Method of quickly detecting road distress

• US 10,109,191 B2
• Filed: 02/10/2016
• Issued: 10/23/2018
• Est. Priority Date: 02/10/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Bills, Tierra, Bryant, Reginald, Tatsubori, Michiaki, Walcott, Aisha
• Primary Examiner(s): Pope, Daryl
• Application Number:
  US15/040,246
• Publication Number:
  US 20170229012A1
• Time in Patent Office: 986 Days
• Field of Search: 340901-905, 340435, 340436
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/0967 Systems involving transmission of highway information, e.g. weather, speed limits transmission of navigation instructions to the vehicle G08G1/0968
• CPC Class Codes: G08G 1/096716 where the received information does not generate an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096725 where the received information generates an automatic action on the vehicle control
• CPC Class Codes: G08G 1/096741 where the source of the transmitted information selects which information to transmit to each vehicle
• CPC Class Codes: G08G 1/096775 where the origin of the information is a central station
• CPC Class Codes: G08G 1/205 Indicating the location of the monitored vehicles as destination, e.g. accidents, stolen, rental

Abstract

In various embodiments, the invention involves methods and systems suitable for roadway monitoring, mapping, and maintenance. The probability of a road distress is calculated by combining various sources of data, and automatic alerts are generated to request mobilization of a road repair resource. Various methods are included to increase the accuracy of the probability calculations.

Claims

1. A method for determining the location of a road distress, comprising:

measuring, by a mobile sensor, a distress data for a road section, wherein the distress data comprises a distress time component and a distress action component;

identifying a relevant traffic data for the road section, the relevant traffic data comprising a traffic time component that corresponds to the distress time component;

calculating a probability of a road distress on the road section based on the distress data and relevant traffic data; and

responsive to the calculated probability exceeding a predetermined threshold probability, generating an alert identifying the road section;

wherein;

the road distress comprises at least one of a hole, a swell, a rock, and debris;

the distress data pertains to a first lane in the road section, and the traffic data pertains to a second lane in the road section, the first lane being adjacent to the second lane;

the distress data comprises a rapid deviation in an x-y plane followed by a rapid return to an initial trajectory for a vehicle in the first lane; and

the traffic data comprises a lack of any vehicles in the second lane at the traffic time component that corresponds to the distress time component.

2. The method of claim 1, wherein the mobile sensor is integral with a vehicle, or wherein the mobile sensor is integral with a mobile device, the mobile device disposed in the vehicle.

3. The method of claim 1, further comprising communicating the distress data to a remote server, via a network, and further comprising communicating the alert via a network.

4. The method of claim 1, wherein the relevant traffic data is identified from a plurality of traffic data for the road section, wherein the plurality of traffic data is indexed by a traffic time component.

5. The method of claim 1, wherein the relevant traffic data is identified from a plurality of traffic data for the road section, wherein the plurality of traffic data is indexed by a traffic time component, and wherein the method further comprises receiving, by the remote server via a network, the plurality of traffic data.

6. The method of claim 1, wherein the distress data further comprises a distress lane indicator and a distress direction component, and wherein the traffic data further comprises a traffic lane indicator and a traffic direction component.

7. The method of claim 1, wherein the probability is determined by a remote server, and wherein the remote server receives a plurality of distress data from the mobile sensor, and wherein the method further comprises identifying a relevant distress action in the distress data.

8. The method of claim 1, wherein the mobile sensor is integral with a vehicle, or wherein the mobile sensor is integral with a mobile device, the mobile device disposed in the vehicle, and wherein the relevant traffic data is identified from a plurality of traffic data for the road section, wherein the plurality of traffic data is indexed by a traffic time component.

9. The method of claim 1, wherein the alert is configured to initiate a road distress avoidance measure in a vehicle.

10. The method of claim 1, wherein the alert is a machine-readable instruction configured to initiate a road distress avoidance measure in a vehicle when the vehicle enters the identified road section, and wherein the method further comprises adding the alert to a database of alerts.

11. A computer system for determining the location of a road distress, comprising:

a processor;

a memory coupled to the processor, the memory configured to store program instructions executable by the processor to cause the computer system to;

receive, from a mobile sensor, a distress data for a road section, wherein the distress data comprises a distress time component and a distress action component;

identify a relevant traffic data for the road section, the relevant traffic data comprising a traffic time component that corresponds to the distress time component;

calculate a probability of a road distress on the road section based on the distress data and relevant traffic data; and

responsive to the calculated probability exceeding a predetermined threshold probability, generate an alert identifying the road section;

wherein;

the road distress comprises at least one of a hole, a swell, a rock, and debris;

the distress data pertains to a first lane in the road section, and the traffic data pertains to a second lane in the road section, the first lane being adjacent to the second lane;

the distress data comprises a rapid deviation in an x-y plane followed by a rapid return to an initial trajectory for a vehicle in the first lane; and

the traffic data comprises a lack of any vehicles in the second lane at the traffic time component that corresponds to the distress time component.

12. The computer system of claim 11, wherein the relevant traffic data is identified from a plurality of traffic data for the road section, wherein the plurality of traffic data is indexed by a traffic time component.

13. The computer system of claim 11, wherein the mobile sensor is integral with a vehicle, or wherein the mobile sensor is integral with a mobile device, the mobile device disposed in the vehicle.

14. The computer system of claim 11, wherein the mobile sensor is integral with a vehicle, or wherein the mobile sensor is integral with a mobile device, the mobile device disposed in the vehicle, and wherein the relevant traffic data is identified from a plurality of traffic data for the road section, wherein the plurality of traffic data is indexed by a traffic time component.

15. The computer system of claim 11, wherein the alert is configured to initiate a road distress avoidance measure in a vehicle.

16. The computer system of claim 11, wherein the alert is a machine-readable instruction configured to initiate a road distress avoidance measure in a vehicle when the vehicle enters the identified road section, and wherein the method further comprises adding the alert to a database of alerts.

17. A method for managing road repair resources, the method comprising:

calculating a probability of a road distress in a road section by combining sensor data from a mobile sensor with relevant traffic data; and

automatically alerting a road repair resource to request repair of the road section when the calculated probability of a road distress exceeds a predetermined threshold probability.

18. The method of claim 17, wherein the sensor data pertains to a first lane in the road section, and wherein the traffic data pertains to a second lane in the road section, the first lane being adjacent to the second lane.

19. The method of claim 17, wherein the distress data pertains to a first lane in the road section, and wherein the traffic data pertains to a second lane in the road section, the first lane being adjacent to the second lane, and wherein the relevant traffic data is identified from a plurality of traffic data for the road section, wherein the plurality of traffic data is indexed by a traffic time component.

20. The method of claim 17, wherein the mobile sensor is integral with a vehicle, or wherein the mobile sensor is integral with a mobile device, the mobile device disposed in the vehicle, and wherein the relevant traffic data is identified from a plurality of traffic data for the road section, wherein the plurality of traffic data is indexed by a traffic time component.