US-20260125081-A1 - SYSTEMS AND METHODS FOR IDENTIFYING A GHOST VEHICLE

Abstract

A method includes the detection of an object in a marshaling environment, a determination of whether one or more conditions is satisfied in response to the detection of the object, a transmission of a request for data originating from one or more sensors of each automated vehicle of one or more automated vehicles, a receipt of the requested data from the one or more automated vehicles, and a performance of one or more corrective actions based on an analysis of the requested data.

Inventors

• Stuart C. Salter
• Krishna Bandi
• Ryan O'Gorman
• Brendan Diamond
• Vyas Darshan Shenoy
• Mario Anthony Santillo

Assignees

• FORD GLOBAL TECHNOLOGIES, LLC

Dates

Publication Date

20260507

Application Date

20241106

Claims (20)

1. 1 . A method comprising: detecting an object in a marshaling environment; determining whether one or more conditions is satisfied in response to the detection of the object; transmitting, to one or more automated vehicles, a request for data originating from one or more sensors of each automated vehicle of the one or more automated vehicles in response to the one or more conditions being satisfied; receiving, from the one or more automated vehicles, the requested data; and performing one or more corrective actions based on an analysis of the requested data.
2. 2 . The method of claim 1 , wherein the one or more conditions includes one or more of: an unexpected location of the object; an inability to identify a historical pathway associated with each automated vehicle of the one or more automated vehicles; an inconsistency between the data originating from the one or more sensors and a controlled location of the one or more automated vehicles, a relative position of the one or more automated vehicles, or a combination thereof; unexpected spacing between each automated vehicle of the one or more automated vehicles; an inability to account for a location of each automated vehicle of the one or more automated vehicles; and an inconsistency between a total number of automated vehicles of the one or more automated and an expected total number of automated vehicles of the one or more automated vehicles.
3. 3 . The method of claim 1 , wherein the analysis of the requested data comprises: determining whether a sensor output associated with one or more sensors of an infrastructure system matches the requested data.
4. 4 . The method of claim 3 , wherein the performance of the one or more corrective actions is further based on a determination that the sensor output does not match the requested data.
5. 5 . The method of claim 1 , wherein the performance of the one or more corrective actions includes one of: initiating one or more reset routines; switching from a first set of one or more sensors of an infrastructure system to a second set of one or more sensors of the infrastructure system; and causing each automated vehicle of the one or more automated vehicles to follow one or more movements of a preceding automated vehicle of the one or more automated vehicles and for a lead automated vehicle of the one or more automated vehicles to follow a historical pathway.
6. 6 . The method of claim 1 , wherein the performance of the one or more corrective actions includes: collecting metadata associated with the object; determining one or more object-prone areas within the marshaling environment; and generating a recommendation to replace one or more sensors of an infrastructure system or to install a second set of one or more sensors based on the determination of the one or more object-prone areas.
7. 7 . A method comprising: detecting an object in a marshaling environment; determining whether one or more conditions is satisfied in response to the detection of the object; transmitting, to one or more automated vehicles, one or more instructions for analyzing data originating from one or more sensors of each automated vehicle of the one or more automated vehicles in response to the one or more conditions being satisfied; receiving, from the one or more automated vehicles, one or more results associated with an analysis of the data performed by the one or more automated vehicles; and performing one or more corrective actions based on the one or more results associated with the analysis of the data.
8. 8 . The method of claim 7 , wherein the one or more conditions includes one or more of: an unexpected location of the object; an inability to identify a historical pathway associated with each automated vehicle of the one or more automated vehicles; an inconsistency between the data originating from the one or more sensors and a controlled location of the one or more automated vehicles, a relative position of the one or more automated vehicles, or a combination thereof; unexpected spacing between each automated vehicle of the one or more automated vehicles; an inability to account for a location of each automated vehicle of the one or more automated vehicles; and an inconsistency between a total number of automated vehicles of the one or more automated and an expected total number of automated vehicles of the one or more automated vehicles.
9. 9 . The method of claim 7 , wherein the analysis of the data by the one or more automated vehicles further comprises: analyzing one or more video recordings of the marshaling environment from each automated vehicle of the one or more automated vehicles; and verifying a location of the object based on the analysis of the one or more video recordings.
10. 10 . The method of claim 7 , wherein the performance of the one or more corrective actions includes one of: initiating one or more reset routines; switching from a first set of one or more sensors of an infrastructure system to a second set of one or more sensors of the infrastructure system; and causing each automated vehicle of the one or more automated vehicles to follow one or more movements of a preceding automated vehicle of the one or more automated vehicles and for a lead automated vehicle of the one or more automated vehicles to follow a historical pathway.
11. 11 . The method of claim 7 , wherein the performance of the one or more corrective actions includes: collecting metadata associated with the object; determining one or more object-prone areas within a marshaling environment; and generating a recommendation to replace one or more sensors of an infrastructure system or to install a second set of one or more sensors based on the determination of the one or more object-prone areas.
12. 12 . A system comprising: an infrastructure system configured to: detect an object in a marshaling environment, determine whether one or more conditions is satisfied in response to the detection of the object, transmit a request for data originating from one or more sensors of each automated vehicle of one or more automated vehicles in response to the one or more conditions being satisfied, receive the requested data, and perform one or more corrective actions based on an analysis of the requested data; and one or more automated vehicles configured to: receive the request for the data originating from the one or more sensors of each automated vehicle of the one or more automated vehicles, and transmit the requested data.
13. 13 . The system of claim 12 , wherein the one or more automated vehicles is further configured to: receive one or more instructions for analyzing the data originating from the one or more sensors of each automated vehicle of the one or more automated vehicles in response to the one or more conditions being satisfied; and transmit one or more results associated with the analysis of the data performed by the one or more automated vehicles.
14. 14 . The system of claim 13 , wherein the infrastructure system is further configured to: transmit the one or more instructions for analyzing the data originating from the one or more sensors of each automated vehicle of the one or more automated vehicles; and receive the one or more results.
15. 15 . The system of claim 13 , wherein performing the analysis of the data by the one or more automated vehicles comprises: analyzing one or more video recordings of the marshaling environment from each automated vehicle of the one or more automated vehicles; and verifying a location of the object based on the analysis of the one or more video recordings.
16. 16 . The system of claim 12 , wherein the one or more conditions includes one or more of: an unexpected location of the object; an inability to identify a historical pathway associated with each automated vehicle of the one or more automated vehicles; an inconsistency between the data originating from the one or more sensors and a controlled location of the one or more automated vehicles, a relative position of the one or more automated vehicles, or a combination thereof; unexpected spacing between each automated vehicle of the one or more automated vehicles; an inability to account for a location of each automated vehicle of the one or more automated vehicles; and an inconsistency between a total number of automated vehicles of the one or more automated and an expected total number of automated vehicles of the one or more automated vehicles.
17. 17 . The system of claim 12 , wherein analyzing the requested data by the infrastructure system comprises: determining whether a sensor output associated with one or more sensors of the infrastructure system matches the requested data.
18. 18 . The system of claim 17 , wherein the performance of the one or more corrective actions is further based on a determination that the sensor output does not match the requested data.
19. 19 . The system of claim 12 , wherein performing the one or more corrective actions by the infrastructure system comprises one of: initiating one or more reset routines; switching from a first set of one or more sensors of the infrastructure system to a second set of one or more sensors of the infrastructure system; and causing each automated vehicle of the one or more automated vehicles to follow one or more movements of a preceding automated vehicle of the one or more automated vehicles and for a lead automated vehicle of the one or more automated vehicles to follow a historical pathway.
20. 20 . The system of claim 12 , wherein performing the one or more corrective actions by the infrastructure system comprises: collecting metadata associated with the object; determining one or more object-prone areas within the marshaling environment; and generating a recommendation to replace one or more sensors of the infrastructure system or to install a second set of one or more sensors based on the determination of the one or more object-prone areas.

