Using machine learning to build maps that give smarter driving advice

If you drive in the United States, chances are you can't remember the last time you bought a paper map, printed out a digital map, or even stopped to ask for directions. Thanks to Global Positioning System (GPS) and the mobile mapping apps on our smartphones and their real-time routing advice, navigation is a solved problem. If you live in a place like Doha, Qatar, where the length of the road network has tripled over the last five years, commercial mapping services from Google, Apple, Bing, or other providers simply can't keep up with the pace of infrastructure change. "Each one of us who grew up in Europe or the US probably cannot understand the scale at which these cities grow," says Rade Stanojevic, a senior scientist at the Qatar Computing Research Institute (QCRI), part of Hamad Bin Khalifa University, a Qatar Foundation university, in Doha. "Pretty much every neighborhood sees a new underpass, new overpass, new large highway being added every couple of months." As Qatar copes with this rapid growth--and especially as it prepares to host the FIFA World Cup in 2022--the bad routing advice and accumulating travel delays from outdated digital maps is increasingly costly. That's why Stanojevic and colleagues at QCRI decided to try applying machine learning to the problem. A road network can be interpreted as a giant graph in which every intersection is a node and every road is an edge, says Stanojevic, whose specialty is network economics. Road segments can have both static characteristics, such as the designated speed limit, and dynamic characteristics, such as rush-hour congestion. To see where traffic really is going--rather than where an old map says it should go--and then predict the best routes through an ever-changing maze, all a machine-learning model would need is lots of up-to-data data on both the static and dynamic factors. "Fortunately enough, modern vehicle fleets have these monitoring systems that produce quite a lot of data," says Stanojevic.