Monitoring of data to predict road conditions
The present disclosure relates to monitoring data in and around a vehicle to predict anomalous, e.g., unsafe, road conditions, and using the data to suggest a corrective action to avoid the unsafe road conditions. A computing device receives information indicative of imagery, sound, or vehicle operation via sensors and/or cameras mounted in or near a vehicle. The information may be received via the vehicle itself or via a device. The computing device then determines whether there is an indication of an anomalous road condition. The computing device also receives vehicle operation data extracted from one or more vehicle sensors. The computing device then determines whether there is an indication of unsafe road conditions, and if there is, the computing device may output a notice or alert via a notification system to alert the driver.
1. A system that detects unsafe road conditions, comprising:
sensors configured to generate sensor information indicative of a condition in or near a vehicle, wherein the sensors comprise a noise detection sensor and a vibration sensor;
a vehicle controller configured to receive vehicle operation data of the vehicle; and
a device configured to receive the sensor information, vehicle location information, and the vehicle operation data, wherein the device comprises a processor configured to:
identify a change in road surface based at least in part on the sensor information upon identifying in the sensor information a low frequency noise in data from the noise detection sensor that is associated with a relative increase in vibrations detected by the vibration sensor;
determine a location of the change in road surface based at least in part on the vehicle operation data; and
in response to identifying the change in road surface and the location of the change in road surface, performing an action to report the change in road surface.
2. The system of claim 1 , wherein the sensors are embedded in the vehicle or in the device.
3. The system of claim 2 , wherein identifying the change in road surface comprises extracting voice data from the sensor information from the noise detection sensor and identifying a characteristic noise associated with the change in road surface.
4. The system of claim 2 , wherein identifying the change in road surface comprises extracting velocity, displacement, proximity, or acceleration data from the sensor information from the vibration sensor.
5. The system of claim 2 , wherein the sensors further comprise a motion sensor, and wherein identifying the change in road surface comprises detecting a change in the sensor information, the sensor information comprising motion data output by the motion sensor.
6. The system of claim 2 , wherein the sensor information comprises image data output from a camera, and wherein identifying the change in road surface comprises identifying a change in the image data output by the camera.
7. The system of claim 6 , wherein the sensor information comprises vibration data from the vibration sensor, and further comprising comparing the change in movement of the image data output by the camera to a change in vibration data output by the vibration sensor.
8. The system of claim 1 , wherein the device is a wearable or a mobile device.
9. The system of claim 1 , wherein the processor is configured to distinguish between a speed bump or a pothole type of change in road surface based on the sensor information.
10. A tangible, non-transitory, machine-readable medium, comprising machine-readable instructions that, when executed by one or more processors, cause the one or more processors to:
receive, via an noise detection sensor, information indicative of a condition in or near a vehicle;
receive, via a vehicle controller, vehicle operation data of the vehicle;
identify a change in road condition based at least in part on the noise detection sensor information;
determine a location of the change in road condition based at least in part on the vehicle operation data;
in response to identifying the change in road condition and the location of the change in road condition, perform an action to report the change in road condition; and
offer a monetary incentive or service discount via a user device to avoid the change in road condition.
11. The tangible, non-transitory, machine-readable medium of claim 10 , wherein the instructions cause the one or more processors to communicate the report the change in road condition to a notification system.
12. The tangible, non-transitory, machine-readable medium of claim 10 , wherein the instructions cause the one or more processors to determine an alternate route that avoids the change in road condition.
13. A processor-implemented method for detecting road conditions, comprising:
receiving, via a sensor, sensor information indicative of a condition in or near a vehicle;
receiving, a vehicle controller, vehicle operation data of the vehicle;
identifying a change in road condition based at least in part on the sensor information, wherein identifying the change in road condition comprises identifying a concurrent event in the vehicle operation data and the sensor information characteristic of a type of road condition;
determining a location of the change in road condition based at least in part on the vehicle operation data; and
in response to identifying the change in road condition and the location of the change in road condition, performing an action to report the change in road condition.
14. The method of claim 13 , further comprising at least one sensor, the at least one sensor comprising one or more of a noise detection sensor, a vibration sensor, a motion sensor, an accelerometer, a gyroscope, a wheel sensor, or a camera, wherein the at least one sensor is embedded in the vehicle or in a device.
15. The method of claim 14 , wherein the at least one sensor comprises the noise detection sensor and the vibration sensor, and wherein identifying the change in road condition comprises associating a humming noise extracted from noise information from the noise detection sensor that occurs concurrently with a detected increase in vibrations detected by the vibration sensor.
16. The method of claim 14 , wherein identifying the change in road condition comprises detecting a change in motion data output by the vibration sensor, the motion sensor, the accelerometer, the gyroscope, or the wheel sensor.
17. The method of claim 13 , wherein the concurrent event comprises a braking event in the vehicle operation data and an increase in vibrations in the sensor information that is characteristic of a speed bump.
18. A processor-implemented method for detecting road conditions, comprising:
receiving, via a sensor, sensor information indicative of a condition in or near a vehicle;
receiving, a vehicle controller, vehicle operation data of the vehicle;
identifying a change in road condition based at least in part on the sensor information, wherein identifying the road condition comprises detecting a change in motion data output by a vibration sensor, a motion sensor, an accelerometer, a gyroscope, or a wheel sensor;
determining a location of the change in road condition based at least in part on the vehicle operation data; and
in response to identifying the change in road condition and the location of the road condition, performing an action to report the change in road condition.
19. A system that detects unsafe road conditions, comprising:
sensors configured to generate sensor information comprising image data and vibration data indicative of a condition in or near a vehicle;
a vehicle controller configured to receive vehicle operation data of the vehicle; and
a device configured to receive the sensor information, vehicle location information, and the vehicle operation data, wherein the device comprises a processor configured to:
identify a change in road condition based at least in part on the sensor information, wherein identifying the change in road condition comprises identifying a change in the image data and comparing the change in movement of the image data to a change in vibration data;
determine a location of the change in road condition based at least in part on the vehicle operation data; and
in response to identifying the change in road condition and the location of the change in road condition, performing an action to report the change in road condition.