*)
`
`Notice:
`
`1)
`y
`Subject to any disclaimer, the term of this
`patent is extended or adjusted under 35
`U.S.C. 154(b) by 0 days.
`
`(21)
`
`Appl. No.:
`
`17/719,541
`
`(22)
`
`Filed:
`
`Apr. 13, 2022
`
`Prior Publication Data
`
`(65)
`
`(63)
`
`(51)
`
`Related U.S. Application Data
`
`Continuation of application No. 17/374,656, filed on
`Jul. 13, 2021, which is a continuation of application
`(Continued)
`
`Int. Cl.
`B6OW 50/12
`GOSD 1/00
`
`(52)
`
`USS. Cl.
`
`(2012.01)
`(2006.01)
`(Continued)
`
`CPC wee B6OW 50/12 (2013.01); BOOW 40/06
`(2013.01); B6OW 40/08 (2013.01); BoOW
`40/10 (2013.01);
`
`Model S Software Update 6.2.
`(Continued)
`
`Primary Examiner — Todd Melton
`(74) Attorney, Agent, or Firm — Kinney & Lange, P.A.
`
`A computer-implemented method, system, and/or computer
`program product controls a driving mode ofa self-driving
`vehicle (SDV). One or more processors compare a control
`processor competence level of an on-board SDV control
`processor in controlling the SDV to a human driver com-
`petence level of a human driver in controlling the SDV while
`the SDV encounters a current roadway condition which is a
`result of current weather conditions of the roadway on which
`the SDV is currently traveling. One or more processors then
`selectively assign control of the SDV to the SDV control
`processoror to the human driver while the SDV encounters
`the current roadway condition based on which ofthe control
`processor competence level and the human driver compe-
`tence level is relatively higher to one another.
`
`US011597402B2
`
`a2) United States Patent
`US 11,597,402 B2
`(0) Patent No.:
`Mar.7, 2023
`(45) Date of Patent:
`Gordonet al.
`
`(54) CONTROLLING DRIVING MODES OF
`SELF-DRIVING VEHICLES
`
`(58) Field of Classification Search
`None
`See application file for complete search history.
`
`(71) Applicant: Slingshot IOT LLC, Baltimore, MD
`(US)
`
`(56)
`
`(72)
`
`Inventors:
`
`Michael S. Gordon, Yorktown Heights,
`NY (US); James R. Kozloski, New
`Fairfield, CT (US); Ashish Kundu,
`New York, NY (US); Peter K. Malkin,
`Ardsley, NY (US); Clifford A.
`Pickover, Yorktown Heights, NY (US)
`
`(73) Assignee: Slingshot IOT LLC, Baltimore, MD
`(US)
`
`CA
`CA
`
`References Cited
`U.S. PATENT DOCUMENTS
`
`4,665,395 A
`4,908,988 A
`
`5/1987 Van
`3/1990 Yamamuraet al.
`(Continued)
`
`FOREIGN PATENT DOCUMENTS
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`2392578 Al
`2392652 Al
`
`$/2001
`$/2001
`
`(Continued)
`
`OTHER PUBLICATIONS
`
`US 2022/0242431 Al
`
`Aug. 4, 2022
`
`(57)
`
`ABSTRACT
`
`(Continued)
`
`24 Claims, 8 Drawing Sheets
`
`
`
`DETERMINE A CONTROL PROCESSOR COMPETENCE LEVEL
`{CPCL} OF AN ON-BOARD SDY CONTROL PROCESSOR OF THE SDV
`
`
`UNDER THE CURRENT OPERATIONAL ANOMALY OF THE SDV
`
`
`RECEIVE A DRIVER PROFILE THAT INCLUDES A HUMAN DRIVER
` 508
`COMPETENCE LEVEL (HOCL) OF THE HUMANDRIVER OF THE SDV
`
`
`UNDER THE CURRENT OPERATIONAL ANOMALY OF THE SDV
`
`
`--510
`‘COMPARE THE CONTROL PROCESSOR COMPETENCELEVEL]
`(CPCL) TO A HUMAN DRIVER COMPETENCE LEVEL (HDCL}
`
`
`
`
`
`
`
`ASSIGN CONTROL OF THE SDV TO
`AN ON-BOARD SDV CONTROL
`
`PROCESSOR ON THE SDV WHILE
`
`THE SDVIS UNDER THE CURRENT
`OPERATIONAL ANOMALY
`
`
`ASSIGN CONTROLOF THE
`SDY 0 THE HUMAN
`
`
`DRIVER OF THE SDV WHILE
`
`THE SDV 1S UNDER THE
`CURRENT OPERATIONAL ANOMALY
`
`
`BIG
`
`IPR2025-00943
`Tesla EX1001 Page1
`
`IPR2025-00943
`Tesla EX1001 Page 1
`
`

`

`US 11,597,402 B2
`
`Page 2
`
`Related U.S. Application Data
`
`No. 16/997,202,filed on Aug. 19, 2020, now Pat. No.
