WO2011071826A1 - Analyse de données à partir de détecteurs de radar en réseau - Google Patents

Analyse de données à partir de détecteurs de radar en réseau Download PDF

Info

Publication number
WO2011071826A1
WO2011071826A1 PCT/US2010/059115 US2010059115W WO2011071826A1 WO 2011071826 A1 WO2011071826 A1 WO 2011071826A1 US 2010059115 W US2010059115 W US 2010059115W WO 2011071826 A1 WO2011071826 A1 WO 2011071826A1
Authority
WO
WIPO (PCT)
Prior art keywords
electromagnetic signal
signal detector
networked
prediction
data
Prior art date
Application number
PCT/US2010/059115
Other languages
English (en)
Inventor
Ronald Byron Kabler
Robert Ryan Brandys
Monica Marie Willemin
Original Assignee
Cobra Electronics Corporation
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Cobra Electronics Corporation filed Critical Cobra Electronics Corporation
Priority to RU2012123469/07A priority Critical patent/RU2515465C2/ru
Priority to CN2010800632586A priority patent/CN102753988A/zh
Priority to US13/514,232 priority patent/US8842004B2/en
Publication of WO2011071826A1 publication Critical patent/WO2011071826A1/fr
Priority to US13/840,496 priority patent/US9132773B2/en
Priority to US13/840,589 priority patent/US20130207829A1/en
Priority to US14/594,823 priority patent/US20150123834A1/en
Priority to US14/594,793 priority patent/US20150123833A1/en
Priority to US14/853,818 priority patent/US9848114B2/en
Priority to US15/809,850 priority patent/US10142535B2/en
Priority to US16/198,232 priority patent/US10298832B2/en

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/021—Auxiliary means for detecting or identifying radar signals or the like, e.g. radar jamming signals
    • G01S7/022—Road traffic radar detectors
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/4804—Auxiliary means for detecting or identifying lidar signals or the like, e.g. laser illuminators
    • G01S7/4806—Road traffic laser detectors

