Automated vehicular accident detection

• US 9,984,331 B2
• Filed: 06/08/2015
• Issued: 05/29/2018
• Est. Priority Date: 06/08/2015
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Cama, Karl J., Herman, Norbert, Ray, Shubhadip
• Primary Examiner(s): Starks, Wilbert L
• Application Number:
  US14/732,836
• Publication Number:
  US 20160358081A1
• Time in Patent Office: 1,086 Days
• Field of Search: None
• CPC Class Codes: B60W 40/00 Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
• CPC Class Codes: G01S 19/14 specially adapted for specific applications
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 18/24765 Rule-based classification
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06N 5/046 Forward inferencing; Production systems
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G06Q 50/40 Business processes related to the transportation industry shipping G06Q10/083
• CPC Class Codes: G06V 10/765 using rules for classification or partitioning the feature space
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G06V 20/59 inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors
• CPC Class Codes: G08G 1/048 with provision for compensation of environmental or other condition, e.g. snow, vehicle stopped at detector
• CPC Class Codes: G08G 1/052 with provision for determining speed or overspeed speed measuring in general G01P
• CPC Class Codes: G08G 1/093 Data selection, e.g. prioritizing information, managing message queues, selecting the information to be output
• CPC Class Codes: G08G 1/09626 where the origin of the information is within the own vehicle, e.g. a local storage device, digital map

Abstract

A vehicle accident detection method and system is provided. The method includes receiving location coordinates associated with a location of an occurring vehicular accident. Data associated with possible causes of the vehicular accident is received from sensors. Traffic related rules associated with a geographical location are retrieved and analyzed with respect to the data. Parameters associated with at least one vehicle involved in the vehicular accident and a possible cause are determined via execution of programming logic and transmitted to additional systems. The possible cause for the vehicular accident is determined from all possible causes based on matching current and historical accident circumstances. Additionally, weighting factors may be available and adjusted over time for accurate accident detection. A possible cause comprising a greatest weighting factor may be used to identify a most likely cause.

Claims

1. A vehicle accident detection and driving mechanism improvement method comprising:

automatically deploying, by a computer processor of a computing system enabling a relative positioning circuit of a vehicle, airbags of said vehicle in response to detecting a vehicular accident involving said vehicle, wherein said relative positioning circuit comprises programmable logic circuitry utilizing state information of computer readable program instructions to personalize electronic circuitry of said relative positioning circuit;

automatically applying, by said computer processor enabling said relative positioning circuit of said vehicle, a braking mechanism of said vehicle in response to detecting said vehicular accident involving said vehicle;

receiving, by said computer processor, location coordinates describing a location where said vehicular accident occurred;

receiving, by said computer processor from a first plurality of sensors, data associated with possible causes of said vehicular accident, wherein said first plurality of sensors automatically detect and convert to said data;

engine conditions of said vehicle, a brake status of said vehicle, and an airbag deployment of said vehicle;

automatically activating, by said computer processor in combination with said first plurality of sensors, a second plurality of sensors capturing time based incidents associated with a point of impact of said vehicle during said vehicular accident;

retrieving, by said computer processor, traffic related rules associated with a geographical location of said location;

analyzing, by said computer processor executing programming logic, said data and said time based incidents with respect to said traffic related rules;

determining, by said computer processor based on results of said analyzing, parameters associated with mechanical issues of said vehicle involved in said vehicular accident;

determining, by said computer processor based on results of said analyzing, distraction parameters associated with distraction related events for a driver of said vehicle involved in said vehicular accident;

determining, by said computer processor executing a diagnostic circuit diagnosing results of said analyzing, said parameters, and said distraction parameters, a possible cause for said vehicular accident, wherein said diagnostic circuit comprises programmable logic circuitry utilizing state information of computer readable program instructions to personalize electronic circuitry of said diagnostic circuit;

generating, by said processor based on said possible cause for said vehicular accident, self learning software code configured to automatically deploy mechanical systems of said vehicle for preventing an additional vehicular accident and improving mechanisms of said vehicle; and

automatically deploying, by said computer processor executing said self learning software code, said mechanical systems of said vehicle in response to detection of a possible vehicular accident involving said vehicle.

2. The method of claim 1, further comprising:

retrieving, by said computer processor, additional determined possible causes for said vehicular accident;

additionally analyzing, by said computer processor, said possible cause with respect to said additional determined possible causes;

applying, by said computer processor based on results of said additionally analyzing, weighting factors to said possible cause and said additional determined possible causes;

determining, by said computer processor based on a highest weighting factor of said weighting factors, a determined cause for said vehicular accident; and

presenting, by said computer processor via a display system, said determined cause for said vehicular accident.

