IP Library Granted Patent US 12,017,665
Granted Patent B2
US 12,017,665 · App. 17/681,063 · Granted Jun 25, 2024

Systems and methods for detecting misbehavior behavior at an autonomous driving system

Inventors: Wenyuan Qi (Shanghai, CN); Kemal Ertugrul Tepe (Huntington Woods, MI); Mohammad Naserian (Windsor, CA); Tianxiang Cao (Shanghai, CN); Zhengyu Xing (Shanghai, CN)
Assignee: GM GLOBAL TECHNOLOGY OPERATIONS LLC
B60W50/0205B60W50/0098G07C5/008H04W12/121B60W2050/0215B60W2556/65
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Quick Facts
Patent No.
US 12,017,665
App. No.
17/681,063
Granted
Jun 25, 2024
Kind
B2
Abstract

An automated driving system (ADS) of an autonomous vehicle includes a communication module, a perception module, a misbehavior detection module, and a processor. The communication module is configured to receive a vehicle-to-vehicle (V2V) message comprising message-based vehicle data. The perception module configured to receive sensor data from at least one vehicle sensing device. The misbehavior detection module is configured to determine whether the V2V message is one of a legitimate message and a malicious message based at least in part on a comparison of the message-based vehicle data with sensor-based vehicle data generated based on the sensor data. The processor is configured to manage performance of the autonomous vehicle in accordance with the message-based vehicle data based on the determination. Other embodiments are described and claimed.

Claims (42)

1. An automated driving system (ADS) of an autonomous vehicle including a misbehavior detection system, comprising:

a communication module configured to receive a vehicle-to-vehicle (V2V) message comprising message-based vehicle data;

a perception module configured to receive sensor data from at least one vehicle sensing device;

a misbehavior detection module configured to determine whether the V2V message is one of a legitimate message and a malicious message based at least in part on a comparison of the message-based vehicle data with sensor-based vehicle data generated based on the sensor data; and

a processor configured to manage performance of the autonomous vehicle in accordance with the message-based vehicle data based on the determination,

wherein the message-based vehicle data comprises a vehicle location of a source vehicle of the V2V message, and the misbehavior detection module is configured to:

determine whether the vehicle location of the source vehicle is disposed within a sensor detection area associated with the at least one vehicle sensing device; and

compare a reputation score received from a security credentials management system (SCMS) and associated with a vehicle identifier associated with the V2V message with a reputation score threshold to identify whether the V2V message is one of the legitimate message and the malicious message based on the determination.

2. The system of claim 1 , wherein the misbehavior detection module is configured to determine whether the V2V message is one of the legitimate message and the malicious message based at least in part on performance of a plausibility check of the message-based vehicle data.

3. The system of claim 1 , wherein the misbehavior detection module is configured to:

and

perform a sensor operation check of the at least one vehicle sensing device based on the determination of whether the vehicle location of the source vehicle is disposed within the sensor detection area associated with the at least one vehicle sensing device.

4. The system of claim 1 , wherein the misbehavior detection module is configured to:

compare the vehicle location of the source vehicle received in the V2V message with historical source vehicle location data to identify whether the V2V message is one of the legitimate message and the malicious message based on the determination of whether the vehicle location of the source vehicle is disposed within the sensor detection area associated with the at least one vehicle sensing device.

5. The system of claim 1 , wherein upon a determination that the V2V message is the malicious message, a misbehavior reporting module is configured to report the vehicle identifier associated with the V2V message to the SCMS.

6. A non-transitory computer readable medium comprising instructions stored thereon for detection of misbehavior at an automated driving system (ADS), that upon execution by a processor, cause the processor to:

receive a vehicle-to-vehicle (V2V) message comprising message-based vehicle data;

receive sensor data received from at least one vehicle sensing device;

determine whether the V2V message is one of a legitimate message and a malicious message based at least in part on a comparison of the message-based vehicle data with sensor-based vehicle data generated based on the sensor data;

manage performance of an autonomous vehicle in accordance with the message-based vehicle data based on the determination;

determine whether a vehicle location of a source vehicle is disposed within a sensor detection area associated with the at least one vehicle sensing device, the message-based vehicle data comprising the vehicle location of the source vehicle of the V2V message; and

compare a reputation score received from a security credentials management system (SCMS) and associated with a vehicle identifier associated with the V2V message with a reputation score threshold to identify whether the V2V message is one of the legitimate message and the malicious message based on the determination.

