Using public transport tap-in data to improve a travel demand model: A Norrköping case study

University essay from Linköpings universitet/Kommunikations- och transportsystem; Linköpings universitet/Tekniska fakulteten

Abstract: With reliable models to forecast travel demand, traffic planners and decision-makers can be assisted in choosing the best solutions to obtain traffic performance goals. Practitioners have traditionally been relying on infrequent, costly and respondent pressurized travel surveys as their main source of data for these models. The drawbacks of the data collection method highlight a need to search for alternative sources of data used for the purpose. One such source is public transport “tap-in” data. This thesis executed a case study with the target of improving the travel demand model of Norrköping via public transport data. An algorithm that estimates the alighting station of travellers was applied to a data set provided by the public transport operator of the city. By allocating the OD-demand from stations to the traffic analysis zones used in the model a straightforward integration method using the tap-in estimate as a reference matrix could be used. The target with the method was to redistribute the demand in such a way that the public transport demand approached the tap-in estimate but that the total demand for all modes for the OD-pair remained unchanged. The results gave some indication that the integration of tap-in data improved the model performance from the perspective of public transports. In a regression analysis comparing the number of entries per station the integration of tap-in data increased the correlation coefficient from 0,845 to 0,864. Further was the performance for other transport modes seemingly not worsened by the integration of tap-in data. Finding an allocation procedure that was generic but still accurate proved complex. Further were drawbacks with the integration procedure highlighted where the method executed affected the results of the model, not its behaviour. The consequence of this is that, though the model might be an accurate representation of the current state of traffic, it is difficult to execute the same procedure when investigating future states. Still, the thesis stressed some of the potential for public transport data in modelling contexts, where the role of the data, given the procedure executed, still is of complementary character to travel surveys.

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