IP Library Granted Patent US 12,488,682
Granted Patent B2
US 12,488,682 · App. 18/340,294 · Granted Dec 2, 2025

Message broadcasting for vehicles

Inventors: Stephen Marc Chaves (Philadelphia, PA); Daniel Warren Mellinger, III (Raleigh, NC); Paul Daniel Martin (Devon, PA); Michael Joshua Shomin (Philadelphia, PA)
Assignee: QUALCOMM Incorporated
G08G1/0141G08G1/0112G08G1/162G08G1/166
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Quick Facts
Patent No.
US 12,488,682
App. No.
18/340,294
Granted
Dec 2, 2025
Kind
B2
Abstract

Various aspects may include methods enabling a vehicle to broadcast intentions and/or motion plans to surrounding vehicles. Various aspects include methods for using intentions and/or motion plans received from one or more surrounding vehicles.

Claims (110)

1 . A method of controlling a vehicle, comprising:

receiving an intention message including a motion plan from a transmitting vehicle,

wherein the motion plan comprises a trajectory of the transmitting vehicle and one or more vehicle descriptors associated with the transmitting vehicle and wherein the one or more vehicle descriptors comprise a vehicle physical capability,

wherein the vehicle physical capability comprises at least one of a turning radius, a vehicle top speed, and a vehicle maximum acceleration;

parsing the intention message to identify the motion plan for the transmitting vehicle;

determining an expected region of interest for the vehicle based at least in part on the motion plan;

selecting a first detection algorithm for detecting a sensor perceptible attribute of the transmitting vehicle based on receiving the motion plan of the transmitting vehicle,

wherein the first detection algorithm is associated with a first confidence threshold for reporting detection of the transmitting vehicle in the expected region of interest,

wherein the first confidence threshold is lower than a second confidence threshold associated with a second detection algorithm;

receiving sensor data from one or more sensors disposed in or on the vehicle;

applying the selected first detection algorithm to a limited subset of received sensor data from the expected region of interest;

setting a future behavior prediction for the transmitting vehicle based at least in part on a vehicle behavior model for the transmitting vehicle limited by the vehicle physical capability and the expected region of interest, wherein setting the future behavior prediction for the transmitting vehicle is based on the application of the selected first detection algorithm; and

controlling the vehicle based at least in part on the motion plan and the future behavior prediction.

2 . The method of claim 1 , wherein the one or more vehicle descriptors comprise the sensor perceptible attribute.

3 . The method of claim 1 , wherein controlling the vehicle based at least in part on the motion plan and the future behavior prediction comprises:

applying the first detection algorithm to the received sensor data at the expected region of interest to detect the transmitting vehicle in the received sensor data based at least in part on the sensor perceptible attribute.

4 . The method of claim 1 , wherein:

the first confidence threshold is fifty percent confidence threshold, and the first detection algorithm reports detection of the sensor perceptible attribute based on confidence of the detection of the sensor perceptible attribute being above the fifty percent confidence threshold; and

the second confidence threshold is a ninety percent confidence threshold, and the second detection algorithm reports detection of the sensor perceptible attribute based on confidence of the detection of the sensor perceptible attribute being above the ninety percent confidence threshold.

5 . The method of claim 1 , wherein controlling the vehicle based at least in part on the motion plan and the future behavior prediction comprises:

correlating vehicle detection sensor data with the transmitting vehicle based at least in part on the sensor perceptible attribute.

6 . The method of claim 1 , further comprising:

determining whether a behavior of the transmitting vehicle conforms to the future behavior prediction; and

updating the future behavior prediction based at least in part on the vehicle physical capability in response to determining that the behavior of the transmitting vehicle does not conform to the future behavior prediction.

7 . The method of claim 1 , wherein the one or more vehicle descriptors comprise a vehicle location attribute.

8 . The method of claim 7 , wherein controlling the vehicle based at least in part on the motion plan and the future behavior prediction comprises:

determining a position of the transmitting vehicle based at least in part on the vehicle location attribute;

determining whether a comparison between a position of the vehicle and the position of the transmitting vehicle indicate an error; and

triggering a recalculation of the position of the vehicle in response to determining the comparison between the position of the vehicle and the position of the transmitting vehicle indicate an error.

9 . The method of claim 1 , wherein controlling the vehicle based at least in part on the motion plan and the future behavior prediction comprises:

determining whether the motion plan is unsafe; and

sending a safety warning to the transmitting vehicle in response to determining the motion plan is unsafe.

10 . The method of claim 1 , wherein the vehicle behavior model for the transmitting vehicle is limited by the turning radius of the transmitting vehicle to constrain potential turning paths of the transmitting vehicle.

