During Smart City Expo and World Congress, IBM (NYSE: IBM) and the City of Lyon, France, today, Nov. 14, announced an 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.
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.
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, says IBM.
Using software from IBM, actionable historical and real-time traffic data from the City of Lyon is combined with advanced analytics and algorithms to help model predicted conditions under both normal and incident conditions, and the resulting impact across the entire network of roads, buses and trams.
The system can also be used to estimate drive times and traffic patterns in a region more accurately and in real-time, says IBM.