Definitions

  • This invention relates generally to the field of sensing equipment meant to alert motor vehicle operators and passengers to potential threats and safety risks such as law enforcement speed monitoring activity, the presence of emergency vehicles, traffic hazard warning devices, and other warnings or hazards.
  • This invention further relates to the field of threat level topography, in which sensing equipment alerts motor vehicle operators to levels of threats that are predicted for specific geographic locations.
  • This invention also relates generally to the "cloud computing" model of data exchange and storage and the “crowd-sourcing” method of data aggregation to enhance sensing equipment meant to alert motor vehicle operators and passengers to potential threats and safety risks.
  • radar detectors detect electromagnetic signals (such as microwave signals) or laser signals transmitted from radar or laser-type speed measurement equipment, such as police radar signals. Thus, radar detectors serve to provide advance warning to drivers who are being monitored by police radar.
  • radar detectors and their scanning algorithms are an imperfect technology. Electromagnetic waves are naturally vulnerable to reflection, bouncing, and scattering. These characteristics create variability and "noise" that a radar detector must detect and analyze before determining whether or not to alert a motor vehicle operator to a potential threat.
  • radar detectors do not actively predict areas for alert and, instead, they react to signals they receive from the environment which limits the amount of advanced warning that can be provided.
  • radar detector and electromagnetic signal detector will be used interchangeably to refer to any of a number of known speed detection units capable of detecting electromagnetic waves on the X- band, K-band or Ka-band.
  • radar detector and electromagnetic signal detector will also be used interchangeably to refer to speed detection units known as laser detectors, and could refer to any electromagnetic wave detector or light wave detector. Examples of known technology in this area include United States Patent Nos. 5,784,021 and 5,151,701.
  • U.S. Patent No. 6,118,403 to Lang generally describes a "Speed Trap Information System.”
  • the system uses radar detectors and a central server to collect information detected by radar detectors and provide the information as it was received to other radar detectors.
  • the '403 patent does not teach a system for analyzing the information for potential false readings.
  • the server receives "speed detecting equipment information and physical location information" from one radar detector and transmits the same information to "authorized users.”
  • the '403 patent does not teach performing a statistical analysis for determining whether or not the "speed detecting equipment information" represents a false reading nor does the patent teach any analysis to determine the likelihood that an alert should be predicted at a later time.
  • U.S. Patent No. 6,384,776 to Martin generally describes an "EM Signal Detection and Position Broadcasting System and Method.”
  • the '776 patent describes using a plurality of radar detectors that broadcast electromagnetic signal positions to other radar detectors. For example, when an electromagnetic signal is detected by one such radar detector, it broadcasts the electromagnetic signal position for any other radar detectors of the system to receive, regardless of whether any other radar detectors are with in the broadcast signal's range.
  • the '776 patent describes using a base station to pass along received electromagnetic signal positions, operating like the system described in the '403 patent. However, like the '403 patent, the '776 patent provides no disclosure of an analysis relating to the potential for false readings or predictability of a threat at a later time.
  • U.S. Patent No. 6,670,905 to Orr generally describes a "Radar Warning Receiver with Position and Velocity Sensitive Functions.”
  • the patent describes a radar detector which is associated with a local list of stationary locations and the capability to compare the radar detector's current location to the list of stationary locations indicating whether to reject a signal based upon proximity to a listed unrelated source.
  • the '905 patent does not disclose a centralized data repository or system that may aggregate and analyze information from one or more radar detectors. Therefore, like the '403 patent, the '905 patent does not provide a disclosure to overcome the problems of existing radar detectors.
  • the '905 patent does not teach an analysis to statistically filter out potential false readings and the '905 patent provides no analysis to predict the probability of a threat at a later time.
  • U.S. Patent No. 6,895,324 to Straub generally describes "Methods and Apparatus for Storing, Accessing, Generating and Using Information About Speed Limits and Speed Traps.”
  • the system of the '324 patent describes a device (which may be a radar or laser detector) that is used to identify speed traps based upon the opinion of an operator and transmit the location and a timestamp to a centralized location, and receives information describing the speed trap inputs from other drivers and speed limits in the area.
  • the '324 patent discloses that locations of signals received by a radar or laser detector may be stored as speed trap locations.
  • the '324 patent provides no disclosure of an analysis relating to the potential false readings or predictability of a threat at a later time.
  • Another drawback to the system of the '324 patent is that information is not analyzed and is based upon potentially false readings, opinions of device operators, and any false reports of speed traps whether intentional or unintentional.
  • a radar detector is fundamentally a device that turns data into actionable information. Data problems like these may be solved with database architectures and analysis algorithms. These analysis algorithms can sift through the noise and variance inherent in the sampling methodology to provide more precise actionable information. Some problems with radar detectors may be minimized by applying database analytical strategies.
  • networked radar detectors may communicate the radar detectors' data for a geographic location to a server that executes analysis algorithms to analyze the aggregated data and make predictions about law enforcement speed monitoring activities and potential safety risks at the geographic location.
  • the server provides alert management that dynamically adjusts alerts based on statistical probabilities and communicates the predictions to the networked radar detectors near the geographic location.
  • the networked radar detectors at the geographical location communicate threat levels and/or predictions of alert levels to motor vehicle operators and/or passengers as alerts. These alerts will help motor vehicle operators minimize the risks associated with law enforcement speed monitoring activity and reduce the probability that a radar detector user will fall into a police speed trap.
  • This present invention may also lead to larger zones of safe driving in compliance with local laws; a goal sought by all traffic regulating authorities.
  • Figure 1 is a block diagram depicting an embodiment of the system of the present invention.
  • Figure 2 is a flowchart depicting an embodiment of the process of the present invention.
  • Figure 3 is a depiction of a map illustration of an embodiment of the present invention.
  • alert levels, alert probabilities, predictions, and threat levels are synonymous and based upon an analysis of data by analysis algorithm 124 whether located in the electromagnetic signal detector, server or elsewhere, and alert level, detection alert level and initial alert level are based upon an electromagnetic signal detectors normal operation and detection of a signal, prior to an analysis by the analysis algorithm 124.
  • a block diagram depicts the system 100 according to an embodiment of the present invention.
  • the depicted system 100 includes a first radar detector 102 and a second radar detector 104.
  • the first radar detector 102 is used by a first motor vehicle 106 and the second radar detector 104 is used by a second motor vehicle 108.
  • Electromagnetic signal devices depicted in Fig. 1 include a mobile police radar unit 1 10, such as a police motorcycle equipped with a radar gun, a fixed police radar unit 112, such as a traffic light camera or fixed speed camera, and a motion-sensing door 1 14, such as an automatic front door for a restaurant that is situated towards the road on which the motor vehicles 106 ⁇ - 108 are travelling.
  • the radar detectors 102 - 104 may detect electromagnetic waves emitted from devices 1 10 - 114.
  • the system 100 may also include a first network interface 116, a second network interface 1 18, a server 120, a database 122, and an analysis algorithm 124.
  • the network interfaces 116 - 118 may enable the radar detectors 102 - 104 to communicate via a communication network, such as a cellular telephone network, a satellite network, a Wi-Fi, another wireless network, and/or the Internet.
  • the network interfaces 1 16 - 1 18 may be incorporated into a single device with radar detectors 102 - 104 or may be otherwise associated with radar detectors 102 - 104 through wired or wireless communication.
  • the system may operate on one or more public networks, private networks or combinations of public and private networks.
  • the system 100 may include any number of radar detectors 102 - 104, motor vehicles 106 - 108, electromagnetic emitting devices 110 - 114, network interfaces 116 - 118, servers 120, databases 122, and analysis algorithms 124 and should not be limited to the illustrative example provided in Fig. 1.
  • the first radar detector 102 accesses the first network interface 116 that promotes communication of data to and from the server 120.
  • the second radar detector 104 accesses the second network interface 1 18 that promotes communication of data to and from the server 120.
  • Each of the radar detectors 102 - 104 and the server 120 has the ability to initiate the process of sending or receiving data.
  • the data may relate to location, speed, and/or acceleration of the motor vehicles 106 - 108, law enforcement activity, detectable electromagnetic waves, traffic patterns and/or conditions, safety alerts, evacuation notices, and/or any other hazards or alerts, identified and flagged at the discretion of the server 120 and/or the users of the radar detectors 102 - 104.
  • law enforcement activity includes speed traps, speed cameras, red light cameras, and any law enforcement personnel and/or device enforcing traffic laws.
  • the data may also include driving patterns of vehicles 106 - 108 and/or specific driving patterns of individuals including patterns relating to the driver's typical reaction to specific alerts under specific circumstances. This allows server 120 to utilize database 122 to customize the alert levels it uploads for each user in order to adjust the alert levels to correlate to the advanced warning desired by the driver.
  • the first radar detector 102 detects the fixed police radar unit 112 and the motion sensing door 1 14 and communicates data representing these detections to the server 120.
  • the second radar detector 104 also detects the fixed police radar unit 1 12 and the motion sensing door 1 14 and communicates data representing these detections to the server 120.
