With the various smart city initiatives being developed around the globe, a common challenge is to enable strategic decisions about planning and managing the flow of traffic in highly populated, often traffic-laden mobility networks involving roads, cycle paths, and public transportation on rails for example. The increased ability to track traffic opens new opportunities to plan for better efficiency of the mobility networks but also to react better in the case of an unanticipated accident. Analytical methods are needed that allow finding mobility bottlenecks and traffic hotspots.
In this use case we exploit a dataset comprising the journeys of almost two hundred million taxi journeys, which happened in New York City over the course of several years. We examine how Transcendental Information Cascades can be used to expose the flow of traffic within an urban environment. We will focus on the analysis of historic data but we will also feed in synthetic data to demonstrate how our method can be used to simulate problematic situations in order to increase resilience.
We can see an increasing number of examples where humans contribute to large-scale collective action by sharing information online. This can be in case of a disastrous event (e.g. the Haiti earthquake) or political crisis (e.g. the Kenyan election). These examples have in common that even though there is some common topic or goal hovering above the information sharing activities of the individuals (e.g. coordinating help in disaster response or optimizing travel routes of people being affected by traffic disruptions) people are not necessarily talking with each other. They are just talking out loudly about the same thing (especially in critical situations when time to make decisions is rare). This suggests that there exists unintended collective action that is the substrate of the accumulated information sharing behaviour of individuals.
With Transcendental Information Cascades we provide a method to capture a macroscopic view to the various streams of information that happen online around a particular topic (e.g. information around the most recent Ebola outbreak on Ushahidi and Twitter). Some of these streams might be polluted with misinformation or just uninformative spam (e.g. tasteless jokes about Ebola) making it hard to extract useful messages . It is necessary for stakeholders involved in aid work to coordinate the own useful information away that it can gain awareness.