`11,091,171, which is a continuation of application
`No. 16/899,407, filed on Jun. 11, 2020, now aban-
`doned, and a continuation of application No. 15/955,
`874, filed on Apr. 18, 2018, now Pat. No. 10,717,446,
`which is a continuation of application No. 15/341,
`225, filed on Nov. 2, 2016, now Pat. No. 10,029,701,
`which is a continuation of application No. 14/865,
`393, filed on Sep. 25, 2015, now Pat. No. 9,566,986.
`
`(51)
`
`(2006.01)
`(2012.01)
`(2012.01)
`(2012.01)
`(2006.01)
`(2006.01)
`
`Int. CL
`Boow 50/00
`BooW 40/06
`Boow 40/08
`Boow 40/10
`B62D 1/28
`B62D 6/00
`(52) U.S. Cl.
`CPC....... BooW 50/0098 (2013.01); GO5D 1/0061
`(2013.01); B6OW 2040/0809 (2013.01); BOOW
`2050/0095 (2013.01); BOOW 2510/30
`(2013.01); B6OW 2540/22 (2013.01); B6OW
`2552/00 (2020.02); B6OW 2555/20 (2020.02);
`BOoOW 2756/10 (2020.02); B62D 1/286
`(2013.01); B62D 6/007 (2013.01); GOS5D
`2201/0213 (2013.01)
`
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`IPR2025-00943
`Tesla EX1001 Page 2
`
`IPR2025-00943
`Tesla EX1001 Page 2
`
`

`

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`
`Mar.7, 2023
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`U.S. Patent
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`Mar.7, 2023
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`Sheet 5 of8
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`US 11,597,402 B2
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`U.S. Patent
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`U.S. Patent
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`Mar.7, 2023
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`US 11,597,402 B2
`
`1
`CONTROLLING DRIVING MODES OF
`SELF-DRIVING VEHICLES
`
`CROSS-REFERENCE TO RELATED
`APPLICATIONS
`
`This application is a continuation of U.S. application Ser.
`No. 17/374,656 filed Jul. 13, 2021, which in turn claims the
`benefit of continuation of U.S. patent application Ser. No.
`16/997,202, filed Aug. 19, 2020, now U.S. Pat. No. 11,091,
`171 on Aug. 17, 2021, which in turn claims the benefit of
`continuation of U.S. application Ser. No. 16/899,407 filed
`Jun. 11, 2020, which in turn claims the benefit of which is
`a continuation of U.S. application Ser. No. 15/955,874 filed
`Apr. 18, 2018, now U.S. Pat. No. 10,717,446 on Jul. 21,
`2020, which in turn claims the benefit of continuation Ser.
`No. 15/341,225 filed Nov. 2, 2016, now U.S. Pat. No.
`10,029,701 on Jul. 24, 2018, which in turn claimsthe benefit
`of continuation Ser. No. 14/865,393, Filed Sep. 25, 2015,
`now USS. Pat. No. 9,566,986 on Feb. 14, 2017, are hereby
`incorporated by reference in their entirety.
`
`BACKGROUND
`
`The present disclosure relates to the field of vehicles, and
`specifically to the field of self-driving vehicles. Still more
`specifically,
`the present disclosure relates to the field of
`controlling whether self-driving vehicles operate in autono-
`mous mode or manual mode.
`Self-driving vehicles (SDVs) are vehicles that are able to
`autonomously drive themselves through private and/or pub-
`lic spaces. Using a system of sensors that detect the location
`and/or surroundings of the SDV, logic within or associated
`with the SDV controls the speed, propulsion, braking, and
`steering of the SDV based on the sensor-detected location
`and surroundings of the SDV.
