{"id":439,"date":"2011-04-13T15:23:42","date_gmt":"2011-04-13T15:23:42","guid":{"rendered":"http:\/\/transportsdufutur.ademe.fr\/?p=439"},"modified":"2015-07-21T16:37:25","modified_gmt":"2015-07-21T16:37:25","slug":"outil-predictif-de-trafic-par-ibm","status":"publish","type":"post","link":"https:\/\/transportsdufutur.ademe.fr\/2011\/04\/outil-predictif-de-trafic-par-ibm.html","title":{"rendered":"Outil pr\u00e9dictif de trafic par IBM"},"content":{"rendered":"\n

IBM’s Smarter Transportation portfolio covers myriad solutions, ranging from baggage management at airports to customer loyalty analytics. That said, we all know from experience that most travel and transport systems have tremendous room for improvement. Commutes can be a daily source of frustration for many, and with more and more cars on the roads, figuring out the best way to get to and from work each day can be quite the science. And in fact, we’re learning it is a science indeed.<\/p>\n

That’s why IBM Research is collaborating with the California Department of Transportation (Caltrans) and the Institute of Transportation Studies (ITS) at UC Berkeley. Combining street sensor data from Caltrans with the road smarts of ITS, IBM predictive analytics can play a key part in delivering traffic information to everyday commuters. IBM’s Traffic Prediction Tool delivers commuters traffic information about their specific routes 30 – 40 minutes before they even get into their cars.<\/strong> You can learn all about it in this video, featuring lead IBM researcher on the project, John Day.<\/p>\n