Nokia and UC Berkeley capture real-time traffic information using GPS enabled mobile devices
Live experiment on the California highway showcases a solution to a global problem
The experiment was carried out to test the traffic data collection and aggregation system, while studying the trade-offs between data accuracy, personal privacy, and data collection costs. The software aggregating the GPS feeds immediately disassociates that data from an individual device and combines it with the general stream of traffic data. To protect privacy, all data is anonymous and aggregated, and protected by banking-grade encryption.
During the experiment, special software on the mobile devices periodically sent anonymous speed and location readings from the integrated GPS to servers. The feeds were then combined to create a real-time picture of traffic speeds and projected travel times.
"Mobile device users control the service. If an individual does not want their device to transmit position data they turn off the feed from their GPS," stated Quinn Jacobson, Research Leader at Nokia Research Center, Palo Alto.
"Nokia is very excited at the potential for this system to revolutionize travel planning, carrying on from the Nokia Maps navigation service available today on certain Nokia devices," continued Jacobson. "Integration of traffic information with functions such as calendar and online timetables may one day mean the mobile device can act as personal travel planner."
"There are mobile device-based systems out there that can collect data in a variety of ways, such as measuring signal strength from towers and triangulating position, but to our knowledge, this is the first demonstration of this scale using GPS-enabled mobile devices to provide traffic related data such as travel times, and with a deliberate focus on critical deployment factors like bandwidth costs and personal privacy issues," said Director Thomas West, director, UC Berkeley's California Center for Innovative Transportation.
The researchers believe that fewer than 5% of drivers need to contribute location data for the system to be effective on any particular highway.
For state transportation agencies such as The California Department of Transport (Caltrans), tapping into the vast network of mobile phones on the road could one day remove the need to invest in expensive infrastructure to obtain traffic information as well as greatly expanding the coverage of such services.
In the USA alone congestion causes 4.2 billion hours extra travel every year and the purchase of extra 2.9 billion gallons of fuel for a congestion cost of USD 78 billion(1). With the number of vehicles on the road increasing rapidly around the world a cost-effective method of travel planning could help drivers make smarter decisions about which routes to take, the researchers say.
The project brings together research teams from the Nokia Research Center (NRC) in Palo Alto and from UC Berkeley, interacting through UC Berkeley's California Center for Innovative Transportation (CCIT). These teams are developing the algorithms, software and architecture of this GPS-based traffic monitoring system.
The project is supported by a USD 186,000 grant from Caltrans. Additional support comes from the National Science Foundation, Nokia, Tekes, Rutgers University's WINLAB, the University of California Transportation Center and the Volvo Center of Excellence for Future Urban Transport at UC Berkeley's Institute of Transportation Studies.
About Nokia Research Center
Nokia Research Center (NRC) looks beyond Nokia's existing business and product development to challenge current strategies and to stimulate renewal in the company's direction. Working closely with all Nokia business units, NRC's research explores new frontiers in digital services, physical-digital connections, human interaction, data and content technologies, device architecture, and access and connectivity. NRC promotes open innovation by working on research projects in collaboration with universities and research institutes around the world. For more information, see our website: http://research.nokia.com.
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