Estimation of Daily Modal Shares for Cities

This contribution describes an approach to estimate the modal share in the city of Cologne on a daily basis which is in contrast to travel demand surveys which are typically used and conducted in frequencies of many years. To accomplish this, it uses a diverse set of input data which are often available in cities: most notably the complete data-base of all traffic detectors in Cologne (loop detectors, but also pedestrian and public transport activation, and dedicated bicycle counters) and the data from a mobile phone provider. These data are cleaned, merged, and then used to estimate the daily number of trips by feet, bicycle, car, or public transport, respectively. This contribution describes the methods and algorithms of this modal share estimation, as well as selected results from the meanwhile two-year application period which show reasonable and promising outcomes concerning periodic fluctuations as well as event-related variations.