A device implementing a system for estimating device location includes at least one processor configured to receive a first and second set of signals, each set corresponding to location data and being received based on a sampling interval. The at least one processor is configured to, for each sampling period defined by the sampling interval, obtain sensor data corresponding to device motion during the sampling period, determine an orientation of the device relative to that of the vehicle based on the sensor data, calculate a non-holonomic constraint based on the orientation of the device relative to that of the vehicle such that the non-holonomic constraint is iteratively updated, and estimate a device state based on the non-holonomic constraint.

A device implementing a system for estimating device location includes at least one processor configured to receive a first and second set of signals, each set corresponding to location data and being received based on a sampling interval. The at least one processor is configured to, for each sampling period defined by the sampling interval, obtain sensor data corresponding to device motion during the sampling period, determine an orientation of the device relative to that of the vehicle based on the sensor data, calculate a non-holonomic constraint based on the orientation of the device relative to that of the vehicle such that the non-holonomic constraint is iteratively updated, and estimate a device state based on the non-holonomic constraint.

A method of navigating with a global navigation satellite system (GNSS) includes receiving a GNSS signal, calculating a GNSS navigation solution according to the GNSS identifying map information corresponding to the GNSS navigation solution, detecting features from the identified map information, and correcting a GNSS navigation based on the features detected from the map information and the GNSS signal.

A method of navigating with a global navigation satellite system (GNSS) includes receiving a GNSS signal, calculating a GNSS navigation solution according to the GNSS identifying map information corresponding to the GNSS navigation solution, detecting features from the identified map information, and correcting a GNSS navigation based on the features detected from the map information and the GNSS signal.

A computer-implemented method of using telematics data at a destination device is provided. The destination device may be a mobile device associated with a driver, or a smart vehicle controller of a destination vehicle. The telematics data is generated by an originating mobile device (i) having a Telematics Application (or “App”), and (ii) associated with a second driver/vehicle, the telematics data including acceleration, braking, speed, heading, and location data associated with an originating vehicle. The telematics data may be broadcast from the originating mobile device to the destination device that (a) analyzes the telematics data received, (b) determines that an abnormal travel condition exists, and (c) automatically take corrective action that alleviates a negative impact of the abnormal travel condition on the destination vehicle to facilitate safer travel. A usage-based or other insurance discount may be provided based upon insured usage of the telematics data-based risk mitigation or prevention functionality.

A computer-implemented method of using telematics data at a destination device is provided. The destination device may be a mobile device associated with a driver, or a smart vehicle controller of a destination vehicle. The telematics data is generated by an originating mobile device (i) having a Telematics Application (or “App”), and (ii) associated with a second driver/vehicle, the telematics data including acceleration, braking, speed, heading, and location data associated with an originating vehicle. The telematics data may be broadcast from the originating mobile device to the destination device that (a) analyzes the telematics data received, (b) determines that an abnormal travel condition exists, and (c) automatically take corrective action that alleviates a negative impact of the abnormal travel condition on the destination vehicle to facilitate safer travel. A usage-based or other insurance discount may be provided based upon insured usage of the telematics data-based risk mitigation or prevention functionality.

A positioning device includes a first GNSS receiver; a communication link configured to receive a spatial position, code measurements and carrier phase measurements of a second GNSS receiver; an input interface to a processing logic, the processing logic being configured to: calculate a position of the first positioning device from communicated data; and to estimate one or more parameters representative of multipath at the position of the first positioning device; wherein the communication link is configured to communicate to a second positioning device the parameters representative of multipath at the position of the first positioning device. Described developments comprise the use of multipath severity indicators, the determination of relative distances between receivers, validity conditions in time and/or space of multipath, various embodiments in a train or in a group of vehicles. Software aspects are discussed.

A positioning device includes a first GNSS receiver; a communication link configured to receive a spatial position, code measurements and carrier phase measurements of a second GNSS receiver; an input interface to a processing logic, the processing logic being configured to: calculate a position of the first positioning device from communicated data; and to estimate one or more parameters representative of multipath at the position of the first positioning device; wherein the communication link is configured to communicate to a second positioning device the parameters representative of multipath at the position of the first positioning device. Described developments comprise the use of multipath severity indicators, the determination of relative distances between receivers, validity conditions in time and/or space of multipath, various embodiments in a train or in a group of vehicles. Software aspects are discussed.

A method for determining the point location of a vehicle stopped on one storage track among a set of storage tracks, using virtual beacons is provided. It determines and compares the likelihood of a plurality of hypotheses as to the stopped location of the vehicle, corresponding to a first set of NBe predefined virtual beacons Be(i), i varying from 1 to NBe, the respective positions of which are known in an amount of one virtual beacon per storage track, by correlating the GNSS geo-positioning signals received at various synchronization reset times of a second set by the GNSS receiver located on board the vehicle with predicted GNSS geo-positioning signals of replicas expected for the various positions of the virtual beacons of the first set at the various times. The detected holding position of the vehicle is the position that corresponds to the maximum likelihood.

A method for determining the point location of a vehicle stopped on one storage track among a set of storage tracks, using virtual beacons is provided. It determines and compares the likelihood of a plurality of hypotheses as to the stopped location of the vehicle, corresponding to a first set of NBe predefined virtual beacons Be(i), i varying from 1 to NBe, the respective positions of which are known in an amount of one virtual beacon per storage track, by correlating the GNSS geo-positioning signals received at various synchronization reset times of a second set by the GNSS receiver located on board the vehicle with predicted GNSS geo-positioning signals of replicas expected for the various positions of the virtual beacons of the first set at the various times. The detected holding position of the vehicle is the position that corresponds to the maximum likelihood.