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US 12,742,660 B1Granted
Driver assist apparatus, method and system utilizing patrol and roadway environmental properties
OwnerSteve Dabellinventor
Life of this patent
Estimating the term…
Abstract
It is an object of the present invention to provide a predictive traffic law enforcement profiler apparatus and method which incorporates a means to determine current location, time, velocity and also incorporates a means to utilize a database derived from historic traffic law enforcement records, crowd sourced records and historical traffic data and also incorporates a predictive processing means to provide historic traffic law enforcement records and estimates of enforced speed limits and enforcement profiles, patrol locations and schedules of traffic law enforcement to a driver.
Claims18
A system for controlling a plurality of vehicles traveling within one or more regions used for one or more of:
- increasing travel efficiencies of said plurality of vehicles, decreasing a probability of said plurality of vehicles receiving traffic law enforcement citations, and decreasing a probability of said plurality of vehicles being involved in an accident, said system comprising:
- a plurality of clients, one or more servers, and one or more networks;
- wherein said one or more networks enables said plurality of clients and said one or more servers to communicate;
- wherein said one or more servers comprise:
- one or more databases configured to store one or more roadway property records specific to at least said one or more regions, wherein said roadway property records comprise one or more traffic law enforcement properties and one or more road environmental condition properties;
- wherein said traffic law enforcement properties comprise one or more of:
- predicted, historical and/or real-time patrol locations and/or patrol schedules;
- wherein said road environmental condition properties comprise one or more conditions, values, types, speeds, directions of movement, and locations absolute and/or relative to a vehicle associated with one or more of:
- signage, road surfaces, road hazards, historical accident reports, real-time accident reports, weather, school zones, construction zones, traffic flow, and surrounding vehicles;
- one or more server predictive processors configured to:
- receive one or more client location-based measurements from said plurality of clients through said one or more networks, and one or more client constraints from said plurality of clients through said one or more networks;
- responsive to receiving said one or more client location-based measurements, determine a presence of a specific vehicle within a particular region of said one or more regions based on said one or more client location-based measurements received;
- responsive to determining said presence of said specific vehicle within said particular region of said one or more regions, access said one or more roadway property records specific to at least said particular region of said one or more regions within said one or more databases;
- responsive to accessing said one or more roadway property records specific to at least said particular region of said one or more regions, process said one or more roadway property records using one or more algorithms, wherein said one or more algorithms comprise one or more of:
- filtering, artificial intelligence, machine learning, inferential statistics, data analytics, correlation, extrapolation, and statistical analysis;
- wherein said processing comprises one or more of:
- deriving one or more traffic law enforcement properties from issued citations, self-sourced enforcement encounters by said specific vehicle, and/or crowd-sourced enforcement encounters;
- and deriving one or more road environmental condition properties from self-sourced vehicle data and/or crowd-sourced data relating to signage, road hazards, accident reports, weather, construction zones, school zones, and surrounding vehicles;
- wherein said one or more traffic law enforcement properties and/or said one or more road environmental condition properties may be stored in said one or more databases and/or used transiently by said one or more server predictive processors for determining vehicle control outputs;
- responsive to processing said one or more roadway property records, transmit through said one or more networks one or more select portions of said roadway property records based on meeting one or more predefined client criteria;
- wherein said predefined client criteria pertain to said one or more client constraints;
- wherein said one or more client constraints comprise at least one of:
- increasing travel efficiencies of said specific vehicle, decreasing a probability of said specific vehicle receiving traffic law enforcement citations, and decreasing a probability of said specific vehicle being involved in an accident;
- wherein each client of said plurality of clients is for a specific vehicle of said plurality of vehicles, wherein each said client comprises:
- one or more location determining systems configured to take one or more client location-based measurements of said specific vehicle and transmit said one or more client location-based measurements;
- one or more client predictive processors configured to receive said one or more client location-based measurements and transmit said one or more client location-based measurements to said one or more servers through said one or more networks, and responsive to receiving said one or more select portions of said roadway property records from said one or more server predictive processors, transmit said one or more select portions of said roadway property records;
- one or more vehicle controllers configured to receive said one or more select portions of said roadway property records and determine one or more vehicle control outputs based at least on said one or more select portions of said roadway property records and said one or more client constraints;
- wherein said one or more vehicle control outputs comprise one or more of:
- speed commands, direction of movement commands, and navigational commands, and wherein said navigational commands comprise route planning for said specific vehicle within said particular region of said one or more regions;
- and one or more user control interfaces configured to receive one or more configuration inputs from one or more human users and/or machine users, wherein said one or more configuration inputs comprise one or more of:
- said one or more client constraints and one or more vehicle control configurations relating to said processing of said roadway property records, and responsive to receiving said one or more configuration inputs, transmit said one or more configuration inputs to said one or more server predictive processors and said one or more vehicle controllers through said one or more networks.
