PREVENTING DRIVER DISTRACTION FROM INCOMING NOTIFICATIONS

• US 20170332347A1
• Filed: 05/11/2016
• Published: 11/16/2017
• Est. Priority Date: 05/11/2016
• Status: Active Grant

• Current Assignee: HCL Technologies Limited
• Original Assignee: International Business Machines Corporation
• Inventors: Boss, Gregory J., Fox, Jeremy R., Jones, Andrew R., McConnell, Kevin C., Moore, JR., John E.
• Granted Patent: US 9,826,500 B1
• Time in Patent Office: Days
• CPC Class Codes: G06V 20/597 Recognising the driver's state or behaviour, e.g. attention or drowsiness
• CPC Class Codes: H04M 1/6075 adapted for handsfree use in a vehicle H04M1/6058 takes precedence; arrangements for holding telephones in a vehicle B60R11/0241
• CPC Class Codes: H04M 1/6091 including a wireless interface
• CPC Class Codes: H04M 1/72436 for text messaging, e.g. short messaging services [SMS] or e-mails
• CPC Class Codes: H04M 1/72454 according to context-related or environment-related conditions
• CPC Class Codes: H04W 24/08 Testing, supervising or monitoring using real traffic
• CPC Class Codes: H04W 68/005 Transmission of information for alerting of incoming communication
• CPC Class Codes: H04W 88/02 Terminal devices

Abstract

Driving condition data is determined. The driving condition data identifies one or more driving actions that require more driver attention and one or more driving actions that require less driver attention. An indication is received that a user has a mobile device and is driving a vehicle. The surrounding environment of the vehicle is monitored. An incoming notification on the mobile device is received. A distraction value is determined. The distraction value is based on the one or more driving actions and the surrounding environment. The incoming notification is modified based on the distraction value.

Claims

1. A method for preventing driver distraction from incoming notifications from a mobile device, the method comprising the steps of:

determining, by one or more computer processors, a driving condition data, wherein the driving condition data identifies one or more driving actions that require more driver attention and one or more driving actions require that less driver attention;

receiving, by one or more computer processors, an indication that a user has a mobile device and the user is driving a vehicle;

monitoring, by one or more computer processors, a surrounding environment of the vehicle;

receiving, by one or more computer processors, an incoming notification on the mobile device of the user;

responsive to receiving an incoming notification on the mobile device of the user, determining, by one or more computer processors, a distraction value, wherein the distraction value is based on the one or more driving actions and the surrounding environment, wherein the distraction value is determined by an algorithm, and wherein the algorithm is selected from the group consisting of summing individual distraction values to determine an overall distraction value and weighting one or more individual distraction values, prior to summing the individual distraction values, to determine the overall distraction value; and

modifying, by one or more computer processors, the incoming notification based on the determined distraction value.

2. The method of claim 1, wherein the one or more driving actions that require more driver attention are selected from the group consisting of driving through an intersection, driving in heavy traffic with many other vehicles around, driving in poor weather conditions, turning left on a red flashing traffic signal, driving during rush hour, driving a never before driven route, in-car distractions, and situations where a driver may not be paying attention to a road, as monitored by an in-car camera.

3. The method of claim 1, wherein the one or more driving actions that require less driver attention are selected from the group consisting of waiting at a stop light or in a traffic jam, driving over a bridge with no cross streets or turns, driving in light traffic conditions with few other vehicles around, driving late at night with fewer vehicles on a road, and driving on familiar routes.

4. The method of claim 1, wherein the step of monitoring, by one or more computer processors, a surrounding environment of the vehicle, comprises:

monitoring, by one or more computer processors, the surrounding environment using one or more safety systems found in the vehicle, wherein the safety system is selected from the group consisting of a driver drowsiness detection system, an automatic braking system, an infrared night vision system, an adaptive headlight system, a reverse backup sensor system, a backup camera, an adaptive cruise control system, a lane departure warning system, a tire pressure monitoring system, an electronic stability control system, a traction control system, an anti-lock braking system, an electronic brakeforce distribution system, a cornering brake control system, and an emergency brake assist system.

5. The method of claim 1, wherein the incoming notification is selected from the group consisting of a notification for a phone call, a notification for a short message service text, a notification for a multimedia message service text message, a social media website notification, an e-mail notification, a weather notification, and a news notification.

7. The method of claim 1, wherein the incoming notification modification type is selected from the group consisting of keeping a default notification of the mobile device, changing an audible notification to a haptic notification, changing an audible notification to a visual notification, changing a haptic notification to a visual notification, silencing an audible notification, silencing a haptic notification, and silencing a visual notification.

