An earpiece includes an earpiece housing, a processor disposed within the earpiece, a speaker operatively connected to the processor, a microphone operatively connected the processor, and a global navigation satellite system (GNSS) receiver disposed within the earpiece. A system may include a first earpiece having a connector with earpiece charging contacts, a charging case for the first earpiece, the charging case having contacts for connecting with the earpiece charging contacts, and a global navigation satellite system (GNSS) receiver disposed within the charging case.

An earpiece includes an earpiece housing, a processor disposed within the earpiece, a speaker operatively connected to the processor, a microphone operatively connected the processor, and a global navigation satellite system (GNSS) receiver disposed within the earpiece. A system may include a first earpiece having a connector with earpiece charging contacts, a charging case for the first earpiece, the charging case having contacts for connecting with the earpiece charging contacts, and a global navigation satellite system (GNSS) receiver disposed within the charging case.

A control system for a screen of a vehicle includes a global positioning system (GPS), an inertia sensor and a control circuit. The GPS detects a satellite signal from a satellite. The inertia sensor senses motion of the vehicle and correspondingly generates a motion state value. The control circuit performs one of a first determination procedure and a second determination procedure according to the state of the satellite signal. In the first determination procedure, the control circuit calculates the vehicle speed of the vehicle according to the satellite signal, and selectively locks the screen of the vehicle according to the vehicle speed. In the second determination procedure, the control circuit generates a motion signal according to the motion state value, and selectively locks the screen of the vehicle according to the motion signal. Accordingly, driving safety can still be effectively ensured even in the case of poor satellite signals.

An apparatus and a method for performing positioning using a Global Navigation Satellite System (GNSS) with a state machine based localization engine are provided. When the apparatus receives GNSS signals, the apparatus provides the localization engine to process the GNSS signals, and determines, based on a GNSS status and a position-velocity-time (PVT) status, a state of the localization engine. Specifically, the state of the localization engine is switchable between at least 3 states, including a dead reckoning state, a tightly coupling state, and a loosely coupling state. Once the state is determined, the localization engine may determine a local accuracy status based on the state of the localization engine. Thus, a downstream module on the apparatus may use the local accuracy status to perform a corresponding downstream action.

An apparatus and a method for performing positioning using a Global Navigation Satellite System (GNSS) with a state machine based localization engine are provided. When the apparatus receives GNSS signals, the apparatus provides the localization engine to process the GNSS signals, and determines, based on a GNSS status and a position-velocity-time (PVT) status, a state of the localization engine. Specifically, the state of the localization engine is switchable between at least 3 states, including a dead reckoning state, a tightly coupling state, and a loosely coupling state. Once the state is determined, the localization engine may determine a local accuracy status based on the state of the localization engine. Thus, a downstream module on the apparatus may use the local accuracy status to perform a corresponding downstream action.

This provides methods and systems for the global navigation satellite system (GNSS) combined with the dead-reckoning (DR) technique, which is expected to provide a vehicle positioning solution, but it may contain an unacceptable amount of error due to multiple causes, e.g., atmospheric effects, clock timing, and multipath effect. Particularly, the multipath effect is a major issue in the urban canyons. This invention overcomes these and other issues in the DR solution by a geofencing framework based on road geometry information and multiple supplemental kinematic filters. It guarantees a road-level accuracy and enables certain V2X applications which does not require sub-meter accuracy, e.g., signal phase timing, intersection movement assist, curve speed warning, reduced speed zone warning, and red-light violation warning. Automated vehicle is another use case. This is used for autonomous cars and vehicle safety, shown with various examples/variations.

This provides methods and systems for the global navigation satellite system (GNSS) combined with the dead-reckoning (DR) technique, which is expected to provide a vehicle positioning solution, but it may contain an unacceptable amount of error due to multiple causes, e.g., atmospheric effects, clock timing, and multipath effect. Particularly, the multipath effect is a major issue in the urban canyons. This invention overcomes these and other issues in the DR solution by a geofencing framework based on road geometry information and multiple supplemental kinematic filters. It guarantees a road-level accuracy and enables certain V2X applications which does not require sub-meter accuracy, e.g., signal phase timing, intersection movement assist, curve speed warning, reduced speed zone warning, and red-light violation warning. Automated vehicle is another use case. This is used for autonomous cars and vehicle safety, shown with various examples/variations.

A system and method include generating environment data from skylight sensor data. The environment data includes a value of a geospatially dependent parameter associated with light received from a predetermined celestial light source. At least two of a compass direction of the predetermined celestial light source when the skylight sensor data was received, a time at which the skylight sensor data was received, or a geospatial coordinate at which the skylight sensor data was collected are received. At least one of the compass direction of the predetermined celestial light source when the skylight sensor data was received, the time at which the skylight sensor data was received, or the geospatial coordinate at which the skylight sensor data was collected is determined, at least in part, from the environment data.

A system and method include generating environment data from skylight sensor data. The environment data includes a value of a geospatially dependent parameter associated with light received from a predetermined celestial light source. At least two of a compass direction of the predetermined celestial light source when the skylight sensor data was received, a time at which the skylight sensor data was received, or a geospatial coordinate at which the skylight sensor data was collected are received. At least one of the compass direction of the predetermined celestial light source when the skylight sensor data was received, the time at which the skylight sensor data was received, or the geospatial coordinate at which the skylight sensor data was collected is determined, at least in part, from the environment data.

A method of automatic labeling of images for supervised machine learning includes obtaining images of roadside objects with a camera mounted to a vehicle, recording a position and orientation of the vehicle within a defined coordinate system while obtaining the images recording position information for each roadside object with the same defined coordinates system as used while recording the position and orientation of the vehicle, and correlating a position of each of the obtained images of the roadside objects with the position information of each roadside object in view of the recorded position and orientation of the vehicle. The images are labeled to identify the roadside objects in view of the correlated position of each of the obtained images of the roadside objects.