  • radar detectors 102 - 104 and server 120 may communicate data in real-time or may communicate data based upon a schedule, a triggering event (such as reaching a data quantity threshold or a data storage size threshold), and/or a combination of a schedule and triggering event and remain within the scope and spirit of the invention.
  • radar detector 102 detects the fixed police radar unit 1 12 and the motion sensing door 114 and stores data representing these detections in internal memory, such as a buffer. Once a threshold quantity of data is surpassed in the buffer, radar detector 102 communicates data representing these detections to the server 120.
  • radar detector 104 may not receive any detection while travelling other roadways and stores data representing the absence of detections along the travelled path. At scheduled times radar detector 104 may communicate data representing the absence of detections to the server 120.
  • the server 120 Upon receipt of such data, the server 120 stores the data into physical or electronic memory in the database 122, which may be part of the server 120 or separate from the server 120.
  • the server administrators may also add other data to the database 122 (pertaining to law enforcement, safety, hazards, public notices, local knowledge, or driving in general) that are not measurable in the electromagnetic and laser spectrums of the radar detectors 102 - 104.
  • This additional data may be updated periodically by the server 120, automatically or through manual data entry. Some data changes frequently, like weather conditions and traffic conditions in local areas. Other data changes infrequently, such as "line segment" approximations of road maps and physical locations of school zones and/or law enforcement monitoring installations. These installations include but are not limited to red light and speed cameras.
  • the analyzed data includes the data from the radar detectors 102 - 104, other data added by administrators as indicated above, and data from other data suppliers, such as local knowledge and observed conditions.
  • the server 120 executes analysis algorithms 124 that periodically collect, sort, organize, and analyze the data.
  • the data is associated with database 122, but as one skilled in the art will recognize, analysis algorithms 124 may incorporate or otherwise analyze data from sources other than database 122 and remain within the scope and spirit of the invention.
  • These analysis algorithms 124 may include statistical or predictive calculations relating to the likelihood of future threats, hazards, alerts, law enforcement speed monitoring activity, or traffic conditions.
  • the storage capacity and processing capacity of the radar devices 102 - 104 may be significantly less than the storage capacity and the processing capacity of the database 122 and the server 120.
  • the database 122 and the server 120 may provide the capability to execute complex analysis algorithms 124 using significant quantities of aggregated data, including data that is not readily available to the radar detectors 102 - 104.
  • the output of each analysis algorithm 124 may be a calculated predictive threat level value or series of values that attempts to approximate and quantify the statistical likelihood of there being law enforcement monitoring activity and/or other safety risks in the geographic locations ahead of or in the immediate vicinity of the motor vehicles 106 - 108.
  • the analysis algorithm may tailor the resulting threat level value or values to an individual radar detector and/or driver based in part upon any considerations entered by the user and/or the user's stored driving patterns.
  • the analysis algorithm may also consider the current day, time, geographic location, heading, speed and acceleration of motor vehicles 106 - 108 to tailor a predicted alert value.
  • the "crowd-sourcing” method of data aggregation is based on analyzing data aggregated from multiple data sources, such as the radar detectors 102 - 104.
  • the "crowd- sourcing” method of data aggregation may produce more accurate results than analysis based on a single source of data, such as data from one of the radar detectors 102 - 104.
  • the analysis algorithm 124 analyzes data that represents detection of electromagnetic signals from the fixed police radar unit 1 12 by the radar detectors 102 - 104 and calculates a very high threat level, such as a 95% certainty, that the fixed police radar unit 1 12 is a law enforcement speed monitoring device. This prediction may be based on a single factor or a combination of factors. For this example, the same pattern of the electromagnetic waves repeatedly detected from the fixed police radar unit 112 by the radar detectors 102 - 104 on a frequent basis may be highly indicative of a law enforcement speed monitoring device. Additionally, the data may indicate that the source of these electromagnetic waves never moves and never ceases to emit electromagnetic waves because there is no data indicating an absence of detections from this location.
  • the regularity indicated by this data combined with geographic data that approximates the source of these electromagnetic waves at a busy traffic intersection may enable the analysis algorithm 124 to predict that the fixed police radar unit 1 12 is a speed- detecting traffic camera fixed at the intersection.
  • An additional factor used to calculate a threat level may be a confirmation of law enforcement speed monitoring activity input by a radar detector user.
  • the analysis algorithm 124 may modify the high probability of 95% certainty to 100% certainty if a specified number of radar detector users submit such confirmations.
  • the analysis algorithm 124 analyzes data that represents detection of electromagnetic signals from the motion-sensing door 114 by the radar detectors 102 - 104 and calculates a very low threat level, such as a 5% certainty, that the motion-sensing door 114 is a law enforcement device or other safety risk. This prediction may be based on a single factor or a combination of factors. For this example, the same pattern of the electromagnetic waves repeatedly detected from the motion-sensing door 114 by the radar detectors 102 - 104 on a frequent basis may not be highly indicative of a law enforcement device or other safety risk.
  • the data may indicate that although the source of these electromagnetic waves never moves, the emission of the electromagnetic waves and the absence of detections of the electromagnetic waves coincides with normal business hours for a restaurant.
  • the regularity indicated by this data combined with geographic data that approximates the source of these electromagnetic waves at a restaurant may enable the analysis algorithm to predict that the motion-sensing door 1 14 is not a law enforcement device or other safety risk.
  • a calculation of a threat level may be based on a motion-sensing door 1 14 and these exemplary factors, predictions may be based on other types of electromagnetic wave devices and other factors.
  • a prediction may consider signal analysis including the signal band analysis, signal frequency analysis, signal strength or intensity measurements, and/or any other signal analysis.
  • the received signal band may be compared to known signal regulations imposed by the FCC or other regulatory or licensing body. For instance, if the signal is in the X or K bands it may be a motion-sensing door, however, if the signal is in the Ka band it is unlikely to be a motion- sensing door.
  • the received signal band may be compared to previously identified signal bands stored in database 122. For instance, database 122 may have stored information associated with one geographic location regarding an X band signal that has a high probability of representing law enforcement activity and a Ka band signal that has a low probability of representing law enforcement activity.
  • the previously identified Ka band signals in the geographic location may factor in analysis algorithm 124 calculating a low probability of the received Ka band signal representing law enforcement activity.
  • a known Ka band microwave communication tower is an example of a non-law enforcement source that may be factored into analysis algorithm 124.
  • a third radar detector may derive the benefits from the system 100 based on detections made by the first radar detector 102 and the second radar detector 104 even when the third radar detector approaches the fixed police radar unit 1 12 for the very first time.
  • the third radar detector may provide an alert for the fixed police radar unit 1 12 without having previously observed and recorded any band emissions from that geographic location.
  • the alert provided by the third radar detector may be based upon periodically received data from server 120 pertaining to predicted probabilities and/or threat levels for potential threats in the local area. Therefore, the system 100 may provide benefits to radar detector users who have never travelled on a specific road segment before based on data from the multiple radar detectors 102 - 104 that have previously travelled on the specific road segment.
  • devices other than radar detectors which are capable of receiving predicted alert levels and/or threat levels in the local area from server 120 may also provide alerts based on data from the multiple radar detectors 102 - 104.
  • an alert level may be based upon the predicted probability, or threat level, that the detected signals represent a law enforcement monitoring device or other safety risk.
  • an alert level may be based upon the predicted probability, or threat level, that a law enforcement monitoring device or other safety risk is within a vicinity determined by radar detector 102, server 120, and/or defined by a user.
  • the alert level may be defined in any number of levels whereby each alert level is correlated to a range of probabilities. For example, if there are two alert levels, a 0-50% probability may represent no threat or a weak or irrelevant received signal or an ignore level while a 51-100% probability may represent a high threat level, and/or strong and/or highly relevant received signal.
  • alert levels may be defined by probability ranges 0-40% (no threat or an ignore level), 41-65% (minor threat), 66-85% (mid-level threat), and 86-100% (high threat).
  • five alert levels may be defined based upon ranges along a probability scale from -50 to 50, whereby probability ranges of -50 through -30 represent a no threat or an ignore level, probability ranges of -29 through -1 represent a minor threat, probability ranges of 1 through 30 represent a mid-level threat, probability ranges of 31 through 50 represent a high threat, and a probability of zero indicates no stored data for analysis.
  • the server 120 may calculate a multitude of probabilities and/or associated threat levels based on specific subsets of the data, i.e. for specific times of the day, days of the week, or months of the year.
  • the alert levels may also be based on data associated with specific geographic location boundaries. This process may create threat levels specific to grid regions bounded by latitude and longitude, or specific to "road segments" where detailed map data is available.
  • the server 120 may associate a weighted factor to various data to represent the strength and/or reliability of the data. For example, a diminishing weight factor may be associated with data based on the age of the data such that older data has a lower weight factor.