7. The non-transitory computer readable medium of claim 6 , further comprising instructions to cause the processor to determine whether the V2V message is one of the legitimate message and the malicious message based at least in part on a comparison of the message-based vehicle data with the sensor-based vehicle data generated based on the sensor data, the message-based vehicle data comprising the vehicle location of the source vehicle of the V2V message and the sensor-based vehicle data comprising a sensor-based vehicle location of the source vehicle based on the sensor data.

8. The non-transitory computer readable medium of claim 6 , further comprising instructions to cause the processor to determine whether the V2V message is one of the legitimate message and the malicious message based at least in part on performance of a plausibility check of the message-based vehicle data.

9. The non-transitory computer readable medium of claim 6 , further comprising instructions to cause the processor to:

perform a sensor operation check of the at least one vehicle sensing device based on the determination of whether the vehicle location of the source vehicle is disposed within the sensor detection area associated with the at least one vehicle sensing device.

10. The non-transitory computer readable medium of claim 6 , further comprising instructions to cause the processor to:

compare the vehicle location of the source vehicle received in the V2V message with historical source vehicle location data to identify whether the V2V message is one of the legitimate message and the malicious message based on the determination.

11. The non-transitory computer readable medium of claim 6 , further comprising instructions to cause the processor to upon a determination that the V2V message is the malicious message, report the vehicle identifier associated with the V2V message to the SCMS.

12. A method of detecting misbehavior at an automated driving system (ADS) comprising:

receiving a vehicle-to-vehicle (V2V) message comprising message-based vehicle data at a communication module;

receiving sensor data received from at least one vehicle sensing device at a perception module;

determining whether the V2V message is one of a legitimate message and a malicious message based at least in part on a comparison of the message-based vehicle data with sensor-based vehicle data generated based on the sensor data at a misbehavior detection module;

managing performance of an autonomous vehicle in accordance with the message-based vehicle data based on the determination;

determining whether a vehicle location of a source vehicle is disposed within a sensor detection area associated with the at least one vehicle sensing device, the message-based vehicle data comprising the vehicle location of the source vehicle of the V2V message; and

comparing a reputation score received from a security credentials management system (SCMS) and associated with a vehicle identifier associated with the V2V message with a reputation score threshold to identify whether the V2V message is one of the legitimate message and the malicious message based on the determination.

13. The method of claim 12 , further comprising determining whether the V2V message is one of the legitimate message and the malicious message based at least in part on a comparison of the message-based vehicle data with the sensor-based vehicle data generated based on the sensor data, the message-based vehicle data comprising the vehicle location of the source vehicle of the V2V message and the sensor-based vehicle data comprising a sensor-based vehicle location of the source vehicle based on the sensor data.

14. The method of claim 12 , further comprising determining whether the V2V message is one of the legitimate message and the malicious message based at least in part on performance of a plausibility check of the message-based vehicle data.

15. The method of claim 12 , further comprising:

performing a sensor operation check of the at least one vehicle sensing device based on the determination of whether the vehicle location of the source vehicle is disposed within the sensor detection area associated with the at least one vehicle sensing device.

16. The method of claim 12 , further comprising:

comparing the vehicle location of the source vehicle received in the V2V message with historical source vehicle location data to identify whether the V2V message is one of the legitimate message and the malicious message based on the determination of whether the vehicle location of the source vehicle is disposed within the sensor detection area associated with the at least one vehicle sensing device.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 28, 2022
From: QI, WENYUAN; TEPE, KEMAL ERTUGRUL; NASERIAN, MOHAMMAD; CAO, TIANXIANG; XING, ZHENGYU
To: GM GLOBAL TECHNOLOGY OPERATIONS LLC
Reel/Frame 059262/0275 →
Priority Claims (1)
CN 202210110707.2 · Jan 29, 2022 · national
Continuity (1)
Related Publication 20230286520A1 · Sep 14, 2023