  Human mobility similarity comparison plays a critical role in mobility
estimation/prediction model evaluation, mobility clustering and mobility
matching, which exerts an enormous impact on improving urban mobility,
accessibility, and reliability. By expanding origin-destination matrix, we
propose a concept named mobility tableau, which is an aggregated tableau
representation to the population flow distributed between different location
pairs of a study site and can be represented by a vector graph. Compared with
traditional OD matrix-based mobility comparison, mobility tableau comparison
provides high-dimensional similarity information, including volume similarity,
spatial similarity, mass inclusiveness and structure similarity. A novel
mobility tableaus similarity measurement method is proposed by optimizing the
least spatial cost of transforming the vector graph for one mobility tableau
into the other and is optimized to be efficient. The robustness of the measure
is supported through several sensitive analysis on GPS based mobility tableau.
The better performance of the approach compared with traditional mobility
comparison methods in two case studies demonstrate the practicality and
superiority, while one study is estimated mobility tableaus validation and the
other is different cities' mobility tableaus comparison.
