Researchers with the Georgia Tech Research Corporation will combine real-time analysis of transportation network data with distributed simulation modeling to provide drivers with information and incentives to reduce energy consumption. The team’s system model will use three sources of data to simulate the transportation network of the Atlanta metro area. The Georgia Department of Transportation’s intelligent transportation system (ITS) data repository, hosted at Georgia Tech, will provide 20-second, lane-specific operations data while team partner, AirSage, will provide highway speeds and origin-destination patterns obtained from cellular networks. The team will also use real-time speed data collected from 40,000 volunteers using a smartphone application. The researchers will use pattern recognition algorithms to identify traffic accidents and recurrent congestion, predict traffic congestion severity, and user responses to congested conditions. Using this information, the team will develop a control architecture that will signal drivers with options to alter departure times, take specific routes, and/or use alternate modes of transportation to reduce energy use. The team anticipates that users will adopt the suggested guidance because the suggestions identified will not increase the time or cost of the trip, and could ultimately save users money in fuel costs.
If successful, the Georgia Tech system will demonstrate that energy-efficiency gains in personal transportation can be accomplished through network controls that encourage individual travelers to take specific, energy-relevant actions.
Georgia Tech’s system could facilitate a reduction in transportation energy use and help reduce demand for imported oil.
More efficient transportation networks will minimize energy consumption, resulting in improved air quality and lower greenhouse gas emissions.
Georgia Tech’s system could help reduce congestion in metro areas without requiring investment in new infrastructure. A more efficient transportation network could further improve the overall productivity within a regional transportation network.