Prediktioner av andelen personer som går respektive cyklar till jobbet: resvaneundersökningar i kombination med geografiskt högupplösta registerdata

Gunnar Isacsson

The Swedish Transport Administration has recently developed a tool (“GC-kalk”) for assessing investments in the infrastructure for walking and bicycling. These assessments are inter alia based on the number of individuals that walk or bicycle before the investment. This report uses the Swedish national travel survey combined with register based (administrative) data with high geographic resolution to generate predictions of the number of people walking or cycling to work in a small geographic area. The basic problem is that the register based material that includes the entire Swedish population and all work places does not include information about mode of transport for the journey to work. Therefore the travel survey is used to fill in this information. A main question of this report concerns the quality of predictions on mode choice that you get from a model estimated on a national travel survey. Therefore a set of models are evaluated by cross validation based on the so-called “bootstrap” method. This method also implies that the uncertainty in mode choice predictions that depend on the sample variation in the travel survey easily can be simulated for all individuals in the register based data. The results suggest that the quality of predictions derived from the model that gives the best predictions at the national level vary across different counties. The chosen model is also used to illustrate how predictions of the shares of individuals walking or bicycling to work in a small area can be generated. In addition, the report discusses how the uncertainty in individual predictions can be used to consider other available information when the number of persons walking or bicycling shall be assessed in a specific situation and in a specific origin-destination pair.



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