28 more elements
A method for controlling a plurality of vehicles traveling within one or more regions, said method comprising:
- receiving, by one or more server processors through one or more networks, one or more location-based measurements from a plurality of client devices associated with a plurality of vehicles;
- receiving, by said one or more server processors through said one or more networks, one or more client constraints associated with at least one vehicle of said plurality of vehicles;
- determining, by said one or more server processors, a presence of said at least one vehicle within a particular region of said one or more regions based on said received location-based measurements;
- accessing, by said one or more server processors, one or more roadway property records associated with said particular region from one or more databases, wherein said roadway property records comprise one or more traffic law enforcement properties and one or more road environmental condition properties;
- processing, by said one or more server processors, said one or more roadway property records using one or more algorithms comprising one or more of filtering, artificial intelligence, machine learning, inferential statistics, data analytics, correlation, extrapolation, and statistical analysis;
- wherein said processing comprises one or more of:
- deriving one or more traffic law enforcement properties from issued citations, self-sourced enforcement encounters by vehicles of said plurality of vehicles, and/or crowd-sourced traffic law enforcement encounters;
- and
- deriving one or more road environmental condition properties from self-sourced vehicle data and/or crowd-sourced data relating to signage, road surfaces, road hazards, historical accident reports, real-time accident reports, weather, school zones, construction zones, traffic flow, and surrounding vehicles;
- selecting, by said one or more server processors, one or more portions of said roadway property records based on one or more predefined client criteria, wherein said predefined client criteria pertain to said one or more client constraints;
- transmitting, by said one or more server processors through said one or more networks, said selected portions of said roadway property records to at least one client device associated with said at least one vehicle;
- receiving, by one or more vehicle controllers associated with said at least one vehicle, said selected portions of said roadway property records;
- and controlling operation of said at least one vehicle based at least on said selected portions of said roadway property records and said one or more client constraints, wherein said one or more client constraints comprise at least one of:
- increasing travel efficiency of said at least one vehicle, decreasing a probability of said at least one vehicle receiving a traffic law enforcement citation, and decreasing a probability of said at least one vehicle being involved in an accident.
11 more elements
A system for a plurality of vehicles traveling within one or more regions used for one or more of increasing travel efficiencies of said plurality of vehicles, decreasing a probability of said plurality of vehicles receiving traffic law enforcement citations, and decreasing a probability of said plurality of vehicles being involved in accidents, said system comprising:
- a plurality of apparatuses, wherein each apparatus of said plurality of apparatuses is for a specific vehicle of said plurality of vehicles, wherein each apparatus of said plurality of apparatuses comprises:
- one or more location determining systems configured to:
- take one or more location-based measurements of said specific vehicle of said plurality of vehicles, responsive to taking said one or more location-based measurements, transmit said one or more location-based measurements;
- one or more databases configured to store one or more records of roadway properties specific to at least said one or more regions, wherein said roadway properties specific to at least said one or more regions comprise one or more traffic law enforcement properties and road environmental condition properties, wherein said traffic law enforcement properties comprise one or more historical and/or real-time patrol locations and/or schedules, and wherein said road environmental condition properties comprise one or more conditions, values, types, speeds, direction of movements, and locations absolute and/or relative to said vehicle associated with one or more signage, road surfaces, road hazards, historical accident reports, real time accident reports, weather, school zones, construction zones, and surrounding vehicles;
- one or more predictive processors configured to:
- receive said one or more location-based measurements from said one or more location determining systems;
- responsive to receiving said one or more location-based measurements, determine a presence of said vehicle within a particular region of said one or more regions based on said one or more location-based measurements received, responsive to determining said presence of said vehicle within said particular region of said one or more regions, access said one or more records of roadway properties specific to at least said particular region of said one or more regions within said one or more databases, responsive to accessing said one or more records of roadway properties specific to at least said particular region of said one or more regions, process said one or more records of roadway properties specific to at least said particular region of said one or more regions using one or more algorithms, wherein said one or more algorithms comprise one or more of filtering, artificial intelligence, machine learning, inferential statistics, data analytics, correlation, extrapolation, and statistical analysis, and wherein said processing said one or more records of roadway properties specific to at least said region using said one or more algorithms comprises one or more of:
- deriving one or more of said traffic law enforcement properties from one or more issued citations and self-sourced by said specific vehicle of said plurality of vehicles and/or crowd-sourced traffic law enforcement encounters, and deriving one or more of said road environmental condition properties from one or more self-sourced by said specific vehicle of said plurality of vehicles and/or crowd-sourced signage, road surfaces, road conditions, road hazards, historical accident reports, real time accident reports, weather, school zones, construction zones;
- responsive to processing said one or more records of roadway properties specific to at least said particular region of said one or more regions, transmit one or more select portions of said one or more records of roadway properties based on meeting one or more predefined criteria, wherein said one or more predefined criteria pertain to one or more constraints identified by one or more human users, machine users, and default settings, and wherein said one or more constraints comprise one or more of said increasing said travel efficiencies of said specific vehicle of said plurality of vehicles, said decreasing said probability of said specific vehicle of said plurality of vehicles receiving said traffic law enforcement citations, and said decreasing said probability of said specific vehicle of said plurality of vehicles being involved in said accidents;
- one or more vehicle controllers for said specific vehicle of said plurality of vehicles configured to:
- receive said one or more select portions of said one or more records of roadway properties transmitted from said one or more predictive processors, and determine one or more vehicle control outputs based on said one or more select portions of said one or more records of roadway properties, wherein said one or more vehicle control outputs are determined based at least on said one or more constraints, and control said specific vehicle of said plurality of vehicles according to said one or more vehicle control outputs, wherein said one or more vehicle control outputs comprise one or more speed commands, direction of movement commands, and navigational commands, and wherein said navigational commands at least comprise route planning for said specific vehicle of said plurality of vehicles in said particular region of said one or more regions;
- and one or more user interfaces configured to:
- receive one or more inputs by one or more of said human users and said machine users, wherein said one or more inputs comprise one or more of said one or more constraints and one or more control commands relating to said processing of said one or more records of roadway properties specific to at least said particular region of said one or more regions using said one or more algorithms by said one or more predictive processors, and responsive to receiving said one or more inputs, transmit said one or more inputs to said one or more predictive processors and said one or more vehicle controllers.
10 more elements
Dependencies are inferred from the claim text.