  • weight factors may be considered to determine a weight factor for any data, different weight factors may be applied for different calculations, weight factors may change over time for all data or specific data, and multiple weight factors may be associated with any data to effect the overall weight of the evidence during analysis and remain within the scope and spirit of the invention.
  • the user of radar detector 102 may program radar detector 102 to provide a minor alert level if there is a 50% predicted probability or threat level, while the user of radar detector 104 may program radar detector 104 to provide a no alert or an ignore level if there is a 50% predicted probability, or threat level.
  • the density of data stored for any geographic location may vary by region.
  • Database algorithms may automatically balance the data density for specific regions based on population density, data density, or other factors in each region.
  • the server 120 may adjust how frequently the analysis algorithms 124 are executed, and evaluate how an ever-enlarging set of data impacts the efficiency of the analysis algorithms 124.
  • the server 120 may instruct radar detectors 102 - 104 to occasionally override, mute, or alter any audible alerts that the server 120 identifies as highly likely to be false alerts, thereby suppressing false alerts in real-time or near-real time as needed.
  • the server 120 may instruct radar detectors 102 - 104 to provide the 95% threat level and/or a high alert to the motor vehicles 106 - 108 travelling on the road segment associated with the fixed police radar unit 112, but suppress the 5% threat level and/or an ignore for the motion-sensing door 114 located nearby the same road segment.
  • radar detectors 102 - 104 may provide an anticipatory alert based upon a high threat level in the anticipated travel segment.
  • radar detector 102 may provide an anticipatory alert prior to receiving a radar signal from fixed police radar unit 112 when motor vehicle 106 is traveling towards fixed police radar unit 112 with a determined 95% threat level. In addition, radar detector 102 may increase the given alert once a signal is received from fixed police radar unit 112.
  • the threat levels and/or probability that the analysis algorithm 124 may predict and that the server 120 may communicate to the radar detectors 102 - 104 are supplementary to the normal operation of the radar detectors 102 - 104.
  • the mobile police radar unit 1 10 may arrive on a police motorcycle at a geographic location where electromagnetic waves have never been detected by the radar detectors 102 - 104 previously.
  • the first radar detector 102 may still detect the mobile police radar unit 110 and provide an alert level and/or detection alert level to the operator of the first motor vehicle 106 even before the first network interface 116 communicates data representing this detection to the server 120.
  • Radar detector 102 also may or may not check its internal database for a probability or threat level before communicating an alert to the user.
  • the first radar detector 102 may determine that the detected signal is not stored in the internal memory of radar detector 102 and communicate an alert to the user based upon the internal analysis and settings of radar detector 102 for new or unrecognized signals.
  • a default setting of radar detector 102 would treat new or unrecognized signals as a threat and provide a default alert or a detection alert unless an internal analysis indicated that the signal is likely a false positive.
  • the radar detector 102 while the radar detector 102 is providing an initial alert to the user, it also may communicate the signal to server 120 for further analysis.
  • Server 120 may recognize that the signal is not in the database and communicate an anticipatory alert based upon the probability that the new electromagnetic wave is a police monitoring unit or other safety risk, or the server 120 may provide a default threat level until additional data is received and analyzed. Server 120 may send a different threat level than radar detector 102 determined, because server 120 may utilize more aggregated data and/or a more thorough analysis algorithm 124 than radar detector 102, which may lead to differences in probability determinations.
  • mobile police radar unit 110 may be turned off until the operator turns it on to specifically target a vehicle. This may prevent radar detector 102 from receiving the electromagnetic signal until the operator of mobile police radar unit 110 targets a car in the vicinity. However, once radar detector 102 receives the signal and uploads it to server 120, server 120 may provide an update to a memory component of radar detector 104 such that as radar detector 104 approaches the location of this threat, radar detector 104 provides an anticipatory alert prior to receiving the electromagnetic signal from mobile police radar unit 1 10.
  • the server 120 communicates the predictions based on specific geographic locations to each of the radar detectors 102 - 104 based on the corresponding geographic locations associated with each of radar detectors 102 - 104.
  • geographic locations associated with radar detector 102 may include the geographic area in which radar detector 102 is currently located, geographic areas which radar detector 102 is approaching or likely to approach, geographic areas designated by the user of radar detector 102, and/or suggested by a mapping or navigation component or device.
  • the size, shape, scope, calculation, and/or any defining parameters of an associated geographic area may vary and remain within the scope and spirit of the present invention.
  • Each of the radar detectors 102 - 104 periodically receives or downloads a subset of these predicted alert levels and/or threat levels from the server 120 that correspond to the current geographic locations associated with each of the radar detectors 102 - 104, including for example road segments currently traveled and road segments likely to be traveled in the future, and/or the particular time of day, day of week, or month of year.
  • Each of radar detectors 102 - 104 uses its location identifier and corresponding timestamp data to provide real-time predicted alert levels specific for the corresponding motor vehicles 106 - 108 using the radar detectors 102 - 104, on that day, at that time, at that geographic location, on that heading, at that speed and acceleration, under those weather and traffic conditions.
  • radar detectors 102 - 104 may be operably associated with a navigation component or device.
  • the geographic location associated with radar detectors 102 - 104 may include the route suggested by the navigation component or device.
  • the analysis algorithm 124 may calculate predicted threat levels based upon data associated with the roadway radar detector 102 is currently located on and any roadways likely to be travelled, and may consider the speed, conditions, direction of travel, history of driving, and/or any other factors associated with travel on the road segments.
  • Radar detector 102 may promote the navigation component or device to suggest alternate routes if an alert probability threshold is surpassed.
  • the radar detector user may respond to threat levels associated with a primary route suggested by the navigation application by requesting the navigation application to suggest an alternative route.
  • the location identifier may operate based on a relative location based system, a latitude/longitude system, another coordinate system, a map or road segment based system (such as one supplied by Google, Inc., Navteq or similar companies), a cellular or Wi-Fi triangulation system, any other system for identifying a location and/or any combination of location systems.
  • radar detectors 102 - 104 use a Global Positioning System (GPS) receiver as the location identifier.
  • GPS Global Positioning System
  • radar detectors 102 - 104 use a device determining the current map segment position (or proximity to the nearest map segment) as the location identifier.
  • a map segment is a representation of a physical road segment.
  • the server 120 may provide the threat levels for a geographic area containing the fixed police radar unit 1 12 and a second geographic area containing the motion- sensing door 1 14 to the second motor vehicle 108 because the geographic locations for the second motor vehicle 108 indicate that the second motor vehicle 108 is currently approaching or may approach the fixed police radar unit 112 and the motion-sensing door 114. Conversely, the server 120 no longer provides the threat levels for the fixed police radar unit 112 to the first motor vehicle 106 because the geographic locations for the first motor vehicle 106 indicate that first motor vehicle 106 has already passed and is currently moving away from the fixed police radar unit 1 12.
  • the server 120 may also communicate the predictions based on specific geographic locations to a mobile communication device, such as a mobile telephone which is not depicted in Fig. 1 , based on a corresponding geographic location for the mobile communication device.
  • a mobile communication device such as a mobile telephone which is not depicted in Fig. 1
  • the mobile communication device must subscribe to a threat level service.
  • the mobile communication device may not have the capacity to detect electromagnetic signals, the mobile communication device user may act as an additional data supplier by submitting a confirmation of law enforcement speed monitoring activity associated with the geographic location of the mobile communication device.
  • the mobile communication device may act as network interface 116 by transmitting and receiving data with server 120 and radar detector 102.
  • a mobile communication device may be any device that can be operably associated with server 120, including a mobile phone, a smart phone, a satellite phone, a portable computer, a navigation system with wireless connectivity, an electromagnetic signal detector, a citizens band radio, and/or any other device with wireless connectivity.
  • a device without wireless connectivity such as a navigation system or GPS system without wireless connectivity, may employ a static but updatable version of the system by downloading a database of threat levels from server 120 into the device's storage element.
  • the device without wireless connectivity could communicate predicted alerts to the user of such device based on the threat levels stored in the device.
  • the database in the device could be updated periodically by the user by connecting the device to a networked device or an external storage device, such as a portable hard drive, in which the database is stored.
  • Each of the radar detectors 102 - 104 communicates an alert level to a corresponding radar detector user based on predictions, or threat levels, that correspond to the geographic locations of the radar detectors 102 - 104, as well as other predictive data described above.
  • the resulting alert may be communicated to the radar detector user through a display, a mechanical response, and/or an audible or voice alert via the radar detector or another mobile device, such as a mobile telephone.
  • the second radar detector 104 flashes red, beeps rapidly, displays a 95% alert level, and provides a voice alert that identifies a 95% alert level when the second vehicle 108 approaches the fixed police radar unit 112.
