One of the many interesting tidbits I learned from reading Jon Gertner’s The Idea Factory earlier this year is that the genius physicist John Van Vleck was always allowed to ride the nation’s passenger trains for free after helping the railroad industry perfect its schedule for maximum efficiency. (For whatever reason, he became obsessed with rail schedules when he was just seven.) Of course, transportation of all types is a target of improvement in the era of Big Data. From Doug Newcomb in Wired:

“IBM is testing the new traffic-management technology in a pilot program in Lyon, France, that’s designed to provide the city’s transportation engineers with ‘real-time decision support’ so they can proactively reduce congestion. Called Decision Support System Optimizer (DSSO), the technology uses IBM’s Data Expansion Algorithm to combine old and new data to predict future traffic flow. Over time the system ‘learns’ from successful outcomes to fine-tune future recommendations.

The company’s technology allows traffic engineers to quickly take action based on constantly updated information, such as putting detours in place or providing alternative routes to get traffic moving after a snag. They’re unable to do this now, according to IBM, since most metro traffic management centers rely only on video feeds and color maps showing real-time traffic conditions. Jurij R. Paraszczak, director of Smarter Cities IBM Research, says this means traffic engineers don’t have a ‘360-degree view’ of traffic, and depending on predefined responses or making reactive decisions, they don’t always fully take into account all current and future patterns.

‘Rather than pulling all the data together and displaying it in one place where people make decisions on to what to do with it, the idea is to pull the data, display it and then provide tools to drive what-ifs,’ Paraszczak told Wired. ‘The idea is to help them make decisions.'”