Trip Oriented Search on Activity Trajectory

Driven by the flourish of location-based services, trajectory search has received significant attentions in recent years. Different from existing studies that focus on searching trajectories with spatio-temporal information and text de-scriptions, we study a novel problem of searching trajectories with spatial distance, activities, and rating scores. Given a query q with a threshold of distance, a set of activities, a start point S and a destination E, trip oriented search on activity trajectory （TOSAT） returns k trajectories that can cover the activities with the highest rating scores within the threshold of distance. In addition, we extend the query with an order, i.e., order-sensitive trip oriented search on activity trajectory （OTOSAT）, which takes both the order of activities in a query q and the order of trajectories into consideration. It is very challenging to answer TOSAT and OTOSAT e？ciently due to the structural complexity of trajectory data with rating infor-mation. In order to tackle the problem e？ciently, we develop a hybrid index AC-tree to organize trajectories. Moreover, the optimized variant RAC＋-tree and novel algorithms are introduced with the goal of achieving higher performance. Extensive experiments based on real trajectory datasets demonstrate that the proposed index structures and algorithms are capable of achieving high e？ciency and scalability.

New reference trajectory optimization algorithm for a flight management system inspired in beam search

With the objective of reducing the flight cost and the amount of polluting emissions released in the atmosphere, a new optimization algorithm considering the climb, cruise and descent phases is presented for the reference vertical flight trajectory. The selection of the reference vertical navigation speeds and altitudes was solved as a discrete combinatory problem by means of a graphtree passing through nodes using the beam search optimization technique. To achieve a compromise between the execution time and the algorithm＇s ability to find the global optimal solution, a heuristic methodology introducing a parameter called ‘‘optimism coefficient was used in order to estimate the trajectory＇s flight cost at every node. The optimal trajectory cost obtained with the developed algorithm was compared with the cost of the optimal trajectory provided by a commercial flight management system（FMS）. The global optimal solution was validated against an exhaustive search algorithm（ESA）, other than the proposed algorithm. The developed algorithm takes into account weather effects, step climbs during cruise and air traffic management constraints such as constant altitude segments, constant cruise Mach, and a pre-defined reference lateral navigation route. The aircraft fuel burn was computed using a numerical performance model which was created and validated using flight test experimental data.

Efficient Similarity Search Based on Semantic Trajectories in Road Networks

In recent years, a few researches focus on the similarity measure of semantic trajectories in road networks, since semantic trajectories in road networks have smaller volumes, higher qualities and can better reflect user behaviors. However, these works do not further discuss how to efficiently search similar trajectories. Thus, to implement an efficient similarity search, we design an index called SIET based on the structures of road networks. Then, we propose a novel algorithm called SSN-BF to search similar trajectories efficiently by using best-first strategy. At last, we take the experimental evaluations on real dataset and prove the efficiency of our algorithm.