Description

FIELD The present disclosure relates to identifying a ghost vehicle. More specifically, the present disclosure relates to identifying a ghost vehicle in a marshaling setting. BACKGROUND The statements in this section merely provide background information related to the present disclosure and may not constitute prior art. Ghost vehicles, or vehicles that do not physically exist, may be detected by infrastructure sensors in marshaling settings. The detection of the ghost vehicles can disrupt marshaling of one or more vehicles as the infrastructure sensors perceive the ghost vehicles as real vehicles, thus attempting to marshal the real vehicles accordingly. The detection of the ghost vehicles thereby results in the marshaling of real vehicles coming to a stop so that the ghost vehicles can be properly identified and the marshaling of the real vehicles may resume without considering the identified ghost vehicles. The present disclosure address these and other issues related to the identification of a ghost vehicle. SUMMARY This section provides a general summary of the disclosure and is not a comprehensive disclosure of its full scope or all of its features. The present disclosure provides a method comprising: detecting an object in a marshaling environment; determining whether one or more conditions is satisfied in response to the detection of the object; transmitting, to one or more automated vehicles, a request for data originating from one or more sensors of each automated vehicle of the one or more automated vehicles in response to the one or more conditions being satisfied; receiving, from the one or more automated vehicles, the requested data; and performing one or more corrective actions based on an analysis of the requested data; wherein the one or more conditions includes one or more of: an unexpected location of the object; an inability to identify a historical pathway associated with each automated vehicle of the one or more automated vehicles; an inconsistency between the data originating from the one or more sensors and a controlled location of the one or more automated vehicles, a relative position of the one or more automated vehicles, or a combination thereof; unexpected spacing between each automated vehicle of the one or more automated vehicles; an inability to account for a location of each automated vehicle of the one or more automated vehicles; and an inconsistency between a total number of automated vehicles of the one or more automated and an expected total number of automated vehicles of the one or more automated vehicles; wherein the analysis of the requested data comprises: determining whether a sensor output associated with one or more sensors of an infrastructure system matches the requested data; wherein the performance of the one or more corrective actions is further based on a determination that the sensor output does not match the requested data; wherein the performance of the one or more corrective actions includes one of: initiating one or more reset routines; switching from a first set of one or more sensors of an infrastructure system to a second set of one or more sensors of the infrastructure system; and causing each automated vehicle of the one or more automated vehicles to follow one or more movements of a preceding automated vehicle of the one or more automated vehicles and for a lead automated vehicle of the one or more automated vehicles to follow a historical pathway; and wherein the performance of the one or more corrective actions includes: collecting metadata associated with the object; determining one or more object-prone areas within the marshaling environment; and generating a recommendation to replace one or more sensors of an infrastructure system or to install a second set of one or more sensors based on the determination of the one or more object-prone areas. The present disclosure provides another method comprising: detecting an object in a marshaling environment; determining whether one or more conditions is satisfied in response to the detection of the object; transmitting, to one or more automated vehicles, one or more instructions for analyzing data originating from one or more sensors of each automated vehicle of the one or more automated vehicles in response to the one or more conditions being satisfied; receiving, from the one or more automated vehicles, one or more results associated with an analysis of the data performed by the one or more automated vehicles; and performing one or more corrective actions based on the one or more results associated with the analysis of the data; wherein the one or more conditions includes one or more of: an unexpected location of the object; an inability to identify a historical pathway associated with each automated vehicle of the one or more automated vehicles; an inconsistency between the data originating from the one or more sensors and a controlled location of the one or more automated vehicles, a relative po