Automated vehicular accident detection

Patent metadata

Field	Value
Publication number	US-10977567-B2
Application number	US-201815912788-A
Country	US
Kind code	B2
Filing date	Mar 6, 2018
Priority date	Jun 8, 2015
Publication date	Apr 13, 2021
Grant date	Apr 13, 2021

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.

First claim

What is claimed is:

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 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;
analyzing, by said computer processor executing programming logic, said data and said time based incidents with respect to traffic related rules associated with a geographical location of a location where said vehicular accident occurred;
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/GP S 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 analyzing, said determining said parameters, and said determining said possible cause.

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 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 b

Assignees

• IBM

Inventors

• Cama Karl J
• Herman Norbert
• Ray Shubhadip

Classifications

• G01S19/14 Primary

  specially adapted for specific applications · CPC title

• G06V10/765

  using rules for classification or partitioning the feature space · CPC title

• G06N5/04 Primary

  Inference or reasoning models · CPC title

• G06F18/24765

  Rule-based classification · CPC title

• G06V20/59

  inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions · CPC title