`
`SUMMARY
`
`A computer-implemented method, system, and/or com-
`puter program product controls a driving mode ofa self-
`driving vehicle (SDV). One or more processors determine a
`control processor competencelevel of a self-driving vehicle
`(SDV) control processor. The control processor competence
`level describes a competence level of the SDV control
`processorin controlling the SDV while the SDV experiences
`the current operational anomaly. One or more processors
`receive a driverprofile of the human driver of the SDV. The
`driver profile describes a humandriver competencelevel of
`the human driver in controlling the SDV while the SDV
`experiences the current operational anomaly. One or more
`processors compare the control processor competencelevel
`to the human driver competence level. One or more proces-
`sors then selectively assign control of the SDV to the SDV
`control processor or to the human driver while the SDV
`experiences the current operational anomaly based on which
`of the control processor competence level and the human
`driver competencelevel is relatively higher to one another.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`FIG. 1 depicts an exemplary system and network in which
`the present disclosure may be implemented;
`FIG. 2 illustrates an exemplary self-driving vehicle
`(SDV) traveling on a roadway in accordance with one or
`more embodiments of the present invention;
`
`25
`
`30
`
`40
`
`45
`
`55
`
`60
`
`2
`FIG.3 depicts additional detail of control hardware within
`an SDV;
`FIG. 4 depicts communication linkages among SDVs,
`roadway sensor(s), a roadway monitoring system, and/or a
`coordinating server;
`FIG. 5 is a high-level flow chart of one or more steps
`performed by one or more processors to control a driving
`mode of an SDV in accordance with one or more embodi-
`
`ments of the present invention;
`FIG. 6 depicts a cloud computing node according to an
`embodimentof the present disclosure;
`FIG. 7 depicts a cloud computing environmentaccording
`to an embodimentof the present disclosure; and
`FIG. 8 depicts abstraction model layers according to an
`embodimentof the present disclosure.
`
`DETAILED DESCRIPTION
`
`The present invention may be a system, a method, and/or
`a computer program product. The computer program prod-
`uct may include a computer readable storage medium (or
`media) having computer readable program instructions
`thereon for causing a processor to carry out aspects of the
`present invention.
`The computer readable storage medium can be a tangible
`device that can retain and store instructions for use by an
`instruction execution device. The computer readable storage
`medium may be, for example, but is not limited to, an
`electronic storage device, a magnetic storage device, an
`optical storage device, an electromagnetic storage device, a
`semiconductor storage device, or any suitable combination
`of the foregoing. A non-exhaustive list of more specific
`examples of the computer readable storage medium includes
`the following: a portable computer diskette, a hard disk, a
`random access memory (RAM), a read-only memory
`(ROM), an erasable programmable read-only memory
`(EPROMor Flash memory), a static random access memory
`(SRAM), a portable compact disc read-only memory (CD-
`ROM), a digital versatile disk (DVD), a memory stick, a
`floppy disk, a mechanically encoded device such as punch-
`cards or raised structures in a groove having instructions
`recorded thereon, and any suitable combination of the fore-
`going. A computer readable storage medium,as used herein,
`is not to be construed as being transitory signals per se, such
`as radio wavesor other freely propagating electromagnetic
`waves, electromagnetic waves propagating through a wave-
`guide or other transmission media(e.g., light pulses passing
`through a fiber-optic cable), or electrical signals transmitted
`through a wire.
`Computer readable program instructions described herein
`can be downloaded to respective computing/processing
`devices from a computer readable storage medium orto an
`external computer or external storage device via a network,
`for example, the Internet, a local area network, a wide area
`network and/or a wireless network. The network may com-
`prise copper transmission cables, optical transmissionfibers,
`wireless transmission, routers, firewalls, switches, gateway
`computers and/or edge servers. A network adapter card or
`network interface in each computing/processing device
`receives computer readable program instructions from the
`network and forwards the computer readable program
`instructions for storage in a computer readable storage
`medium within the respective computing/processing device.
`Computer readable program instructions for carrying out
`operations of the present
`invention may be assembler
`instructions, instruction-set-architecture (ISA) instructions,
`machine instructions, machine dependent
`instructions,
`
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`3
`state-setting data, or
`firmware instructions,
`microcode,
`either source code or object code written in any combination
`of one or more programming languages, including an object
`oriented programming language such as Java, Smalltalk,
`C++ or the like, and conventional procedural programming
`languages, such as the “C” programming languageor similar
`programming languages.