  Trip data that records each vehicle's trip activity on the road network
describes the operation of urban traffic from the individual perspective, and
it 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 vehicle trip dataset by generating for
each individual based on the historical trip data, where the availability and
trip data privacy protection are balanced. Privacy protection inevitably
affects the availability of data. Therefore, we have conducted numerous
experiments to demonstrate the performance and reliability of the synthetic
data in different dimensions and at different granularities to help users
properly judge the tasks it can perform. The result shows that the synthetic
data is consistent with the real data (i.e., historical data) on the aggregated
level and reasonable from the individual perspective.
