Rogue vehicle detection

• US 9,262,914 B2
• Filed: 09/07/2012
• Issued: 02/16/2016
• Est. Priority Date: 09/29/2011
• Status: Active Grant

• Current Assignee: TATA Consultancy Services Limited (Tata Sons Pvt Ltd.)
• Original Assignee: TATA Consultancy Services Limited (Tata Sons Pvt Ltd.)
• Inventors: Purushothaman, Balamuralidhar, Bhattachar, Rajan Mindigal Alasingara
• Primary Examiner(s): Jabr, Fadey
• Assistant Examiner(s): Soofi, Yazan A
• Application Number:
  US14/348,294
• Publication Number:
  US 20140222323A1
• Time in Patent Office: 1,257 Days
• Field of Search: 701/117
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G08G 1/00 Traffic control systems for road vehicles arrangement of road signs or traffic signals E01F9/00 ; automatic vehicle control B62D
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

The present subject matter relates to a method for rogue vehicle detection. The method includes receiving at least one violation report for a vehicle from at least one mobile communication device. The at least one violation report is indicative of a traffic violation made by the one or more vehicles. The method further includes categorizing the vehicle as a rogue vehicle, based on at least one rogue vehicle detection metric, the at least one rogue vehicle detection metric being determined from the violation report. The method also includes compiling a traffic observation record based on at least one of the violation report and the rogue vehicle detection metric.

Claims

1. A method for rogue vehicle detection, the method comprising:

receiving at least one violation report for a vehicle from at least one mobile communication device, wherein the at least one violation report is indicative of a traffic violation made by one or more vehicles, and wherein the at least one violation report includes data elements of the vehicle;

extracting the data elements from the at least one violation report for the vehicle;

authenticating the at least one violation report based on an authenticity metric, wherein a value of the authenticity metric is computed by comparing the extracted data elements with reference authenticity measurement data, the reference authenticity measurement data indicates conditions pertaining to a location from which violation by the vehicle is reported;

determining trustworthiness of the at least one violation report using a trustworthiness metric, wherein the trustworthiness metric is based on the authenticity metric and trustworthiness parameters;

categorizing the vehicle as a rogue vehicle, based on the authenticating and the determining trustworthiness; and

compiling a traffic observation record of the rogue vehicle based on at least one of the at least one violation report, the authenticity metric, and the trustworthiness metric.

2. The method as claimed in claim 1, wherein the at least one violation report comprises one or more authenticity parameters, the authenticity parameter comprises at least one of a time stamp, a GPS location, an audio clip, an ambient environmental parameter, and one or more third party parameters.

3. The method as claimed in claim 1, wherein the trustworthiness parameters include at least one of a number of independent violation reports of the same violation incident, registration status of a user, reputation level of the user, a rogueness index of the vehicle, and a collusion index.

4. The method as claimed in claim 3, wherein the rogueness index of the vehicle is a time dependent function.

5. The method as claimed in claim 1, further comprising forwarding the traffic observation record to at least one agency based on a type of traffic violation and a severity of the traffic violation, wherein the at least one agency includes at least one of an insurance agency, vehicle fleet owner, state department, traffic enforcement agency, and an individual user.

6. A computing system for detecting a rogue vehicle, the system comprising:

a processor; and

a memory coupled to the processor for executing a plurality of modules present in the memory, the plurality of modules comprising;

a validation module for;

receiving at least one violation report from at least one mobile communication device, wherein the at least one violation report is indicative of traffic violation made by one or more vehicles, and wherein the at least one violation report includes data elements of the vehicle;

extracting the data elements from the at least one violation report for the vehicle;

authenticating the at least one violation report based on an authenticity metric, wherein a value of the authenticity metric is computed by comparing the extracted data elements with reference authenticity measurement data, the reference authenticity measurement data indicates conditions pertaining to a location from which violation by the vehicle is reported;

determining trustworthiness of the at least one violation report using a trustworthiness metric, wherein the trustworthiness metric is based on the authenticity metric and trustworthiness parameters; and

categorizing the vehicle as a rogue vehicle, based on the authenticating and the determining trustworthiness;

a compilation module for compiling a traffic observation record of the rogue vehicle based on the at least one violation report, the authenticity metric, and the trustworthiness metric.

7. The computing system as claimed in claim 6, wherein the computing system is implemented at least at one of a third party service provider and a state department.

8. The computing system as claimed in claim 6, wherein the validation module further rejects the at least one violation report based on a comparison of a value of the authenticity metric with a value of a threshold authenticity metric.

9. The computing system as claimed in claim 6, wherein the validation module further determines a collusion index of the at least one violation report, wherein the collusion index is indicative of a level of collusion of a plurality of submitted violation reports regarding the rogue vehicle.

10. The computing system as claimed in claim 6, wherein the compilation module further forwards the traffic observation record to at least one agency based on a type of traffic violation and a severity of the traffic violation.

11. The computing system as claimed in claim 6, wherein the compilation module further forwards an alert based on the traffic observation record to a user within a predetermined radius of a location of a violation incident.

12. The computing system as claimed in claim 6, wherein the compilation module further imposes a penalty against the rogue vehicle based on a rogueness index of the rogue vehicle.

13. The computing system as claimed in claim 6, wherein the compilation module allots award points to a user based on at least one of a number of violation reports submitted by the user, a nature of the violation, and a severity of the violation, and wherein a redeeming of the award points by the user is facilitated.

14. A non-transitory computer-readable medium having embodied thereon a computer program for executing a method comprising:

receiving at least one violation report for a vehicle from at least one mobile communication device, wherein the at least one violation report is indicative of a traffic violation made by one or more vehicles, and wherein the at least one violation report includes data elements of the vehicle;

extracting the data elements from the at least one violation report for the vehicle;

authenticating the at least one violation report based on an authenticity metric, wherein, a value of the authenticity metric is computed by comparing the extracted data elements with reference authenticity measurement data, the reference authenticity measurement data indicates conditions pertaining to a location from which violation by the vehicle is reported;

determining trustworthiness of the at least one violation report using a trustworthiness metric, wherein the trustworthiness metric is based on the authenticity metric and trustworthiness parameters;

categorizing the vehicle as a rogue vehicle, based on the authenticating and the determining trustworthiness; and

compiling a traffic observation record of the rogue vehicle based on at least one of the violation report, the authenticity metric, and the trustworthiness metric.