Extracting Activity-travel Diaries from GPS Data: Towards Integrated Semi-automatic Imputation

This paper presents an integrated approach to extracting activity-travel diaries from GPS data. The imputation involves a semi-automatic procedure of transportation mode and activity type recognition, and applies full and partial consistency principles to different trip episodes of a tour. Complementing earlier work on the evaluation of this approach at the epoch level, this paper investigates the performance of the integrated imputation at the episode level. The originally imputed data were used as reference to compare the superimposed data against validated data. Results indicate that the distribution of transportation modes and activity types are similar for these data sets. The new algorithm imputes diary data that are closer to the validated data that the results of the original algorithm.