095 - Exploitation of Geo-spatial Data for Automated Vehicles

095 - Exploitation of Geo-spatial Data for Automated Vehicles


The provision of ubiquitous, high-quality, positioning, navigation, and timing information, and the full situation awareness of the environment, belong to the main challenges for Connected, Cooperative and Automated Vehicles (CCAV), that need to be countered in the future. 


Geo-spatial datasets capturing the topographic surface of the Earth and its overlying features, such as building and roads, can provide information not only for the static environment surrounding a moving agent, but also to assist the navigation engine into providing accurate and trust-worthy position fixes. Several research works have demonstrated the value of incorporating height information provided by Digital Elevation Models (DEMs). 


Road Network (RN) data, on the other hand, comprise already an important element of commercial in-vehicle navigations units, and in conjunction with map-matching algorithms can reduce the accuracy of GNSS position fixes down to the road-level (i.e., 2-5m), even in deep-urban environments. Finally, pre-computed 3D Building Models (3DBMs), ray-tracing and feature matching algorithms offer the unique opportunity of exploiting (instead of detecting and excluding) Non-Light-Of-Sight (NLOS) measurements for positioning purposes, thus eliminating the last critical barrier that degrades the performance of GNSS receivers in challenging environments (i.e., urban and deep-urban). 


The objective of this activity is to define and demonstrate the exploitation of Geo-spatial data for Connected, Cooperative and automated vehicles, and identify the key enabling technologies, together with their maturity state, for its realisation. The main innovation element of this activity will be the detection, and more importantly cost effective and computationally efficient exploitation of heavily biased GNSS measurements for accurate positioning in urban/deep-urban environments, with the aid of a multitude of geo-spatial datasets.

The tasks to be performed shall include:

  • User-terminal algorithms are to be developed for the computationally efficient consumption of geo-spatial datasets by the positioning engine. Existing European space assets (e.g., Copernicus mission), but also novel imaging/reconstruction techniques for the generation of relevant geo-spatial products that can be upscaled to future ESA missions are to be considered.


The main outputs of the activity will consist of:

  • Survey of state of the art on geo-spatial data products generation methods and instruments
  • An end-to-end software emulator of the overall high-accuracy service
  • Roadmap for large scale service provision of geo-spatial data products for positioning applications