Digitalization in the Service of Society: The Case of Big Vehicle Trajectory Data.

The ongoing, sweeping digitalization of societal processes generates massive volumes of data that capture the underlying processes at an unprecedented level of detail, in turn enabling us to better understand and improve those processes. Put differently, if harnessed properly, data holds the potential to enable value creation throughout society.

Considering primarily vehicle trajectory data, this talk put focus on the important process of transportation: While we all depend on it for mobility, transportation has adverse effects on (i) our productivity due to lack of predictability and congestion, (ii) the climate due to greenhouse gas emissions, and (iii) our health and safety due to air and noise pollution and accidents. Thus, it makes good sense to invent techniques capable of leveraging big data for the improvement of transportation.

The talk describes how the availability of massive trajectory data renders the traditional routing paradigm, where a road network is modeled as an edge-weighted graph, inadequate. Instead, new paradigms that thrive on massive trajectory data are called for. The talk covers several such paradigms, including path-centric, on-the-fly, and cost-oblivious routing [2, 3, 4, 10, 11, 12]. As even massive volumes of trajectory data are sparse in these settings, the talk also covers means of making good use of available data [6, 7, 13]. Finally, trajectory data has many uses beyond routing—the talk covers several such uses [1, 5, 8, 9].