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Vehicle reidentification with Bluetooth signal data has emerged as an effective and economical means for collecting traffic data including origin–destination (O-D) information, which is crucial for transportation planning. Direct vehicle tracking based on time-lapse aerial photography (TLAP) is also increasingly used for O-D studies. Neither technique has previously been validated, so the objective of this study was to validate O-Ds generated by using both techniques against a ground-truth O-D. Traffic volume–, Bluetooth-, and TLAP-based O-D data collected at an interchange in Madison, Wisconsin, were used in this study. Significant variability (2.3% to 7.2%) in Bluetooth match rates was observed for the 12 O-D pairs of the interchange, which were calculated by using a heuristic measure of the difference between traffic volumes (the GEH formula). Uniproportional scaling of the sample Bluetooth O-D (using the average detection rate) resulted in poor fit to the true O-D, but biproportional factoring (Fratar or Furness procedure) resulted in about 85% of the movements’ having a GEH statistic less than 5. Combining Bluetooth data from multiple days resulted in a better fit than the use of a single day's data. The analysis showed that Bluetooth technology could be used to obtain representative O-D information of an access-controlled network for planning applications. TLAP sample O-D data were scaled with an origin-specific factor and resulted in reasonable fit to the true O-D data. Biproportional factoring resulted in a better fit in which 100% of the movements had a GEH value less than 5. Therefore, biproportional factoring is also recommended for TLAP data.
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