# US 11,299,167 B2 · System and method for improving real-time estimates of visitor volume to places > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,299,167 B2 - Document ID: US11299167B2 - Status: Granted - Kind: B2 - Application number: 17/016,068 - Filed: 2020-09-09 - Published: 2022-03-10 - Granted: 2022-04-12 - Earliest claimed: 2020-09-09 - Applicants: Arrivalist Co. - Inventors: Cree Lawson - Web page: https://patentgrep.com/patent/US11299167B2 ## CPC - B60W 40/09: Driving style or behaviour - G08G 1/146: {where the parking area is a limited parking space, e.g. parking garage, restricted space} - G06Q 10/063: Operations research, analysis or management - G06Q 30/02: Marketing; Price estimation or determination; Fundraising - G06Q 50/26: Government or public services (business processes related to the transportation industry G06Q50/40) - G06Q 50/40: Business processes related to the transportation industry (shipping G06Q10/083) - G06V 40/20: Movements or behaviour, e.g. gesture recognition (recognition of facial expressions G06V40/16) - G08G 1/0108: {based on the source of data} - G08G 1/0125: {Traffic data processing} - G08G 1/0133: {for classifying traffic situation} - G08G 1/065: by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count - 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 - G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93}) - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract The present invention is a system and method for improving the accuracy with which human behavioral insights regarding visitor volume to places can be predicted. The process aligns at least two different data sets and normalizes the information by removing statistical bias. In a particular implementation motor vehicle data is collected from a known subset of road-borne vehicles and compared to data collected from unknown vehicles. The data is then increased or discounted to remove biases present in the known subset. The system analyzes the normalized data and returns a report including predictions to a human user. ## Claims ### Claim 1 A method for improving estimates of visitor volume to places, comprising: collecting a first data set in response to a first sensor triggering event comprising vehicle location data from one or more devices associated with occupants of a known motor vehicle, the first data set representing known characteristics of said occupants in a motor vehicle panel data set; collecting one or more second data sets in response to a second sensor triggering event comprising activating a geographically placed traffic sensor, the one or more second data sets representing characteristics of occupants of known and unknown motor vehicles; aggregating said first data set and at least one of the one or more second data sets into a data set comprising known and unknown vehicles; identifying a known, empaneled vehicle in the first data set and at least one of the one or more second data sets by comparing synchronized timestamps recorded with each first data set and one or more second data sets and labeling all other vehicles in said aggregated data set as not empaneled; calculating the presence of one or more statistical biases associated with said empaneled vehicles; normalizing the one or more statistical biases and producing a resulting data set comprising one or more results that apply to all vehicles within said aggregated data set; analyzing the resulting aggregated data set for human behavioral insights for all vehicles within said aggregated data set and providing a report upon said human behavioral insights to a user. ### Claim 2 (depends on 1) The method of claim 1, where correcting the one or more statistical biases is affected by applying a multiplier. ### Claim 3 (depends on 1) The method of claim 1, where the human behavioral insights reflect prospective human travel behavior. ### Claim 4 (depends on 1) The method of claim 1, where the one or more second data sets capture real-time vehicle data. ### Claim 5 (depends on 4) The method of claim 4, where the real-time vehicle data is captured using a digital device application, and/or a traffic data monitor, and/or a satellite monitor, or where the real-time vehicle data is captured using a combination of any of the digital device application, and/or the traffic data monitor, and/or the satellite monitor. ### Claim 6 (depends on 1) The method of claim 1, where the vehicle data is supplemented by third-party sources. ### Claim 7 A system for improving estimates of visitor volume to places, comprising: a server with a processor in communication with one or more digital devices; said server collecting a first data set in response to a first sensor triggering event comprising vehicle location data from one or more devices associated with occupants of a known motor vehicle, the first data set representing known characteristics of said occupants in a motor vehicle panel data set; said server collecting one or more second data sets in response to a second sensor triggering event comprising activating a geographically placed traffic sensor, the one or more second data sets representing characteristics of occupants of known and unknown motor vehicles; said server aggregating said first data set and at least one of the one or more second data sets into an aggregated data set comprising known and unknown motor vehicles; said server identifying a known, empaneled vehicle in the first data set and at least one of the one or more second data sets by comparing synchronized timestamps recorded with each first data set and one or more second data sets and labeling all other vehicles in said aggregated data set as not empaneled; said server operative to calculate the presence of one or more statistical biases associated with said empaneled vehicles; said server normalizing the one or more statistical biases and producing a resulting data set comprising one or more results that apply to all vehicles within said aggregated data set and storing said results within an electronic storage element within said server; said server analyzing the resulting data set for human behavioral insights for all vehicles within said aggregated data set and providing a report upon said human behavioral insights to a user. ### Claim 8 (depends on 7) The system of claim 7, where correcting the one or more statistical biases is affected by applying a multiplier. ### Claim 9 (depends on 7) The system of claim 7, where the human behavioral insights reflect prospective human travel behavior. ### Claim 10 (depends on 7) The system of claim 7, where the one or more motor vehicle second data sets capture real-time vehicle data. ### Claim 11 (depends on 10) The system of claim 10, where the real-time vehicle data is captured using a digital device application, and/or a traffic data monitor, and/or a satellite monitor, or where the real-time vehicle data is captured using a combination of any of the digital device application, and/or the traffic data monitor, and/or the satellite monitor. ### Claim 12 (depends on 7) The method of claim 7, where the vehicle data is supplemented by third-party sources.