Abstract: A method for estimating a precise position of a vehicle on a map includes acquiring at least one geolocated position of the vehicle by way of a geolocation system, pre-positioning the vehicle on the map, and particle filtering in which possible positions of the vehicle, called particles are processed. The particle filtering includes distributing particles on the map, and then updating the particles on the map, calculating the likelihood of each particle, selecting a limited set of particles, and, if an indicator relating to the likelihood of the selected particles and to the number of selected particles drops below a threshold, resampling particles on the map.

Abstract: A method for selecting a restricted or empty set of hypotheses of possible positions of a vehicle from among a plurality of hypotheses includes acquiring a geolocated position of the vehicle by a geolocation system, acquiring a plurality of hypotheses of possible positions of the vehicle, determining a covariance of the geolocated position of the vehicle and a covariance of each acquired hypothesis, calculating, for each acquired hypothesis, a Mahalanobis distance as a function of the covariance of the geolocated position of the vehicle and of the covariance of the hypothesis, and selecting a restricted or empty set of hypotheses from among the acquired hypotheses, as a function of each calculated Mahalanobis distance.

Abstract: A method for estimating a precise position of a vehicle on a map includes acquiring at least one geolocated position of the vehicle by way of a geolocation system, pre-positioning the vehicle on the map, and particle filtering in which possible positions of the vehicle, called particles are processed. The particle filtering includes distributing particles on the map, and then updating the particles on the map, calculating the likelihood of each particle, selecting a limited set of particles, and, if an indicator relating to the likelihood of the selected particles and to the number of selected particles drops below a threshold, resampling particles on the map.

Abstract: The present invention relates to a method for creating a correspondence between the local time of a first machine (B), having a first clock (HB), and that of a second machine (A), having a second clock (HA). The invention also relates to a method of synchronization between data recorded and date stamped by said first machine (B) with respect to the local time of said second machine (A). In order to make it more flexible and robust, this method does not comprise a synchronization of said clocks (HA, HB), but is based on the establishment of a correspondence ‘by intervals’ between the times that they indicate. In order to establish correspondence, a non-monotonic temporal reference may be formed by the clock of a synchronous bus connecting, at least temporarily, the two machines (and possibly other devices).

Abstract: The present invention relates to a method for creating a correspondence between the local time of a first machine (B), having a first clock (HB), and that of a second machine (A), having a second clock (HA). The invention also relates to a method of synchronization between data recorded and date stamped by said first machine (B) with respect to the local time of said second machine (A). In order to make it more flexible and robust, this method does not comprise a synchronization of said clocks (HA, HB), but is based on the establishment of a correspondence ‘by intervals’ between the times that they indicate. In order to establish correspondence, a non-monotonic temporal reference may be formed by the clock of a synchronous bus connecting, at least temporarily, the two machines (and possibly other devices).