Data Processing System with Machine Learning Engine for Providing Driving Data Analysis and Vehicle Control Functions
US-2019101914-A1 · Apr 4, 2019 · US
US12307885B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12307885-B2 |
| Application number | US-202217815506-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jul 27, 2022 |
| Priority date | Jul 27, 2022 |
| Publication date | May 20, 2025 |
| Grant date | May 20, 2025 |
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Disclosed are systems, apparatuses, processes, and computer-readable media for wireless communications. For example, an example of a process includes receiving, by an onboard unit (OBU) of a vehicle, sensor data from a plurality of sensors of the vehicle. The process may include determining, by the OBU based on the sensor data, a score level for an event associated with the vehicle. The process may further include determining the score level is greater than a threshold score level and, based on the score level being greater than the threshold score level, broadcasting an alert message related to the event to one or more devices.
Opening claim text (preview).
What is claimed is: 1. A method for wireless communications at a vehicle, the method comprising: receiving, by an onboard unit (OBU) of the vehicle, sensor data from a plurality of sensors of the vehicle; determining, by the OBU based on the sensor data, a first score level for a vehicle malfunction associated with the vehicle; determining, by the OBU based on the sensor data, a second score level for a driver misbehavior associated with a driver of the vehicle; determining the first score level and the second score level are greater than at least one threshold score level; and transmitting, by the OBU based on the first score level and the second score level being greater than the at least one threshold score level, at least one alert message related to the vehicle malfunction and the driver misbehavior to one or more vehicles via sidelink communications. 2. The method of claim 1 , wherein the vehicle malfunction is at least one of a burst tire, a smooth tire, a faulty brake, faulty steering, a malformed headlight operating under poor visibility conditions, a malformed taillight operating under the poor visibility conditions, a malfunctioning windshield wiper operating in heavy rain conditions, or an engine failure. 3. The method of claim 1 , wherein the driver misbehavior is at least one of a hand of the driver not on a steering wheel for a predefined duration of time, frequent head turns by the driver, eating by the driver, drinking by the driver, operation of a computing device by the driver, an attempt by the driver to make one or more calls on a mobile phone, the driver looking at an object not related to driving located within the vehicle, the driver looking at an object not related to driving located outside of the vehicle, frequent interaction of the driver with passengers of the vehicle, singing by the driver, movement of the driver to music, grooming by the driver, the driver reaching for an object located within the vehicle, sudden braking, frequent braking, or frequent lane departures. 4. The method of claim 1 , wherein the at least one alert message is transmitted to at least one of a roadside unit (RSU), a mobile device of a pedestrian outside of the vehicle, an infrastructure control unit (ICU), a base station, a server associated with a vehicle service center, or a server associated with a law enforcement agency. 5. The method of claim 1 , wherein the at least one alert message is one of a Basic Safety Message (BSM), a Cooperative Awareness Message (CAM), a Collective Perception Message (CPM), a Sensor Data Sharing Message (SDSM), or a Decentralized Environmental Message (DENM). 6. The method of claim 1 , wherein the at least one alert message comprises information regarding at least one of a specific type of vehicle malfunction or a specific type of driver misbehavior. 7. The method of claim 1 , wherein the at least one alert message is broadcast via sidelink communications. 8. The method of claim 1 , wherein the at least one alert message is broadcast at a maximum power level for transmission of the at least one alert message. 9. The method of claim 1 , wherein the first score level and the second score level are determined using a machine learning model. 10. The method of claim 1 , wherein the plurality of sensors include at least one of a camera, a light detection and ranging (LIDAR) sensor, or a radar sensor. 11. The method of claim 1 , wherein transmitting the at least one alert message comprises broadcasting the at least one alert message. 12. The method of claim 1 , wherein the first score level indicates a probability that the vehicle malfunction has occurred, and wherein the second score level indicates a probability that the driver misbehavior has occurred. 13. An apparatus for wireless communications, comprising: at least one memory; and at least one processor coupled to at least one memory and configured to: receive sensor data from a plurality of sensors of a vehicle; determine, based on the sensor data, a first score level for a vehicle malfunction associated with the vehicle; determine, based on the sensor data, a second score level for a driver misbehavior associated with a driver of the vehicle; determine the first score level and the second score level are greater than at least one threshold score level; and based on the first score level and the second score level being greater than the at least one threshold score level, cause at least one alert message related to the event vehicle malfunction and the driver misbehavior to be transmitted to one or more vehicles via sidelink communications. 14. The apparatus of claim 13 , wherein the vehicle malfunction is at least one of a burst tire, a smooth tire, a faulty brake, faulty steering, a malformed headlight operating under poor visibility conditions, a malformed taillight operating under the poor visibility conditions, a malfunctioning windshield wiper operating in heavy rain conditions, or an engine failure. 15. The apparatus of claim 13 , wherein the driver misbehavior is at least one of a hand of the driver not on a steering wheel for a predefined duration of time, frequent head turns by the driver, eating by the driver, drinking by the driver, operation of a computing device by the driver, an attempt by the driver to make one or more calls on a mobile phone, the driver looking at an object not related to driving located within the vehicle, the driver looking at an object not related to driving located outside of the vehicle, frequent interaction of the driver with passengers of the vehicle, singing by the driver, movement of the driver to music, grooming by the driver, the driver reaching for an object located within the vehicle, sudden braking, frequent braking, or frequent lane departures. 16. The apparatus of claim 13 , wherein the at least one processor is configured to cause the at least one alert message to be transmitted to at least one of a roadside unit (RSU), a mobile device of a pedestrian outside of the vehicle, an infrastructure control unit (ICU), a base station, a server associated with a vehicle service center, or a server associated with a law enforcement agency. 17. The apparatus of claim 13 , wherein the at least one alert message is one of a Basic Safety Message (BSM), a Cooperative Awareness Message (CAM), a Collective Perception Message (CPM), a Sensor Data Sharing Message (SDSM), or a Decentralized Environmental Message (DENM). 18. The apparatus of claim 13 , wherein the at least one alert message comprises information regarding at least one of a specific type of vehicle malfunction or a specific type of driver misbehavior. 19. The apparatus of claim 13 , wherein the at least one processor is configured to cause the at least one alert message to be broadcast via sidelink communications. 20. The apparatus of claim 13 , wherein the at least one processor is configured to cause the at least one alert message to be broadcast at a maximum power level for transmission of the at least one alert message. 21. The apparatus of claim 13 , wherein the at least one processor is configured to determine the first score level and the second score level are using a machine learning model. 22. The apparatus of claim 13 , wherein the plurality of sensors include at least one of a camera, a light detection and ranging (LIDAR) sensor, or a radar sensor. 23. The apparatus of claim 13 , wherein the apparatus is implemented as an onboard unit (OBU) of the vehicle.
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