  • Each of the radar detectors 102 - 104 may communicate the initial detection alert level, a predicted alert level or threat level, and/or a combined alert level to a radar detector user.
  • each of the radar detectors 102 - 104 may communicate other relevant data, such as local traffic, safety or evacuation notices,
  • the first radar detector 102 may provide a first display showing a medium detection alert, a second display showing a 85% probability threat level, a third display showing a combined 95% alert level, and an audible voice alert providing notice that speed limits in the local area are known to be strictly enforced.
  • the display may be color change on the radar detector, a series of light-emitting diodes, a liquid crystal display, and/or any other display known or yet to be discovered and will remain within the scope and spirit of the invention.
  • the mechanical response may be a change to the vehicles operation, such as automatically decelerating the vehicle as a safety risk approaches, and/or any other mechanical response known or yet to be discovered and will remain within the scope and spirit of the invention.
  • the audible alert may be a beep, buzz, voice response, and/or any other audible alert known or yet to be discovered and will remain within the scope and spirit of the invention.
  • Radar detectors 102 - 104 include data storage components such as a buffer or other form of memory and data processing components. In one embodiment, these components may contain a selected data set and be capable of processing all or portions of analysis algorithm 124 within radar detectors 102 - 104 for the data set in memory.
  • radar detector 102 may contain a data set in memory relating to the surrounding geographic area that includes predicted alert levels within that geographic area. As radar detector 102 is in use it collects additional data relevant to the same geographic area and aggregates the collected data with the stored data, and analysis algorithm 124 calculates updated probabilities and threat levels based upon the aggregated data.
  • This embodiment allows continued updating in a given area without connection to server 120 permitting continued analysis without taking up the communication network's bandwidth and/or analysis when connection to server 120 is not available.
  • Communication with server 120 may be based upon a schedule to upload collected data to server 120 and a schedule to download any updated data from server 120. For example, if a server predicts a change in threat levels in the geographic area to occur around 4:30 p.m., it may initiate a download of updated threat levels to radar detector 102 at 4:15 p.m.
  • communication with server 120 may be triggered by specified events.
  • radar detector 102 may initiate communication with server 120 in order to download an updated data set based upon the current location of radar detector 102 and the direction of travel.
  • server 120 may initiate communication with server 120 in order to download an updated data set based upon the current location of radar detector 102 and the direction of travel.
  • the extent and scope of the data set stored in memory of radar detectors 102 - 104 and the extent of analysis conducted within the data processor of radar detectors 102 - 104 may vary and remain within the scope and spirit of the present invention.
  • Figure 2 is a flowchart depicting an embodiment of process 200.
  • the process 200 may be a method executed by the system 100 and/or a computer program product to provide predictions based on data analyzed from networked radar detectors.
  • data is communicated from electromagnetic signal detectors to a server.
  • the first radar detector 102 and the second radar detector 104 communicate data that indicates detection of the fixed police radar unit 112 to the server 120.
  • an analysis algorithm is executed to analyze data and generate predictions of alert levels based on geographic locations. For example, the analysis algorithm predicts a 95% probability, or threat level, that the fixed police radar unit 112 is a law enforcement speed monitoring device based on the aggregated data received from the first radar detector 102 and the second radar detector 104.
  • the aggregated data may also include information received other radar detectors associated with the system which have passed through the identical segment or segments in close proximity to that segment and/or any other data sources which are associated with or entered into the system.
  • a plurality of radar detectors is not necessary because a single radar detector may collect data for aggregation over time, thereby supporting the predictive analysis.
  • predictions of alert levels and/or threat levels based on geographic locations are communicated to a mobile communication device.
  • the server 120 communicates the 95% probability and/or a high threat level to the radar detectors 102 - 104 whenever any of the radar detectors 102 - 104 approach the geographic location likely to contain fixed police radar unit 1 12.
  • predictions of alert levels and/or threat levels based on geographic locations are communicated to mobile communication device users.
  • the second radar detector 104 receives the 95% probability, or threat level, and communicates an alert level to the operator of the second motor vehicle 108 whenever the second motor vehicle approaches the geographic location likely to contain fixed police radar unit 112.
  • the radar detectors 102 - 104 and/or their mobile communication devices may utilize the "cloud computing" software usage model, where individual client devices can quickly begin using the latest software without the need for a firmware update or hardware revision. Changes made on the database or "cloud" side may be seen in near-real-time for the installed client / user base.
  • the radar detectors 102 - 104 may query the server 120 and/or the database 122 for any updates to the data upload packet protocol, and download any updates as appropriate. This may be a simple software change, a firmware update, and/or any other method for updating.
  • the radar detectors 102 - 104 may read data coming from the logging outputs of the radar detectors 102 - 104 in real time, and may parse that data according to the loaded packet protocol before reformatting the data and uploading the data to the server 120. Based on the volume of data that the server 120 receives from the radar detectors 102 - 104, the server 120 may adjust the packet protocols and parsing algorithms to get the highest quality of data using the lowest possible bandwidth.
  • radar detectors 102 - 104 have a proximity mode designed for use when multiple radar detectors and/or mobile communication devices are within a certain proximity to one another.
  • Server 120 may monitor the geographic proximity of radar detector 102 to radar detector 104. When server 120 determines that radar detectors 102 - 104 are within a certain proximity to one another, server 120 may transmit instructions to radar detectors 102— 104 to execute in proximity mode. In the proximity mode, radar detectors 102 - 104 operate with a real-time or near-real-time communication with server 120 which analyzes and transfers updates to each radar detector in the given proximity.
  • radar detectors 102 - 104 when radar detectors 102 - 104 are within a given proximity and operating in proximity mode, if radar detector 102 detects an electromagnetic signal, radar detector 102 communicates data regarding the detected electromagnetic signal to server 120 in near-real time. Server 120 analyzes the new data from radar detector 102, updates threat levels based upon the new data, and communicates the updated threat levels to radar detector 104 in near-real time. When radar detectors 102 - 104 separate beyond a certain proximity, both radar detectors exit out of proximity mode (unless one is within proximity to another device). As one skilled in the art will recognize, what constitutes a certain proximity may vary, and the proximity for entering proximity mode and exiting proximity mode may be the same or may differ and remain within the scope and spirit of the invention. Proximity mode's functional distance may vary based on vehicle speed, heading, time of day, volume of data in the database at that location, or any other criteria not listed here, and remain within the scope and spirit of the invention.
  • Figure 3 depicts one embodiment of a map illustration with overlaid threat levels.
  • the map illustration may be displayed on any display associated with a mobile communication device.
  • the display may be shown on a mobile phone, a portable computer, and/or an electromagnetic signal detector having a display.
  • Key 300 shows the overlay styles and associates a meaning, such as the threat level, with each style of overlay.
  • a meaning such as the threat level
  • any meaning may be associated with a given overlay style and remain within the scope and spirit of the invention.
  • overlay styles there are four overlay styles: overlay design 302 associated with a high threat level, overlay design 304 associated with a medium threat level, overlay design 306 associated with a low threat level, and overlay design 308 associated with a not applicable threat level due to a lack of data.
  • any number of overlays may be employed and remain within the scope and spirit of the invention.
  • any overlay design may be used, including color overlays, line designs (such as those pictured), other designs and/or any combination of colors and designs.
  • Map 310 depicts a street layout with portions overlaid with threat levels associated with key 300.
  • overlay segment 312 has overlay design 304 indicating the road section covered by overlay segment 312 has a medium threat level
  • overlay segments 314 and 320 have overlay design 306 indicating the road sections covered by overlay segments 314 and 320 have a low threat level
  • overlay segments 316 and 318 have overlay design 302 indicating the road sections covered by overlay segments 316 and 318 have a high threat level.
  • the portions of map 310 not overlaid with overlay designs 302 - 306 are overlaid with overlay design 308 indicating that a threat level is not applicable due to a lack of data in areas covered by overlay design 308.
  • Overlay segments may be associated with specific road segments, such as those depicted by overlay segments 312 - 316, or may be based upon an area evaluation, such as the rectangular overlay segment 318 and radial overlay segment 320 depicted in this embodiment.
  • overlay segments may correlate to individual road segments, grid sections of a map, geographical areas, shapes, and/or any design related to the map or the geographical area the map represents, and remain within the scope and spirit of the invention.
  • the various overlay segments 312 - 320 may change which overlay design is displayed as the mobile communication device downloads an update from server 120.
  • server 120 may predict that a road section covered by a portion of overlay segment 314 should be associated with a high threat level based upon data collected by radar detector 102. Accordingly, once radar detector 104 downloads the update, the relevant portion of overlay segment 314 will depict overlay design 302 indicating the high threat level, while the remainder of overlay segment 314 will maintain overlay design 306 indicating a low threat level.
  • individual road segments may change color on map 310 to indicate reevaluated threat levels.