3. The method of claim 2, wherein said additional determined possible causes comprise causes selected from the group consisting of previous accidents associated with said driver of said at least one vehicle, weather and terrain related conditions, and previous driver related records of said driver.

4. The method of claim 2, further comprising:

executing, by said computer processor, predictive modeling algorithms with respect to said determined cause for said vehicular accident and additional determined causes for additional vehicular accidents previously occurring at said location;

generating, by said computer processor based on an application of results of said executing said predictive modeling algorithms, modified programming logic associated with said programming logic; and

executing, by said computer processor, said modified programming logic with respect to related data associated with possible causes of an additional vehicular accident.

5. The method of claim 4, further comprising:

predicting, by said computer processor based on said results of said executing said programming logic, results of said executing said predictive modeling algorithms, and results of said executing said modified programming logic, possible future vehicular accidents at said location.

6. The method of claim 4, further comprising:

predicting, by said computer processor based on said results of said executing said programming logic, results of said executing said predictive modeling algorithms, and results of said executing said modified programming logic, possible future vehicular accidents comprising similar circumstances with respect to said vehicular accident.

7. The method of claim 1, wherein said data associated with said vehicular accident comprises data selected from the group consisting of historical data associated with said location, sensor data from sensors located adjacent to said location, smart phone/GPS related data, environmental condition data, data retrieved from systems of said at least one vehicle, traffic signal data, and data defining accident circumstances.

8. The method of claim 1, wherein said parameters comprise a determined coefficient of friction between tires of said at least one vehicle and a driving surface.

9. The method of claim 1, wherein said distraction parameters comprise distraction based parameters selected from the group consisting of electronics based distraction parameters and food/drink based distraction parameters.

10. The method of claim 1, further comprising:

providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable code in the computing system, said code being executed by the computer processor to implement said receiving said location coordinates, said receiving said data, said retrieving, said analyzing, said determining said parameters, said determining said possible cause, and said transmitting.

11. A computing system comprising a computer processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the computer processor implements a vehicle accident detection and driving mechanism improvement method comprising:

automatically deploying, by said computer processor enabling a relative positioning circuit of a vehicle, airbags of said vehicle in response to detecting a vehicular accident involving said vehicle, wherein said relative positioning circuit comprises programmable logic circuitry utilizing state information of computer readable program instructions to personalize electronic circuitry of said relative positioning circuit;

automatically applying, by said computer processor enabling said relative positioning circuit of said vehicle, a braking mechanism of said vehicle in response to detecting said vehicular accident involving said vehicle;

receiving, by said computer processor, location coordinates describing a location where said vehicular accident occurred;

receiving, by said computer processor from a first plurality of sensors, data associated with possible causes of said vehicular accident, wherein said first plurality of sensors automatically detect and convert to said data;

engine conditions of said vehicle, a brake status of said vehicle, and an airbag deployment of said vehicle;

automatically activating, by said computer processor in combination with said first plurality of sensors, a second plurality of sensors capturing time based incidents associated with a point of impact of said vehicle during said vehicular accident;

retrieving, by said computer processor, traffic related rules associated with a geographical location of said location;

analyzing, by said computer processor executing programming logic, said data and said time based incidents with respect to said traffic related rules;

determining, by said computer processor based on results of said analyzing, parameters associated with mechanical issues of said vehicle involved in said vehicular accident;

determining, by said computer processor based on results of said analyzing, distraction parameters associated with distraction related events for a driver of said vehicle involved in said vehicular accident;

determining, by said computer processor executing a diagnostic circuit diagnosing results of said analyzing, said parameters, and said distraction parameters, a possible cause for said vehicular accident, wherein said diagnostic circuit comprises programmable logic circuitry utilizing state information of computer readable program instructions to personalize electronic circuitry of said diagnostic circuit;

generating, by said processor based on said possible cause for said vehicular accident, self learning software code configured to automatically deploy mechanical systems of said vehicle for preventing an additional vehicular accident and improving mechanisms of said vehicle; and

automatically deploying, by said computer processor executing said self learning software code, said mechanical systems of said vehicle in response to detection of a possible vehicular accident involving said vehicle.

12. The computing system of claim 11, wherein said method further comprises:

retrieving, by said computer processor, additional determined possible causes for said vehicular accident;

additionally analyzing, by said computer processor, said possible cause with respect to said additional determined possible causes;

applying, by said computer processor based on results of said additionally analyzing, weighting factors to said possible cause and said additional determined possible causes;

determining, by said computer processor based on a highest weighting factor of said weighting factors, a determined cause for said vehicular accident; and

presenting, by said computer processor via a display system, said determined cause for said vehicular accident.

