<p>Efficient and fast access to big geostreaming data in the road network space requires an efficient spatiotemporal index. Although a few spatiotemporal index methods consider the distribution of spatiotemporal objects along with the road network, these methods are difficult to balance data update and retrieval costs. To solve the existing problem, we propose a time hierarchical network temporal (T-HNT) index method for geostreaming data. The T-HNT index consists of three major components: time partitioning the table component, the spatial index component (HN-tree), and the temporal index component (B+-tree). The core idea of constructing the T-HNT index is as follows: First, the lifespan of the spatiotemporal dataset is partitioned into a sequence of time intervals; then the spatiotemporal dataset in each time interval is hierarchically partitioned and generates the balanced tree structure for the number of objects. Finally, a B+-tree is constructed to index the temporal information. By leveraging the T-HNT index, the optimizing update and spatiotemporal query algorithm are presented, which are empirically evaluated using the synthetic and real-world datasets and several state-of-the-art spatiotemporal indexes. The experimental results demonstrate that the T-HNT outperforms existing methods.</p>