City-Scale Synthetic Individual-level Vehicle Trip Data
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The trip data that records each vehicle's trip behavior on the road network describes the operation of urban traffic from the perspective of individuals and is extremely valuable for transportation research. However, restricted by data privacy, the trip data of individual-level cannot be opened for all researchers, while the need for it is very urgent. In this paper, we produce a city-scale synthetic individual-level trip data by regenerating for all individuals based on their historical trip data. The availability and trip data privacy protection are balanced during generation, making the synthetic dataset remains valuable and can be opened. A series of experiments were done to verify the reliability of the dataset. The result shows that the synthetic data is consistent with the real data at the aggregated level. Further, the trip behaviors of individuals indicated by the trip data from the individual perspective are reasonable.
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