IP Library › Granted Patent US 12,679,417
Granted Patent B2
US 12,679,417 · App. 17/337,121 · Granted Jul 14, 2026

Assessment of a vehicle control system

Inventors: Magnus Gyllenhammar (Pixbo, SE); Carl Zandén (Lindome, SE); Majid Khorsand Vakilzadeh (Mölndal, SE)
Assignee: Zenseact AB
B60W60/0018B60W40/10B60W2520/06B60W2554/4041B60W2556/45B60W2756/10
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,679,417
App. No.
17/337,121
Filed
Jun 2, 2021
Granted
Jul 14, 2026
Kind
B2
Art Unit
3664
USPC
701/23
Abstract

The present disclosure relates to a method performed by a trajectory monitoring system of a vehicle for assessment of a vehicle control system of an advanced driver-assistance system, ADAS, or autonomous driving, AD, system of the vehicle. The trajectory monitoring system determines in view of a reference system a planned vehicle trajectory adapted to be executed by the vehicle control system during a predeterminable time period (T). The trajectory monitoring system furthermore determines following initiation and/or completion of the time period, an actual vehicle trajectory of the vehicle during the time period in view of the reference system. Moreover, the trajectory monitoring system determines an accuracy deviation measure indicating deviation between the actual vehicle trajectory and the planned vehicle trajectory. The trajectory monitoring system further communicates acknowledgment data indicative of the accuracy deviation measure.

Claims (53)

1 . A method performed by a trajectory monitoring system of a vehicle for assessment of a vehicle control system of one of an advanced driver-assistance system, ADAS, and autonomous driving, AD, system of the vehicle, the method comprising:

determining in view of a reference system a planned vehicle trajectory adapted to be executed by the vehicle control system during a predeterminable time period;

determining following at least one of initiation and completion of the time period, an actual vehicle trajectory of the vehicle during the time period in view of the reference system, the actual vehicle trajectory being determined at least in part based on data received from an on-board vehicle perception system;

mapping, based on the reference system, the planned vehicle trajectory and the actual vehicle trajectory;

determining an accuracy deviation measure indicating deviation between the mapped actual vehicle trajectory and the mapped planned vehicle trajectory;

selecting a threshold level for a deviation exceedance criteria from a plurality of threshold levels by:

determining a criticality of the accuracy deviation measure, the criticality being based on a closeness of an object in a vicinity of the vehicle; and

selecting the threshold level from the plurality of threshold levels based on the determined criticality of the accuracy deviation measure; and

communicating acknowledgment data indicative of the accuracy deviation measure based on at least a portion of the accuracy deviation measure fulfilling the deviation exceedance criteria corresponding to the selected threshold level.

2 . The method according to claim 1 , wherein the determining an accuracy deviation measure is based on comparison of at least a first actual vehicle position of the actual vehicle trajectory, at an at least first time point (t 1 ), with at least a first planned vehicle position of the planned vehicle trajectory at the at least first time point (t 1 ).

3 . The method according to claim 1 , wherein the communicating acknowledgment data comprises at least one of:

transmitting the acknowledgment data to a remote entity, the acknowledgment data comprising data reflecting at least one of the planned vehicle trajectory and the actual vehicle trajectory; and

transmitting the acknowledgment data to an on-board AD/ADAS control system adapted to control the one of the ADAS and AD system, the acknowledgment data comprising an indication to at least partly disable the ADAS or AD system.

4 . The method according to claim 3 , further comprising:

communicating, when at least a portion of the accuracy deviation measure fulfills further deviation exceedance criteria, further acknowledgment data, the deviation exceedance criteria differing from the further deviation exceedance criteria.

5 . The method according to claim 1 , further comprising:

communicating, when at least a portion of the accuracy deviation measure fulfills further deviation exceedance criteria, further acknowledgment data, the deviation exceedance criteria differing from the further deviation exceedance criteria.

6 . The method according to claim 5 , wherein the communicating further acknowledgment data comprises at least one of:

transmitting the further acknowledgment data to a remote entity, the further acknowledgment data comprising data reflecting the planned vehicle trajectory and/or the actual vehicle trajectory; and

transmitting the further acknowledgment data to an on-board AD/ADAS control system adapted to control the ADAS or AD system, the further acknowledgment data comprising an indication to at least partly disable the ADAS or AD system.