11 . A processing device for use in a vehicle, the processing device configured to:

receive an intention message including a motion plan from a transmitting vehicle,

wherein the motion plan comprises a trajectory of the transmitting vehicle and one or more vehicle descriptors associated with the transmitting vehicle and wherein the one or more vehicle descriptors comprise a vehicle physical capability,

wherein the vehicle physical capability comprises at least one of a turning radius, a vehicle top speed, and a vehicle maximum acceleration;

parse the intention message to identify the motion plan for the transmitting vehicle;

determine an expected region of interest for the vehicle based at least in part on the motion plan;

select a first detection algorithm for detecting a sensor perceptible attribute of the transmitting vehicle based on receiving the motion plan of the transmitting vehicle,

wherein the first detection algorithm is associated with a first confidence threshold for reporting detection of the transmitting vehicle in the expected region of interest,

wherein the first confidence threshold is lower than a second confidence threshold associated with a second detection algorithm;

receive sensor data from one or more sensors disposed in or on the vehicle;

apply the selected first detection algorithm to a limited subset of received sensor data from the expected region of interest;

set a future behavior prediction for the transmitting vehicle based at least in part on a vehicle behavior model for the transmitting vehicle limited by the vehicle physical capability and the expected region of interest, wherein setting the future behavior prediction for the transmitting vehicle is based on the application of the selected first detection algorithm; and

control the vehicle based at least in part on the motion plan and the future behavior prediction.

12 . The processing device of claim 11 , wherein the one or more vehicle descriptors comprise the sensor perceptible attribute.

13 . The processing device of claim 11 , wherein the processing device is configured to control the vehicle based at least in part on the motion plan and the future behavior prediction by:

applying the first detection algorithm to the received sensor data at the expected region of interest to detect the transmitting vehicle in the received sensor data based at least in part on the sensor perceptible attribute.

14 . The processing device of claim 11 , wherein:

the first confidence threshold is fifty percent confidence threshold, and the first detection algorithm reports detection of the sensor perceptible attribute based on confidence of the detection of the sensor perceptible attribute being above the fifty percent confidence threshold; and

the second confidence threshold is a ninety percent confidence threshold, and the second detection algorithm reports detection of the sensor perceptible attribute based on confidence of the detection of the sensor perceptible attribute being above the ninety percent confidence threshold.

15 . The processing device of claim 11 , wherein the processing device is configured to control the vehicle based at least in part on the motion plan and the future behavior prediction by:

correlating vehicle detection sensor data with the transmitting vehicle based at least in part on the sensor perceptible attribute.

16 . The processing device of claim 11 , wherein the processing device is further configured to:

determine whether a behavior of the transmitting vehicle conforms to the future behavior prediction; and

update the future behavior prediction based at least in part on the vehicle physical capability in response to determining that the behavior of the transmitting vehicle does not conform to the behavior prediction.

17 . The processing device of claim 11 , wherein the one or more vehicle descriptors comprise a vehicle location attribute.

18 . The processing device of claim 17 , wherein the processing device is configured to control the vehicle based at least in part on the motion plan and the future behavior prediction by:

determining a position of the transmitting vehicle based at least in part on the vehicle location attribute;

determining whether a comparison between a position of the vehicle and the position of the transmitting vehicle indicate an error; and

triggering a recalculation of the position of the vehicle in response to determining the comparison between the position of the vehicle and the position of the transmitting vehicle indicate an error.

19 . The processing device of claim 11 , wherein the processing device is configured to control the vehicle based at least in part on the motion plan and the future behavior prediction by:

determining whether the motion plan is unsafe; and

sending a safety warning to the transmitting vehicle in response to determining the motion plan is unsafe.

20 . The processing device of claim 11 , wherein the vehicle behavior model for the transmitting vehicle is limited by the turning radius of the transmitting vehicle to constrain potential turning paths of the transmitting vehicle.

21 . A processing device, comprising:

means for receiving an intention message including a motion plan from a transmitting vehicle,

wherein the motion plan comprises a trajectory of the transmitting vehicle and one or more vehicle descriptors associated with the transmitting vehicle and wherein the one or more vehicle descriptors comprise a vehicle physical capability,

wherein the vehicle physical capability comprises at least one of a turning radius, a vehicle top speed, and a vehicle maximum acceleration;

means for parsing the intention message to identify the motion plan for the transmitting vehicle;

means for determining an expected region of interest for the vehicle based at least in part on the motion plan;

means for selecting a first detection algorithm for detecting a sensor perceptible attribute of the transmitting vehicle based on receiving the motion plan of the transmitting vehicle,

wherein the first detection algorithm is associated with a first confidence threshold for reporting detection of the transmitting vehicle in the expected region of interest,

wherein the first confidence threshold is lower than a second confidence threshold associated with a second detection algorithm;

means for receiving sensor data from one or more sensors disposed in or on the vehicle;

means for applying the selected first detection algorithm to a limited subset of received sensor data from the expected region of interest;

means for setting a future behavior prediction for the transmitting vehicle based at least in part on a vehicle behavior model for the transmitting vehicle limited by the vehicle physical capability and the expected region of interest, wherein setting the future behavior prediction for the transmitting vehicle is based on the application of the selected first detection algorithm; and

means for controlling the vehicle based at least in part on the motion plan and the future behavior prediction.

