Centre National Detudes Spatiales

Continental Automotive Gmbh

M3 Systems

Continental Automotive France

Continental Automotive Technologies Gmbh

Institut Superieur De L'aeronautique Et De L'espace

Willy Vigneau

Lionel Ries

Nabil Jardak

François-Xavier Marmet

Lucien Garcia

Philippe Paimblanc

Nabil Kbayer

Anchalee Puengnim

Benjamin Rollet

Vincent Calmettes

Stéphanie Bidon

Jean-Rémi De Boer

Olivier Desenfans

A method for determining a speed limit on a road segment on which a vehicle is travelling, including steps of obtaining a first speed limit by querying a geospatial database on the basis of a geographical location of the vehicle, of determining a confidence index associated with the first speed limit, of determining a second speed limit by analyzing at least one image obtained from a sensor of the vehicle, of determining a confidence index associated with the second speed limit, of selecting the speed limit associated with the highest confidence index, and of configuring an item of equipment of the vehicle on the basis of the speed limit associated with the highest confidence index.

Method, device and server for determining a speed limit on a road segment

Subjects of the present disclosure are methods for training deep learning models, methods for predicting a map matching parameter, methods for updating a digital road map, and a computer program making it possible to implement the methods and devices for updating a digital road map. The general principle is based on the use of machine learning. Accordingly, a statistical deep learning model is trained according to a 'supervised' machine learning scheme. Thereafter, the pretrained statistical deep learning model is used to predict a map matching parameter on the basis of a measurement of geographic coordinates and of an identifier of the position sensor that has performed the measurement of geographic coordinates. Finally, the map matching parameter can be used to update a digital road map.

Prediction of a cartographic readjustment parameter by deep learning

Locating a vehicle to be located (V), which has at least a GNSS receiver, via a location system including at least a computer by: receiving a message that includes at least a GNSS signal and that is transmitted by the vehicle to be located (V), receiving a message that is transmitted by at least one located vehicle (V), which has a GNSS receiver, the message including a location of the vehicle, the location being associated with a high confidence level, and a GNSS signal generated by the GNSS receiver of the vehicle, determining a location of the vehicle to be located, on the basis of the location of at least one located vehicle (V), the GNSS signal from the located vehicle, and the GNSS signal from the vehicle to be located, and transmitting the determined location to the vehicle to be located (V).

Location method using GNSS signals

A GNSS receiver and the associated method, for calculating an unbiased position and time measurement from a plurality of satellite positioning signals, the receiver comprising: A GNSS receiver further comprising a second computer logic configured to calculate a second unbiased position and time from the first position and time, and the second signal processing signals.

GNSS receiver with an improved capability to resolve sub-carrier tracking ambiguities

A GNSS receiver comprising a circuit configured to receive a positioning signal comprising a carrier modulated by a subcarrier and a PRN code; a subcarrier and code tracking loop, comprising a first discrimination circuit, configured to calculate a first pseudo range from said received positioning signal and a first reference signal; a code tracking loop, comprising a second discrimination circuit, configured to calculate a second pseudo range from said received positioning signal and a second reference signal; and a calculation circuit configured to evaluate a difference between said first pseudo range and said second pseudo range, and to modify the output of the first discrimination circuit accordingly. The invention further addresses a method for calculating a pseudo-range in such a GNSS receiver.

Device for tracking a satellite radionavigation signal in a multipath environment

A receiver, and associated process, for tracking a GNSS positioning signal comprising a carrier modulated by a subcarrier and a spreading code, the receiver comprising:

GNSS receiver calculating a non-ambiguous discriminator to resolve subcarrier tracking ambiguities

A radionavigation signal tracking device comprises a first and a second tracking stage for radionavigation signals. The first tracking stage comprises a first carrier phase-locked loop. The latter produces a first error signal arising from a phase difference between the first carrier and its replica. The phase of the replica of the first carrier is adjusted with the first error signal. The second tracking stage comprises a second carrier phase-locked loop. The latter produces a second error signal arising from a difference between the first phase difference and a phase difference between the second carrier and the replica thereof. The phase of the replica of the second carrier is adjusted with the first and second error signals.

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Muret, France

Willy Vigneau