7 . A trajectory monitoring system of a vehicle for assessment of a vehicle control system of one of an advanced driver-assistance system, ADAS, and autonomous driving, AD, system of the vehicle, the trajectory monitoring system comprising:

a planned trajectory determining unit for:

determining in view of a reference system a planned vehicle trajectory adapted to be executed by the vehicle control system during a predeterminable time period, the actual vehicle trajectory being determined at least in part based on data received from an on-board vehicle perception system; and

mapping, based on the reference system, the planned vehicle trajectory;

an actual trajectory determining unit for:

determining following initiation and/or completion of the time period, an actual vehicle trajectory of the vehicle during the time period in view of the reference system; and

mapping, based on the reference system, the actual vehicle trajectory;

a deviation determining unit for determining an accuracy deviation measure indicating deviation between the mapped actual vehicle trajectory and the mapped planned vehicle trajectory and for selecting a threshold level for a deviation exceedance criteria from a plurality of threshold levels by:

determining a criticality of the accuracy deviation measure, the criticality being based on a closeness of an object in a vicinity of the vehicle; and

selecting the threshold level from the plurality of threshold levels based on the determined criticality of the accuracy deviation measure; and

an acknowledgment communicating unit for communicating acknowledgment data indicative of the accuracy deviation measure based on at least a portion of the accuracy deviation measure fulfilling the deviation exceedance criteria corresponding to the selected threshold level.

8 . The trajectory monitoring system according to claim 7 , wherein the deviation determining unit is configured to determine the accuracy deviation measure based on comparison of at least a first actual vehicle position of the actual vehicle trajectory, at an at least first time point (t 1 ), with at least a first planned vehicle position of the planned vehicle trajectory at the at least first time point (t 1 ).

9 . The trajectory monitoring system according to claim 7 , wherein the acknowledgment communicating unit is configured to at least one of:

transmit the acknowledgment data to a remote entity, the acknowledgment data comprising data reflecting at least one of the planned vehicle trajectory and the actual vehicle trajectory; and

transmit the acknowledgment data to an on-board AD/ADAS control system configured to control the one of the ADAS and AD system, the acknowledgment data comprising an indication to at least partly disable the one of the ADAS and AD system.

10 . The trajectory monitoring system according to claim 7 , further comprising:

a further acknowledgment communicating unit for communicating, when at least a portion of the accuracy deviation measure fulfills further deviation exceedance criteria, further acknowledgment data, the deviation exceedance criteria differing from the further deviation exceedance criteria.

11 . The trajectory monitoring system according to claim 9 , further comprising:

a further acknowledgment communicating unit for communicating, when at least a portion of the accuracy deviation measure fulfills further deviation exceedance criteria, further acknowledgment data, the deviation exceedance criteria differing from the further deviation exceedance criteria.

12 . The trajectory monitoring system according to claim 10 , wherein the further acknowledgment communicating unit is configured to at least one of:

transmit the further acknowledgment data to a remote entity, the further acknowledgment data comprising data reflecting the planned vehicle trajectory and/or the actual vehicle trajectory; and

transmit the further acknowledgment data to an on-board AD/ADAS control system configured to control the ADAS or AD system, the further acknowledgment data comprising an indication to at least partly disable the one of the ADAS and AD system.

13 . The trajectory monitoring system according to claim 7 , wherein the trajectory monitoring system is comprised in a vehicle.

14 . A computer storage medium storing a computer program containing computer program code that when executed causes one of a computer and a processor to perform a method for assessment of a vehicle control system of one of an advanced driver-assistance system, ADAS, and autonomous driving, AD, system of the vehicle, the method comprising:

determining in view of a reference system a planned vehicle trajectory adapted to be executed by the vehicle control system during a predeterminable time period;

determining following at least one of initiation and completion of the time period, an actual vehicle trajectory of the vehicle during the time period in view of the reference system, the actual vehicle trajectory being determined at least in part based on data received from an on-board vehicle perception system;

mapping, based on the reference system, the planned vehicle trajectory and the actual vehicle trajectory;

determining an accuracy deviation measure indicating deviation between the mapped actual vehicle trajectory and the mapped planned vehicle trajectory;

selecting a threshold level for a deviation exceedance criteria from a plurality of threshold levels by:

determining a criticality of the accuracy deviation measure, the criticality being based on a closeness of an object in a vicinity of the vehicle; and

selecting the threshold level from the plurality of threshold levels based on the determined criticality of the accuracy deviation measure; and

communicating acknowledgment data indicative of the accuracy deviation measure based on at least a portion of the accuracy deviation measure fulfilling the deviation exceedance criteria corresponding to the selected threshold level.