22 . The processing device of claim 21 , wherein the one or more vehicle descriptors comprise the sensor perceptible attribute.

23 . The processing device of claim 21 , wherein means for controlling the vehicle based at least in part on the motion plan and the future behavior prediction comprises:

means for applying the first detection algorithm to the received sensor data at the expected region of interest to detect the transmitting vehicle in the received sensor data based at least in part on the sensor perceptible attribute.

24 . The processing device of claim 21 , wherein:

the first confidence threshold is fifty percent confidence threshold, and the first detection algorithm reports detection of the sensor perceptible attribute based on confidence of the detection of the sensor perceptible attribute being above the fifty percent confidence threshold; and

the second confidence threshold is a ninety percent confidence threshold, and the second detection algorithm reports detection of the sensor perceptible attribute based on confidence of the detection of the sensor perceptible attribute being above the ninety percent confidence threshold.

25 . The processing device of claim 21 , wherein means for controlling the vehicle based at least in part on the motion plan and the future behavior prediction comprises:

means for correlating vehicle detection sensor data with the transmitting vehicle based at least in part on the sensor perceptible attribute.

26 . The processing device of claim 21 , further comprising:

means for determining whether a behavior of the transmitting vehicle conforms to the future behavior prediction; and

means for updating the future behavior prediction based at least in part on the vehicle physical capability in response to determining that the behavior of the transmitting vehicle does not conform to the future behavior prediction.

27 . The processing device of claim 21 , wherein the one or more vehicle descriptors comprise a vehicle location attribute.

28 . The processing device of claim 27 , wherein means for controlling the vehicle based at least in part on the motion plan and the future behavior prediction comprises:

means for determining a position of the transmitting vehicle based at least in part on the vehicle location attribute;

means for determining whether a comparison between a position of the vehicle and the position of the transmitting vehicle indicate an error; and

means for triggering a recalculation of the position of the vehicle in response to determining the comparison between the position of the vehicle and the position of the transmitting vehicle indicate an error.

29 . The processing device of claim 21 , wherein means for controlling the vehicle based at least in part on the motion plan and the future behavior prediction comprises:

means for determining whether the motion plan is unsafe; and

means for sending a safety warning to the transmitting vehicle in response to determining the motion plan is unsafe.

30 . A non-transitory processor-readable storage medium having stored thereon processor-executable instructions to cause a processor in a vehicle to perform operations comprising:

receiving an intention message including a motion plan from a transmitting vehicle,

wherein the motion plan comprises a trajectory of the transmitting vehicle and one or more vehicle descriptors associated with the transmitting vehicle, and

wherein the one or more vehicle descriptors comprise a vehicle physical capability that comprises at least one of a turning radius, a vehicle top speed, and a vehicle maximum acceleration;

determining an expected region of interest for the vehicle based at least in part on the motion plan;

selecting a first detection algorithm for detecting a sensor perceptible attribute of the transmitting vehicle based on receiving the motion plan of the transmitting vehicle,

wherein the first detection algorithm is associated with a first confidence threshold for reporting detection of the transmitting vehicle in the expected region of interest,

wherein the first confidence threshold is lower than a second confidence threshold associated with a second detection algorithm;

receiving sensor data from one or more sensors disposed in or on the vehicle;

applying the selected first detection algorithm to a limited subset of received sensor data from the expected region of interest;

setting a future behavior prediction for the transmitting vehicle based at least in part on a vehicle behavior model for the transmitting vehicle limited by the vehicle physical capability and the expected region of interest, wherein setting the future behavior prediction for the transmitting vehicle is based on the application of the selected first detection algorithm; and

