applied to simulation projects.
“The idea is to use this data [cellphone movement data] along with the sensor data, because the nice thing about this data is it has a lot more penetration,” said Balaprakash.
“You can combine the data in different ways, and try to build predictive models,” he added. “What we have done is built really large-scale models.”
The use of big data for traffic management and other transportation applications is becoming increasingly common, said Ben Volkow, CEO of Otonomo, a connected vehicle technology company based in Israel with an office in San Francisco.
“Transportation is a major factor affecting urban areas, and a key use case for smart cities,” said Volkow. “Intelligent transportation systems, often using a traffic management center to monitor and coordinate a large network of sensors, will find even more innovative ways to improve traffic congestion and urban mobility.”
Some trends to expect going forward, said Volkow, include improved connectivity infrastructure thanks to the rollout of 5G, as well as increased data regulations related to data privacy. Also, watch for “widespread deployment of Intelligent Traffic Systems [ITS], utilizing connected vehicle data, [which] will lead to safer roads and less congestion,” said Volkow.
“So that we can take those models, those simulations, and ask 'what if' questions. So what if we implement this type of policy? What if we change the infrastructure here? What are the bottlenecks?” Balaprakash offered.
The Los Angeles Department of Transportation is not involved in the project. Currently, traffic management is handled by the Los Angeles Automated Traffic Surveillance and Control (ATSAC) Center.