Relational time-space data structure to enable strategic de-confliction with a global scope in the presence of a large number of 4D trajectories

Abstract

This paper introduces an innovative framework for the design and implementation of new ATM decision support tools for strategic de-confliction. The main key implementation aspects to support an efficient state space analysis of more than 4000 4D Trajectories in the entire European ATM is described. The paper focuses on the innovative aspects developed to improve Spatial Data Structures, i.e. the paper focuses on the new Relational Space Data Structures and Time-Space Data Structures concepts, that allow supporting strategic Conflict Detection (CD) between a large number of 4D trajectories and a wide airspace region. Results have been tested in the WP-E project STREAM, whose aim is to coordinate the entire European ATM traffic at strategic and tactical levels, thus requiring the processing of large number of trajectories under heavy traffic conditions. The new and efficient CD algorithms presented in this paper may contribute to increase airspace capacity in the SESAR framework for the period up to 2020.

Research on Airspace Conflict Detection Method Based on Spherical Discrete Grid Representation

“…Jardin M [7] proposed a CD algorithm based on a four-dimensional spatial and temporal grid to represent aircraft trajectories in airspace, which determines whether there is a conflict by checking grid occupancy. S. Ruiz et al [8] proposed a CD algorithm based on spatial data structure by storing the trajectory information in a square grid space and using a conflict detection method based on correlated spatial data structure as well as a CD method based on spatio-temporal data structure to achieve fast CD; Kuenz A [9] proposed a new 4D airspace modeling method that combines traffic, weather, restricted areas and other objects in 4D airspace for CD and disambiguation. Miao S et al [10] proposed a new multi-level grid spatio-temporal index for a new low-altitude flight CD algorithm; Liu ZQ et al [11] proposed a method to characterize the conflicting airspace based on the earth profile grid model and calculate the conflicting airspace using a multinomial tree structure; Gong W et al [12] proposed a raster model-based airspace CD and deconfliction technique and established a numerical model of airspace conflict; Sui D et al [13] established a deterministic CD and deconfliction module, used the R-tree algorithm with low time complexity to effectively reduce the number of comparisons between aircraft 4DTs, and proposed a Monte Carlo tree search algorithm; Cai M et al [14] proposed a method to determine the airspace conflict by using the GJK algorithm to transform the airspace grid (AG) set into a coordinate set and by judging the inclusion relationship between the Minkowski difference set and the coordinate origin.…”

Unmanned Aerial Vehicle conflict detection based on spatiotemporal data grid

“…Therefore, there is a need to find methods for conflict detection that make more efficient use of memory for a given computer memory limit.As shown in the figure3, since the total number of grid cells in the studied airspace is much larger than the number of coordinates used by all aircraft, most of the storage locations in the TSDS are null and are not used to store information about aircraft. Based on this situation, in order to reduce the memory required by TSDS during the process of performing conflict detection, the Relational Time-Space Data Structure (RTSDS) is proposed by creating two different linear storage tables for managing the information[13] . As shown in the figure4, one of the storage tables is used to store the basic structure of the TSDS, i.e., the information of the four-dimensional space-time grid cells of the studied airspace; the other storage table is used to store the non-space-time information of the trajectory, and the information between the two storage tables is related to each other by pointers.…”