controlling the vehicle based at least in part on the motion plan and the future behavior prediction.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 23, 2023
From: CHAVES, STEPHEN MARC; MELLINGER, DANIEL WARREN, III; MARTIN, PAUL DANIEL; SHOMIN, MICHAEL JOSHUA
To: QUALCOMM INCORPORATED
Reel/Frame 064043/0019 →
Continuity (3)
Continuation 16439956 · Jun 13, 2019
Provisional Application 62782573 · Dec 20, 2018
Related Publication 20230334983A1 · Oct 19, 2023
References Cited (72)
US 6720920B2 · Breed et al. · 2004 [cited by applicant]
US 6861957B2 · Koike · 2005 [cited by applicant]
US 7889065B2 · Smith et al. · 2011 [cited by applicant]
US 8520695B1 · Rubin · 2013 [cited by examiner]
US 8532862B2 · Neff · 2013 [cited by applicant]
US 8700251B1 · Zhu · 2014 [cited by examiner]
US 9600768B1 · Ferguson · 2017 [cited by examiner]
US 9864064B2 · Ishigami et al. · 2018 [cited by applicant]
US 10037696B2 · Laur et al. · 2018 [cited by applicant]
US 10098014B1 · Shimizu · 2018 [cited by examiner]
US 10440668B1 · Wu · 2019 [cited by examiner]
US 11054834B2 · Russell · 2021 [cited by examiner]
US 11906625B2 · Rangesh · 2024 [cited by examiner]
US 20070162550A1 · Rosenberg · 2007 [cited by examiner]
US 20100256852A1 · Mudalige · 2010 [cited by examiner]
US 20130278769A1 · Nix et al. · 2013 [cited by applicant]
US 20130279393A1 · Rubin et al. · 2013 [cited by applicant]
US 20150161894A1 · Duncan · 2015 [cited by examiner]
US 20160358477A1 · Ansari · 2016 [cited by applicant]
US 20170003136A1 · Barnard et al. · 2017 [cited by applicant]
US 20170031361A1 · Olson · 2017 [cited by examiner]
US 20180056998A1 · Benosman et al. · 2018 [cited by applicant]
US 20180067495A1 · Oder · 2018 [cited by examiner]
US 20180148051A1 · Lujan · 2018 [cited by examiner]
US 20180208195A1 · Hutcheson et al. · 2018 [cited by applicant]
US 20180257645A1 · Buburuzan · 2018 [cited by examiner]
US 20180319403A1 · Buburuzan · 2018 [cited by examiner]
US 20190005812A1 · Matus et al. · 2019 [cited by applicant]
US 20190035275A1 · Nishi · 2019 [cited by applicant]
US 20190061712A1 · Melik-Barkhudarov · 2019 [cited by examiner]
US 20190236955A1 · Hu · 2019 [cited by examiner]
US 20190266498A1 · Maluf et al. · 2019 [cited by applicant]
US 20190339082A1 · Doig · 2019 [cited by examiner]
US 20200003861A1 · Eriksson · 2020 [cited by examiner]
US 20200097841A1 · Petousis et al. · 2020 [cited by applicant]
US 20200202706A1 · Chaves et al. · 2020 [cited by applicant]
US 20210067926A1 · Hwang · 2021 [cited by examiner]
CN 101526615A · 2009 [cited by applicant]
CN 102963355A · 2013 [cited by applicant]
CN 103646298A · 2014 [cited by applicant]
CN 104167097B · 2016 [cited by applicant]
CN 106128137A · 2016 [cited by applicant]
CN 106428009A · 2017 [cited by applicant]
CN 106485949A · 2017 [cited by applicant]
CN 106781551A · 2017 [cited by applicant]
CN 107146408A · 2017 [cited by applicant]
CN 107155407A · 2017 [cited by applicant]
CN 107561969A · 2018 [cited by applicant]
CN 107284452B · 2018 [cited by applicant]
CN 108027243A · 2018 [cited by applicant]
CN 105761546B · 2018 [cited by applicant]
CN 108349496A · 2018 [cited by applicant]
CN 108564234A · 2018 [cited by applicant]
CN 109017782A · 2018 [cited by applicant]
CN 109035862A · 2018 [cited by applicant]
CN 109863500A · 2019 [cited by applicant]
CN 109920246A · 2019 [cited by applicant]
CN 113228129B · 2023 [cited by applicant]
DE 102009035072A1 · 2011 [cited by applicant]
DE 102015220481A1 · 2017 [cited by applicant]
EP 1459977A1 · 2004 [cited by applicant]
EP 3021305A2 · 2016 [cited by applicant]
EP 3121762A1 · 2017 [cited by applicant]
EP 3364393A1 · 2018 [cited by applicant]
JP 2003228800A · 2003 [cited by applicant]
JP 2007094698A · 2007 [cited by applicant]
JP 2010019588A · 2010 [cited by applicant]
JP 2012112691A · 2012 [cited by applicant]
Alonso J., et al., “Autonomous Vehicle Control Systems for Safe Crossroads,” 2011, 16 pages. [cited by applicant]
International Preliminary Report on Patentability—PCT/US2019/058460, The International Bureau of WIPO—Geneva, Switzerland, Jul. 1, 2021. 13 pages. [cited by applicant]
International Search Report and Written Opinion—PCT/US2019/058460—ISA/EPO—Jun. 18, 2020. 21 pages. [cited by applicant]
Partial International Search Report—PCT/US2019/058460—ISA/EPO—Feb. 14, 2020. 17 pages. [cited by applicant]