The calculation of travel time of city roads is an important issue in the domain of the intelligent transportation system research.License plate recognition data is one kind of monitoring data for vehicles running on urban roads

which has some new features

such as high volume

high velocity and spatio-temporal correlation.In order to achieve travel time calculations on massive license plate recognition data collection

we present the formal definition of travel time calculation based on license plate recognition data set

and propose a pipelined parallel computing model based on spatio-temporal data partition.Moreover

the implementation of the computing model is given based on a real-time MapReduce computing system.The corresponding experiments based on real license plate recognition data set show that

the computing performance on million-level data sets of our method can achieve three times increasing compared to traditional travel time calculation methods.Meanwhile our method is more suitable for fine-grained partition and large scale traffic network.