Landscapes

  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Optics & Photonics (AREA)
  • Traffic Control Systems (AREA)
  • Alarm Systems (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

L'invention porte sur un détecteur de radar, qui accède à un module d'interface réseau, lequel permet une communication de données vers et à partir d'un serveur. Le serveur exécute des algorithmes d'analyse qui analysent des données reçues à partir de multiples détecteurs de radar afin de développer des prédictions concernant la probabilité d'alertes ou de menaces futures dans des emplacements géographiques. Le serveur communique les prédictions à chacun des détecteurs de radar sur la base des emplacements géographiques correspondant à chacun des détecteurs de radar. Chaque détecteur de radar communique des niveaux d'alerte selon les besoins à son utilisateur de détecteur de radar correspondant sur la base de prédictions qui correspondent aux emplacements géographiques correspondant à chacun des détecteurs de radar.
PCT/US2010/059115 2009-12-07 2010-12-06 Analyse de données à partir de détecteurs de radar en réseau WO2011071826A1 (fr)

Priority Applications (10)

Application Number Priority Date Filing Date Title
RU2012123469/07A RU2515465C2 (ru) 2009-12-07 2010-12-06 Способ анализирования данных, полученных от объединенных детекторов радаров
CN2010800632586A CN102753988A (zh) 2009-12-07 2010-12-06 对来自网络化雷达检测器的数据的分析
US13/514,232 US8842004B2 (en) 2009-12-07 2010-12-06 Analyzing data from networked radar detectors
US13/840,496 US9132773B2 (en) 2009-12-07 2013-03-15 Mobile communication system and method for analyzing alerts associated with vehicular travel
US13/840,589 US20130207829A1 (en) 2009-12-07 2013-03-15 Analyzing data from networked radar detectors
US14/594,823 US20150123834A1 (en) 2009-12-07 2015-01-12 Analyzing data from networked radar detectors
US14/594,793 US20150123833A1 (en) 2009-12-07 2015-01-12 Analyzing data from networked radar detectors
US14/853,818 US9848114B2 (en) 2009-12-07 2015-09-14 Vehicle camera system
US15/809,850 US10142535B2 (en) 2009-12-07 2017-11-10 Vehicle camera system
US16/198,232 US10298832B2 (en) 2009-12-07 2018-11-21 Vehicle camera system

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US26717209P 2009-12-07 2009-12-07
US61/267,172 2009-12-07

Related Parent Applications (2)

Application Number Title Priority Date Filing Date
PCT/US2010/060952 Continuation-In-Part WO2011087714A1 (fr) 2009-12-07 2010-12-17 Détecteur de radar assurant l'interface avec un dispositif de communication mobile
US13/518,167 Continuation-In-Part US8970422B2 (en) 2009-12-22 2010-12-17 Radar detector that interfaces with a mobile communication device

Related Child Applications (5)

Application Number Title Priority Date Filing Date
US13/514,232 A-371-Of-International US8842004B2 (en) 2009-12-07 2010-12-06 Analyzing data from networked radar detectors
PCT/US2010/060952 Continuation-In-Part WO2011087714A1 (fr) 2009-12-07 2010-12-17 Détecteur de radar assurant l'interface avec un dispositif de communication mobile
US13/518,167 Continuation-In-Part US8970422B2 (en) 2009-12-22 2010-12-17 Radar detector that interfaces with a mobile communication device
US13/840,589 Continuation US20130207829A1 (en) 2009-12-07 2013-03-15 Analyzing data from networked radar detectors
US13/840,496 Continuation-In-Part US9132773B2 (en) 2009-12-07 2013-03-15 Mobile communication system and method for analyzing alerts associated with vehicular travel

Publications (1)

Publication Number Publication Date
WO2011071826A1 true WO2011071826A1 (fr) 2011-06-16

Family

ID=44145872

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2010/059115 WO2011071826A1 (fr) 2009-12-07 2010-12-06 Analyse de données à partir de détecteurs de radar en réseau

Country Status (4)

Country Link
US (4) US8842004B2 (fr)
CN (1) CN102753988A (fr)
RU (1) RU2515465C2 (fr)
WO (1) WO2011071826A1 (fr)

Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2013132031A1 (fr) * 2012-03-07 2013-09-12 Tomtom International B.V. Système de maintenance de base de données de points d'intérêt
WO2014001579A1 (fr) * 2012-06-29 2014-01-03 Tomtom Development Germany Gmbh Procédé et système d'estimation de position
US8842004B2 (en) 2009-12-07 2014-09-23 Cobra Electronics Corporation Analyzing data from networked radar detectors
JP2014535189A (ja) * 2011-10-01 2014-12-25 クゥアルコム・インコーポレイテッドＱｕａｌｃｏｍｍ Ｉｎｃｏｒｐｏｒａｔｅｄ コンテキストデータのロケーションベースクラウドソーシングのためのフレキシブルなアーキテクチャ
US8970422B2 (en) 2009-12-22 2015-03-03 Cobra Electronics Corporation Radar detector that interfaces with a mobile communication device
US9031779B2 (en) 2012-05-30 2015-05-12 Toyota Motor Engineering & Manufacturing North America, Inc. System and method for hazard detection and sharing
US9132773B2 (en) 2009-12-07 2015-09-15 Cobra Electronics Corporation Mobile communication system and method for analyzing alerts associated with vehicular travel
US9786171B2 (en) 2016-01-26 2017-10-10 Toyota Motor Engineering & Manufacturing North America, Inc. Systems and methods for detecting and distributing hazard data by a vehicle
US9848114B2 (en) 2009-12-07 2017-12-19 Cobra Electronics Corporation Vehicle camera system
US10197665B2 (en) 2013-03-12 2019-02-05 Escort Inc. Radar false alert reduction
US20190361116A1 (en) * 2018-05-28 2019-11-28 Electronics And Telecommunications Research Institute Apparatus and method for high-speed tracking of vessel
US10677888B2 (en) 2015-09-28 2020-06-09 Escort Inc. Radar detector with multi-band directional display and enhanced detection of false alerts
US11061108B1 (en) 2017-12-18 2021-07-13 Escort Inc. Sliding window discrete Fourier transform (SWDFT) police signal warning receiver

Families Citing this family (36)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11697372B1 (en) * 2011-01-04 2023-07-11 Spirited Eagle Enterprises, LLC System and method for enhancing situational awareness in a transportation vehicle
US9227568B1 (en) 2012-01-04 2016-01-05 Spirited Eagle Enterprises LLC System and method for managing driver sensory communication devices in a transportation vehicle
US8838321B1 (en) 2012-11-15 2014-09-16 Google Inc. Modifying a vehicle state based on the presence of a special-purpose vehicle
US9779357B1 (en) * 2013-03-07 2017-10-03 Steve Dabell Method and apparatus for providing estimated patrol properties and historic patrol records
US9251687B2 (en) * 2013-04-19 2016-02-02 Jonathan Thompson Global positioning system equipped hazard detector and a system for providing hazard alerts thereby
US9329262B2 (en) * 2013-10-25 2016-05-03 Raytheon Company Situational awareness personal service
CN104867347A (zh) * 2014-02-26 2015-08-26 厦门瑞忆科技有限公司 无线安全警示器数据更新装置
DE112014006741B4 (de) 2014-06-12 2021-10-28 Motorola Solutions, Inc. Verfahren und Systeme zur automatischen Einrichtung von Gesprächsgruppen basierend auf dem Received-Signal-Strength-Indicator (RSSI)
RU2577848C1 (ru) * 2014-09-05 2016-03-20 Супра Технолоджис Лимитед Радар-детектор
CN105564301B (zh) * 2014-10-11 2017-10-24 惠州市德赛西威汽车电子股份有限公司 一种带倒车雷达自动诊断的汽车音响系统及其诊断方法
FR3029293B1 (fr) * 2014-12-01 2018-03-02 Airbus Group Sas Procede et ensemble de localisation de decharges electrostatiques sur aeronef en vol
US20180174446A1 (en) * 2015-02-09 2018-06-21 Kevin Sunlin Wang System and method for traffic violation avoidance
JP6193912B2 (ja) * 2015-04-24 2017-09-06 株式会社パイ・アール ドライブレコーダ
US10261170B2 (en) * 2015-06-02 2019-04-16 Valentine Research, Inc. Image analysis and radar detectors
US9467922B1 (en) * 2015-06-15 2016-10-11 Amazon Technologies, Inc. Cellular connections between user equipment and wireless stations based on user equipment location and wireless station locations
US9771082B2 (en) * 2015-08-13 2017-09-26 International Business Machines Corporation Reducing cognitive demand on a vehicle operator by generating passenger stimulus
WO2017048581A1 (fr) * 2015-09-14 2017-03-23 Cobra Electronics Corporation Système de caméra de véhicule
US10019904B1 (en) 2016-04-11 2018-07-10 State Farm Mutual Automobile Insurance Company System for identifying high risk parking lots
US10247565B2 (en) 2016-04-11 2019-04-02 State Farm Mutual Automobile Insurance Company Traffic risk avoidance for a route selection system
US10026309B1 (en) 2016-04-11 2018-07-17 State Farm Mutual Automobile Insurance Company Networked vehicle control systems to facilitate situational awareness of vehicles
US11851041B1 (en) 2016-04-11 2023-12-26 State Farm Mutual Automobile Insurance Company System for determining road slipperiness in bad weather conditions
US10486708B1 (en) 2016-04-11 2019-11-26 State Farm Mutual Automobile Insurance Company System for adjusting autonomous vehicle driving behavior to mimic that of neighboring/surrounding vehicles
US10222228B1 (en) 2016-04-11 2019-03-05 State Farm Mutual Automobile Insurance Company System for driver's education
US10233679B1 (en) * 2016-04-11 2019-03-19 State Farm Mutual Automobile Insurance Company Systems and methods for control systems to facilitate situational awareness of a vehicle
US10872379B1 (en) 2016-04-11 2020-12-22 State Farm Mutual Automobile Insurance Company Collision risk-based engagement and disengagement of autonomous control of a vehicle
US10571283B1 (en) 2016-04-11 2020-02-25 State Farm Mutual Automobile Insurance Company System for reducing vehicle collisions based on an automated segmented assessment of a collision risk
US11002826B2 (en) * 2016-05-18 2021-05-11 Nec Corporation Distributed-cooperative-information processing device, distributed-cooperative-information processing method, and recording medium
US20180082599A1 (en) * 2016-09-21 2018-03-22 Trung Nguyen Collision Warning Assembly
RU2666103C2 (ru) * 2016-12-13 2018-09-05 Федеральное государственное бюджетное образовательное учреждение высшего образования "Юго-Западный государственный университет" (ЮЗГУ) Способ автоматизированного оповещения водителей транспортных средств на особо опасных участках дороги
RU2645598C1 (ru) * 2017-01-31 2018-02-21 "Войсковая Часть 2337" Способ охранного мониторинга с применением линейного радиоволнового средства обнаружения
CN107682110B (zh) * 2017-03-06 2020-02-11 北京猎户星空科技有限公司 一种数据传输方法、装置及雷达设备
US10719899B1 (en) * 2017-08-31 2020-07-21 Steve Dabell Method and apparatus for utilizing estimated patrol properties and historic patrol records
CN108549073B (zh) * 2018-03-26 2020-09-29 北京航天广通科技有限公司 一种参数测量方法及系统
US11176799B2 (en) 2019-09-10 2021-11-16 Jonathan Thompson Global positioning system equipped with hazard detector and a system for providing hazard alerts thereby
US20210201666A1 (en) * 2019-12-31 2021-07-01 Oath Inc. Scalable and distributed detection of road anomaly events
US11781883B1 (en) * 2020-06-08 2023-10-10 Steve Dabell Method and apparatus for utilizing estimated patrol properties and historic patrol records