13. The computing system of claim 12, wherein said method further comprises:

wherein said additional determined possible causes comprise causes selected from the group consisting of previous accidents associated with said driver of said at least one vehicle, weather and terrain related conditions, and previous driver related records of said driver.

14. The computing system of claim 12, wherein said method further comprises:

executing, by said computer processor, predictive modeling algorithms with respect to said determined cause for said vehicular accident and additional determined causes for additional vehicular accidents previously occurring at said location;

generating, by said computer processor based on an application of results of said executing said predictive modeling algorithms, modified programming logic associated with said programming logic; and

executing, by said computer processor, said modified programming logic with respect to related data associated with possible causes of an additional vehicular accident.

15. The computing system of claim 14, wherein said method further comprises:

predicting, by said computer processor based on said results of said executing said programming logic, results of said executing said predictive modeling algorithms, and results of said executing said modified programming logic, possible future vehicular accidents at said location.

16. The computing system of claim 14, wherein said method further comprises:

predicting, by said computer processor based on said results of said executing said programming logic, results of said executing said predictive modeling algorithms, and results of said executing said modified programming logic, possible future vehicular accidents comprising similar circumstances with respect to said vehicular accident.

17. The computing system of claim 11, wherein said data associated with said vehicular accident comprises data selected from the group consisting of historical data associated with said location, sensor data from sensors located adjacent to said location, smart phone/GPS related data, environmental condition data, data retrieved from systems of said at least one vehicle, traffic signal data, and data defining accident circumstances.

18. The computing system of claim 11, wherein said parameters comprise a determined coefficient of friction between tires of said at least one vehicle and a driving surface.

19. The computing system of claim 11, wherein said distraction parameters comprise distraction based parameters selected from the group consisting of electronics based distraction parameters and food/drink based distraction parameters.

20. A computer program product for vehicle accident detection and driving mechanism improvement, the computer program product comprising:

one or more computer-readable, tangible storage devices;

program instructions, stored on at least one of the one or more storage devices, to automatically deploy, via a relative positioning circuit of a vehicle, airbags of said vehicle in response to detecting a vehicular accident involving said vehicle, wherein said relative positioning circuit comprises programmable logic circuitry utilizing state information of computer readable program instructions to personalize electronic circuitry of said relative positioning circuit;

program instructions, stored on at least one of the one or more storage devices, to automatically apply, via said relative positioning circuit of said vehicle, a braking mechanism of said vehicle in response to detecting said vehicular accident involving said vehicle;

program instructions, stored on at least one of the one or more storage devices, to receive location coordinates describing a location where said vehicular accident occurred;

program instructions, stored on at least one of the one or more storage devices, to receive from a first plurality of sensors, data associated with possible causes of said vehicular accident, wherein said first plurality of sensors automatically detect and convert to said data;

engine conditions of said vehicle, a brake status of said vehicle, and an airbag deployment of said vehicle;

program instructions, stored on at least one of the one or more storage devices, to automatically activate, via said first plurality of sensors, a second plurality of sensors capturing time based incidents associated with a point of impact of said vehicle during said vehicular accident,

program instructions, stored on at least one of the one or more storage devices, to retrieve traffic related rules associated with a geographical location of said location;

program instructions, stored on at least one of the one or more storage devices, to analyze said data and said time based incidents with respect to said traffic related rules;

program instructions, stored on at least one of the one or more storage devices, to determine parameters associated with mechanical issues of said vehicle involved in said vehicular accident;

program instructions, stored on at least one of the one or more storage devices, to determine distraction parameters associated with distraction related events for a driver of said vehicle involved in said vehicular accident;

program instructions, stored on at least one of the one or more storage devices, to determine, via execution of a diagnostic circuit diagnosing results of the analyses, the parameters, and the distraction parameters, a possible cause for said vehicular accident, wherein said diagnostic circuit comprises programmable logic circuitry utilizing state information of computer readable program instructions to personalize electronic circuitry of said diagnostic circuit;

program instructions, stored on at least one of the one or more storage devices, to generate, based on said possible cause for said vehicular accident, self learning software code configured to automatically deploy mechanical systems of said vehicle for preventing an additional vehicular accident and improving mechanisms of said vehicle; and

program instructions, stored on at least one of the one or more storage devices, to automatically deploy, via execution of said self learning software code, said mechanical systems of said vehicle in response to detection of a possible vehicular accident involving said vehicle.