15 . The computer storage medium according to claim 14 , wherein the determining an accuracy deviation measure is based on comparison of at least a first actual vehicle position of the actual vehicle trajectory, at an at least first time point (t 1 ), with at least a first planned vehicle position of the planned vehicle trajectory at the at least first time point (t 1 ).

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 3, 2021
From: GYLLENHAMMAR, MAGNUS; ZANDÉN, CARL; VAKILZADEH, MAJID KHORSAND
To: ZENUITY AB
Reel/Frame 056434/0981 →
Priority Claims (1)
EP 20181332 · Jun 22, 2020 · regional
Continuity (1)
Related Publication 20210394794A1 · Dec 23, 2021
References Cited (21)
US 8954217B1 · Montemerlo · 2015 [cited by examiner]
US 9315178B1 · Ferguson et al. · 2016 [cited by applicant]
US 20190064823A1 · Jiang · 2019 [cited by examiner]
US 20200039528A1 · Ewert · 2020 [cited by applicant]
WO WO02055356 · 2002 [cited by examiner]
WO WO02055356A1 · 2002 [cited by examiner]
WO WO2017079301 · 2017 [cited by examiner]
WO WO2017079301A1 · 2017 [cited by examiner]
WO WO2020079698 · 2020 [cited by examiner]
Espacnet translation of WO 02055356 (Year: 2002). [cited by examiner]
S. Wei, P. E. Pfeffer and J. Edelmann, “State of the Art: Ongoing Research in Assessment Methods for Lane Keeping Assistance Systems,” in IEEE Transactions on Intelligent Vehicles. 2023 (Year: 2023). [cited by examiner]
A. Reschka, J. R. Böhmer, T. Nothdurft, P. Hecker, B. Lichte and M. Maurer, “A surveillance and safety system based on performance criteria and functional degradation for an autonomous vehicle,” 2012 15th Int. IEEE Conf… [cited by examiner]
Muhammad Sualeh and Gon-Woo Kim “Dynamic Multi-LiDAR based multiple Object Detection and Tracking,” Sensors 2019, 19, 14 (Year: 2019). [cited by examiner]
Of Muhammad Sualeh and Gon-Woo Kim “Dynamic Multi-LiDAR based multiple Object Detection and Tracking,” Sensors 2019, 19, 1474. (Year: 2019). [cited by examiner]
A. Reschka, J. R. Böhmer, T. Nothdurft, P. Hecker, B. Lichte and M. Maurer, “A surveillance and safety system based on performance criteria and functional degradation for an autonomous vehicle,” 2012 15th International … [cited by examiner]
B. Thomas, J. Lowenau, S. Durekovic, M. Landwehr and M. Flament, “Test Results and Validation of the FeedMAP Framework with ADAS Applications,” 2008 11th International IEEE Conference on Intelligent Transportation Syste… [cited by examiner]
F. Biral, R. Antonello, E. Bertolazzi and F. Zendri, “Integration of optimal maneuver prediction in active safety control systems: considerations on driving safety improvements,” 2010 IEEE International Conference on Co… [cited by examiner]
Muhammad Sualeh and Gon-Woo Kim “Dynamic Multi-LiDAR based multiple Object Detection and Tracking,” Sensors 2019, 19, 1474. (Year: 2019). [cited by examiner]
European Search Report dated Dec. 9, 2020 for International Application No. 20181332.6 filed on Jun. 22, 2020, consisting of 9-pages. [cited by applicant]
Comparison of Trajectory Tracking Controllers For Emergency Situations; Daniel Heb et al; 2013 IEEE Intelligent Vehicles Symposium (iv), IEEE, Jun. 23, 2013, p. 163-170, XP032501964; consisting of 8 pages. [cited by applicant]
Chinese Office Action and English Translation dated Jul. 2, 2025 for Application No. 202110681448.4, consisting of 16 pages. [cited by applicant]