Objective
Automatic and driverless vehicles do operate already, making use of anti-collision devices which enable their perfectly safe movings. But currently, most of these systems are guided by railways, fiberglass or magnetic wires.
More recently, a few demonstrations have been undertaken in order to demonstrate the capabilities of satellite based navigation systems to clear the roads from such heavy infrastructures. Particularly, ROBOSOFT and M3SYSTEMS designed several transportation platforms which guidance was based on Differential GPS hybridized with inertial systems. Although such vehicles are operational today, their GNSS based navigation equipment are seen as being very expensive for allowing a larger vehicle deployment. Moreover, the vehicles have to go very slowly when going along buildings as soon as ‘light’ canyoning effects are observed. As a result, pilot users explained they were not confident enough in the reliability of the service they got.
In this context, the TAXISAT project aims at developing a driverless GNSS based taxi application capable to operate cost effectively, safely and with a high reliability within private circumscribed sites whatever their topographic configurations are.
Indeed, the TAXISAT consortium is convinced that considerable gains could be achieved with the new EGNOS and GALILEO capabilities in order to reach the 1-meter accuracy positioning asked for the sake of transportation safety, while making use of future mass market GNSS systems.
The current GPS receiver developed by M3SYSTEMS will be improved through the development of specific EGNOS/EDAS processing filters and the hybridation with SLAM video in masked areas. The use of the “the expected path of the vehicle” will also be used to improve the navigation filter performance.
The TAXISAT service will be integrated and tested in real conditions for a few weeks on one or two sites of demonstration. Experimentations with the IOV GALILEO signals will be also conducted.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Call for proposal
FP7-GALILEO-2011-GSA-1-b
See other projects for this call
Funding Scheme
CP - Collaborative project (generic)Coordinator
64210 Bidart
France