# US 11,440,543 B2 · Prefix-based bounded-error estimation with intermittent observations > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,440,543 B2 - Document ID: US11440543B2 - Status: Granted - Kind: B2 - Application number: 16/256,270 - Filed: 2019-01-24 - Published: 2020-07-30 - Granted: 2022-09-13 - Earliest claimed: 2019-01-24 - Assignees: The Regents of Hte University of Michigan - Applicants: The Regents of the University of Michigan - Inventors: Necmiye Ozay; Sze Zheng Yong; Kwesi J. Rutledge - Web page: https://patentgrep.com/patent/US11440543B2 ## CPC - B60W 30/146: {Speed limiting} - B60W 50/02: Ensuring safety in case of control system failures, e.g. by diagnosing, circumventing or fixing failures - B60W 50/0225: {Failure correction strategy} - B60W 50/06: Improving the dynamic response of the control system, e.g. improving the speed of regulation or avoiding hunting or overshoot - G01S 17/89: for mapping or imaging - G01S 17/931: of land vehicles - B60W 2050/0052: {Filtering, filters} - B60W 2050/0215: {Sensor drifts or sensor failures} - B60W 2420/408: Radar; Laser, e.g. lidar - B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES ## Abstract A method of the disclosure implements a prefix-based estimator system. The method includes: receiving a plurality of vehicle states at a plurality of time points from at least one sensor coupled to a vehicle, wherein each of the plurality of vehicle states includes at least one parameter information and a discrete state; determining a most recent vehicle state of the plurality of vehicle states has at least one parameter information missing; identifying a prefix comprising a missing data pattern that matches a sequence of discrete states of a subset of time-ordered vehicle states including the most recent vehicle state, wherein the subset of time-ordered vehicle states correspond to the prefix; calculating an estimated updated vehicle state of the vehicle using an optimized prefix-based dynamic estimator based on the prefix and the subset of time ordered vehicle states; and providing the estimated updated vehicle state to a driving control system of the vehicle. ## Claims ### Claim 1 A method for data processing in a system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to implement a prefix-based estimator system, the method comprising: receiving a plurality of vehicle states at a plurality of time points from at least one sensor coupled to a vehicle, wherein each of the plurality of vehicle states includes at least one parameter, and a discrete state; determining a most recent vehicle state of the plurality of vehicle states has at least one missing parameter; identifying a prefix comprising a missing data pattern that matches a sequence of discrete states of a subset of time-ordered vehicle states including the most recent vehicle state, wherein the subset of time-ordered vehicle states correspond to the prefix; calculating an estimated updated vehicle state of the vehicle using an optimized prefix-based dynamic estimator based on the prefix and the subset of time-ordered vehicle states; and providing the estimated updated vehicle state to a driving control system of the vehicle. ### Claim 2 (depends on 1) The method of claim 1, wherein the at least one sensor includes a speedometer. ### Claim 3 (depends on 1) The method of claim 1, wherein the at least one sensor includes a LIDAR sensor. ### Claim 4 (depends on 1) The method of claim 1, wherein the at least one sensor includes a camera. ### Claim 5 (depends on 1) The method of claim 1, wherein the prefix belongs to a language comprising a plurality of prefixes. ### Claim 6 (depends on 5) The method of claim 5, wherein the optimized prefix-based dynamic estimator is optimized to provide a bounded error estimate for all prefixes in the language. ### Claim 7 (depends on 1) The method of claim 1, wherein the optimized prefix-based dynamic estimator is optimized using a Q-parametrization technique. ### Claim 8 (depends on 1) The method of claim 1, wherein the driving control system is an adaptive cruise control system. ### Claim 9 (depends on 1) The method of claim 1, wherein the missing data pattern comprises six discrete states. ### Claim 10 (depends on 1) The method of claim 1, wherein at least one of the time-ordered vehicle states preceding the most recent vehicle state has at least one missing parameter. ### Claim 11 A driving control system for a vehicle having at least one sensor, the driving control system comprising: at least one sensor coupled to a vehicle; and a controller in electrical communication with the at least one sensor, the controller being configured to execute a program stored in the controller to: (i) receive a plurality of vehicle states at a plurality of time points from the at least one sensor coupled to a vehicle, wherein each of the plurality of vehicle states includes at least one parameter, and a discrete state; (ii) determine a most recent vehicle state of the plurality of vehicle states has at least one missing parameter; (iii) identify a prefix comprising a missing data pattern that matches a sequence of discrete states of a subset of time-ordered vehicle states including the most recent vehicle state, wherein the subset of time-ordered vehicle states correspond to the prefix; (iv) calculate an estimated updated vehicle state of the vehicle using an optimized prefix-based dynamic estimator based on the prefix and the subset of time-ordered vehicle states; and (v) provide the estimated updated vehicle state to a driving control system of the vehicle. ### Claim 12 (depends on 11) The system of claim 11, wherein the at least one sensor includes a speedometer. ### Claim 13 (depends on 11) The system of claim 11, wherein the at least one sensor includes a LIDAR sensor. ### Claim 14 (depends on 11) The system of claim 11, wherein the at least one sensor includes a camera. ### Claim 15 (depends on 11) The system of claim 11, wherein the prefix belongs to a language comprising a plurality of prefixes. ### Claim 16 (depends on 15) The system of claim 15, wherein the optimized prefix-based dynamic estimator is optimized to provide a bounded error estimate for all prefixes in the language. ### Claim 17 (depends on 11) The system of claim 11, wherein the optimized prefix-based dynamic estimator is optimized using a Q-parametrization technique. ### Claim 18 (depends on 11) The system of claim 11, wherein the driving control system is an adaptive cruise control system. ### Claim 19 (depends on 11) The system of claim 11, wherein the missing data pattern comprises six discrete states. ### Claim 20 (depends on 11) The system of claim 11, wherein at least one of the time-ordered vehicle states preceding the most recent vehicle state has at least one missing parameter.