6. (canceled)

8. A computer program product for preventing driver distraction from incoming notifications from a mobile device, the computer program product comprising:

one or more computer readable storage media; and

program instructions stored on the one or more computer readable storage media, the program instructions comprising;

program instructions to determine a driving condition data, wherein the driving condition data identifies one or more driving actions that require more driver attention and one or more driving actions require that less driver attention;

program instructions to receive an indication that a user has a mobile device and the user is driving a vehicle;

program instructions to monitor a surrounding environment of the vehicle;

program instructions to receive an incoming notification on the mobile device of the user;

responsive to receiving an incoming notification on the mobile device of the user, program instructions to determine a distraction value, wherein the distraction value is based on the one or more driving actions and the surrounding environment, wherein the distraction value is determined by an algorithm, and wherein the algorithm is selected from the group consisting of summing individual distraction values to determine an overall distraction value and weighting one or more individual distraction values, prior to summing the individual distraction values, to determine the overall distraction value; and

program instructions to modify the incoming notification based on the determined distraction value.

9. The computer program product of claim 8, wherein the one or more driving actions that require more driver attention are selected from the group consisting of driving through an intersection, driving in heavy traffic with many other vehicles around, driving in poor weather conditions, turning left on a red flashing traffic signal, driving during rush hour, driving a never before driven route, in-car distractions, and situations where a driver may not be paying attention to a road, as monitored by an in-car camera.

10. The computer program product of claim 8, wherein the one or more driving actions that require less driver attention are selected from the group consisting of waiting at a stop light or in a traffic jam, driving over a bridge with no cross streets or turns, driving in light traffic conditions with few other vehicles around, driving late at night with fewer vehicles on a road, and driving on familiar routes.

11. The computer program product of claim 8, wherein the step of monitoring, by one or more computer processors, a surrounding environment of the vehicle, comprises:

monitoring, by one or more computer processors, the surrounding environment using one or more safety systems found in the vehicle, wherein the safety system is selected from the group consisting of a driver drowsiness detection system, an automatic braking system, an infrared night vision system, an adaptive headlight system, a reverse backup sensor system, a backup camera, an adaptive cruise control system, a lane departure warning system, a tire pressure monitoring system, an electronic stability control system, a traction control system, an anti-lock braking system, an electronic brakeforce distribution system, a cornering brake control system, and an emergency brake assist system.

12. The computer program product of claim 8, wherein the incoming notification is selected from the group consisting of a notification for a phone call, a notification for a short message service text, a notification for a multimedia message service text message, a social media website notification, an e-mail notification, a weather notification, and a news notification.

14. The computer program product of claim 8, wherein the incoming notification modification type is selected from the group consisting of keeping a default notification of the mobile device, changing an audible notification to a haptic notification, changing an audible notification to a visual notification, changing a haptic notification to a visual notification, silencing an audible notification, silencing a haptic notification, and silencing a visual notification.

13. (canceled)

15. A computer system for preventing driver distraction from incoming notifications from a mobile device, the computer system comprising:

one or more computer processors;

one or more computer readable storage media; and

program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more computer processors, the program instructions comprising;

program instructions to determine a driving condition data, wherein the driving condition data identifies one or more driving actions that require more driver attention and one or more driving actions require that less driver attention;

program instructions to receive an indication that a user has a mobile device and the user is driving a vehicle;

program instructions to monitor a surrounding environment of the vehicle;

program instructions to receive an incoming notification on the mobile device of the user;

responsive to receiving an incoming notification on the mobile device of the user, program instructions to determine a distraction value, wherein the distraction value is based on the one or more driving actions and the surrounding environment, wherein the distraction value is determined by an algorithm, and wherein the algorithm is selected from the group consisting of summing individual distraction values to determine an overall distraction value and weighting one or more individual distraction values, prior to summing the individual distraction values, to determine the overall distraction value; and

program instructions to modify the incoming notification based on the determined distraction value.

16. The computer system of claim 15, wherein the one or more driving actions that require more driver attention are selected from the group consisting of driving through an intersection, driving in heavy traffic with many other vehicles around, driving in poor weather conditions, turning left on a red flashing traffic signal, driving during rush hour, driving a never before driven route, in-car distractions, and situations where a driver may not be paying attention to a road, as monitored by an in-car camera.

17. The computer system of claim 15, wherein the one or more driving actions that require less driver attention are selected from the group consisting of waiting at a stop light or in a traffic jam, driving over a bridge with no cross streets or turns, driving in light traffic conditions with few other vehicles around, driving late at night with fewer vehicles on a road, and driving on familiar routes.

18. The computer system of claim 15, wherein the step of monitoring, by one or more computer processors, a surrounding environment of the vehicle, comprises:

monitoring, by one or more computer processors, the surrounding environment using one or more safety systems found in the vehicle, wherein the safety system is selected from the group consisting of a driver drowsiness detection system, an automatic braking system, an infrared night vision system, an adaptive headlight system, a reverse backup sensor system, a backup camera, an adaptive cruise control system, a lane departure warning system, a tire pressure monitoring system, an electronic stability control system, a traction control system, an anti-lock braking system, an electronic brakeforce distribution system, a cornering brake control system, and an emergency brake assist system.

19. The computer system of claim 15, wherein the incoming notification is selected from the group consisting of a notification for a phone call, a notification for a short message service text, a notification for a multimedia message service text message, a social media website notification, an e-mail notification, a weather notification, and a news notification.

20. (canceled)