Predicting freeway traffic states is, so far, based on predicting speeds or traffic volumes with various methodological approaches ranging from statistical modeling to deep learning. Traffic on freeways, however, follows specific patterns in space-time, such as stop-and-go waves or mega jams....

Road traffic jams are a major problem in most cities of the world, resulting in massive delays, increased fuel wastage, and monetary and productivity losses. Unlike conventional computer networks, which experience congestion due to excessive traffic, road transportation networks can experience...

Time scarcity is one of the strongest correlates of fast food consumption. To estimate the causal effect of time lost on food choice, we match daily store-specific foot traffic data traced via smartphones to plausibly exogenous shocks in highway traffic data in Los Angeles. We find that on days...

The COVID-19 pandemic has been posing unprecedented challenges for the transport sector. Urban travel has declined all over the world, but not uniformly for all modes; public transportation has taken the hardest blow. As a result, there has been a widespread reduction in public transport...

Ride-hailing applications create new challenges for governments providing transit services, but also create new opportunities to raise tax revenue. To shed light on the effect of taxing or subsidizing ride-hailing applications, we extend a pseudo-monocentric city model to include multiple...