BARCELONA, Spain, Nov. 14, 2012 /PRNewswire/ -- During Smart City Expo and World Congress, IBM (NYSE: IBM) and the City of Lyon, France, today announced a first-of-a-kind analytics technology that brings new intelligence to the city's transportation management center. The pilot gives transportation engineers real-time decision support on steps to reduce traffic congestion and enable faster incident response time when an unexpected event occurs. (Logo: http://photos.prnewswire.com/prnh/20090416/IBMLOGO ) Proactively managing the resulting traffic congestion means travelers spend less time stuck in a traffic jam because detours can be put into place quickly and more accurate alternate route suggestions help citizens get back on their way sooner. IBM researchers are piloting a system with the City of Lyon which will be used to help traffic operators in its transportation management center evaluate an incident and make more informed assessments about which actions would restore traffic flow. Using real-time traffic data, the new analytics and optimization technology can help officials predict outcomes and analyze different scenarios to resolve problems. For example, recommended actions could be adjusting traffic signals to allow cars to detour more quickly and to allow for emergency vehicles to enter, adjusting ramp metering or road closures or changing variable message signs to alert of trouble ahead. "As the city of Lyon strives to improve mobility for its citizens and become a leader in sustainable transportation, piloting this analytics technology will help the city anticipate and avoid many traffic jams before they happen and lessen their impact on citizens," said Gerard Collomb, Senator Mayor of Lyon. "Using the data that we are collecting to make more informed decisions will help us to promote about how to resolve unexpected traffic events and optimize public transportation that is becoming a credible alternative to the use of private cars." Traffic management centers have sophisticated video walls and color maps of real-time traffic that can integrate different streams of traffic data, but do not provide full situational awareness across the transportation network. Today, command center officials use predefined response plans or make decisions on the fly. Neither method allows traffic operators to factor current and future traffic patterns into their decision-making process.