A trajectory can be seen as the imprint left in space by a moving object over time. In recent years, with widespread use of civil GPS and other positioning devices on mobile terminals development popularity location-based services social networks, large amount data is increasingly accumulated daily life served different types applications. generated fields traffic, weather, ecology services. Th...

Trajectory analysis holds many promises, from improvements in traffic management to routing advice or infrastructure development. However, learning users' paths is extremely privacy-invasive. Therefore, there a necessity protect trajectories such that we preserve the global properties, useful for analysis, while specific and private information of individuals remains inaccessible. Trajectories,...

The current commercial intelligent driving systems still take the optimal strategy judged by machine to be only goal. Therefore, in order improve experience of following scene, based on assumption that environmental factors remain unchanged for a short time, five important parameters affecting scene are selected through correlation analysis, and vehicle-following research is carried out. This p...

Existing work repeatedly addresses that the ubiquitous positioning devices will start to generate an unprecedented stream of time-stamped positions leading to storage and computation challenges. Hence the need for trajectory compression arises. The goal of this paper is to estimate the effect of compression in spatiotemporal querying; towards this goal, we present an analysis of this effect and...

Predicting motions of surrounding vehicles is critically important to help autonomous driving systems plan a safe path and avoid collisions. Although recent social pooling based LSTM models have achieved significant performance gains by considering the motion interactions between close each other, vehicle trajectory prediction still remains as challenging research issue due dynamic high-order i...