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020135504A1 (en) * 2001-04-09 2002-09-26 Neil Singer Networked radar detection system and method
US20030214430A1 (en) * 2002-05-03 2003-11-20 Paul Husted Method and apparatus for physical layer radar pulse detection and estimation
US20040254729A1 (en) * 2003-01-31 2004-12-16 Browne Alan L. Pre-collision assessment of potential collision severity for road vehicles
US20070222639A1 (en) * 2006-03-24 2007-09-27 Wavetronix Llc Monitoring signalized traffic flow

Family Cites Families (62)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3956626A (en) 1973-06-14 1976-05-11 Mcdonnell Douglas Corporation Pulse quaternary communication means
US5943653A (en) 1989-09-21 1999-08-24 Ultradata Systems, Inc. Electronic coupon storage and retrieval system correlated to highway exit service availability information
US5229947A (en) 1989-09-21 1993-07-20 Laser Data Technology, Inc. Highway information system
US5021961A (en) 1989-09-21 1991-06-04 Laser Data Technology, Inc. Highway information system
US5218467A (en) 1990-12-28 1993-06-08 Nasa And Laser Data Technology, Inc. Multi-access laser communications transceiver system
US5151701A (en) 1991-02-25 1992-09-29 Valentine Research, Inc. Police radar detectors for detecting radar signals and determining the directional origin of the signal source
US5206651A (en) 1991-04-18 1993-04-27 Valentine Research, Inc. Motor vehicle police radar detector for detecting multiple radar sources
US5250951A (en) 1991-04-18 1993-10-05 Valentine Research, Inc. Motor vehicle police radar detector for detecting multiple radar sources
US5515402A (en) 1992-08-14 1996-05-07 Harris Corporation Quadrature filter with real conversion
RU2084910C1 (ru) * 1993-10-18 1997-07-20 Государственный центральный научно-исследовательский радиотехнический институт Автомобильное устройство обнаружения сигналов радарных установок контроля скорости движения на автотрассах
USD366659S (en) 1993-12-08 1996-01-30 Laser Data Technology, Inc. Cradle mount for a personal computer for use in a vehicle
WO1995019030A1 (fr) 1994-01-05 1995-07-13 Pois, Inc. Appareil et procede pour systeme personnel d'information a bord d'un vehicule
US5510793A (en) 1995-03-30 1996-04-23 Gregg, Iii; Eugene S. Combined radar detector, speed measuring device and printer for verifying vehicle speed
US5784021A (en) 1996-01-25 1998-07-21 Cobra Electronics Corporation Noiseless radar detector
US7042345B2 (en) * 1996-09-25 2006-05-09 Christ G Ellis Intelligent vehicle apparatus and method for using the apparatus
US5815092A (en) 1997-04-22 1998-09-29 Gregg, Iii; Eugene Stuart Combined speed measuring device detector, speed measuring device and printer for verifying vehicle speed
US5977884A (en) 1998-07-01 1999-11-02 Ultradata Systems, Inc. Radar detector responsive to vehicle speed
US6118403A (en) 1998-11-13 2000-09-12 Lang; Brook Speed trap information system
US6204798B1 (en) 1999-04-14 2001-03-20 Fleming, Iii Hoyt A. Method and apparatus for alerting an operator of a motor vehicle to an incoming radar signal
US6384776B1 (en) 1999-04-30 2002-05-07 B. Todd Martin EM signal detection and position broadcasting system and method
US6201493B1 (en) 1999-05-28 2001-03-13 Lucent Technologies Inc. Radar detector arrangement
US6266617B1 (en) 1999-06-10 2001-07-24 Wayne W. Evans Method and apparatus for an automatic vehicle location, collision notification and synthetic voice
US8525723B2 (en) 1999-06-14 2013-09-03 Escort Inc. Radar detector with navigation function
CA2381585C (fr) 1999-06-14 2008-08-05 Escort Inc. Recepteur d'alerte radar avec fonctions sensibles a la position et a la vitesse
US6611755B1 (en) * 1999-12-19 2003-08-26 Trimble Navigation Ltd. Vehicle tracking, communication and fleet management system
US7183942B2 (en) 2000-01-26 2007-02-27 Origin Technologies Limited Speed trap detection and warning system
US6590529B2 (en) 2000-02-14 2003-07-08 Mysky Communications Individualized, location specific weather forecasting system
US6980092B2 (en) 2000-04-06 2005-12-27 Gentex Corporation Vehicle rearview mirror assembly incorporating a communication system
US6400304B1 (en) 2000-05-15 2002-06-04 Chubbs, Iii William Integrated GPS radar speed detection system
US6265989B1 (en) 2000-06-17 2001-07-24 Richard Taylor GPS enabled speeding detector
US6675085B2 (en) 2000-08-17 2004-01-06 Michael P. Straub Method and apparatus for storing, accessing, generating and using information about speed limits and speed traps
US6498569B2 (en) 2001-01-12 2002-12-24 Patrick Dijkstra Traffic information analyzer system
US6748322B1 (en) 2001-01-12 2004-06-08 Gem Positioning System, Inc. Speed monitoring device for motor vehicles
US20020152264A1 (en) 2001-02-07 2002-10-17 Zandiant Technologies, Inc. Personal vehicular internet appliance
CA2355426A1 (fr) * 2001-08-17 2003-02-17 Luther Haave Systeme et methode de suivi des biens
US6469653B1 (en) 2001-08-22 2002-10-22 Uniden America Corporation Apparatus and method for selectively monitoring radar signals and providing an alert responsive thereto
US6567035B1 (en) * 2001-11-30 2003-05-20 Bbnt Solutions Llc Systems and methods for networking radar detectors
US6985753B2 (en) 2001-12-07 2006-01-10 Dashsmart Investments Llc Portable navigation and communication systems
US6480144B1 (en) 2002-01-30 2002-11-12 Ford Global Technologies, Inc. Wireless communication between countermeasure devices
US6845317B2 (en) 2002-11-04 2005-01-18 Dean A. Craine Navigational-based speed limit recording and warning system
US9818136B1 (en) 2003-02-05 2017-11-14 Steven M. Hoffberg System and method for determining contingent relevance
KR100467350B1 (ko) 2003-06-02 2005-01-24 (주)씨에이치테크 지피에스 수신기가 결합된 무선 통신 방식을 이용한차량용 레이더/레이저 검출기
US7301494B2 (en) 2004-05-03 2007-11-27 Jeffrey Waters Combination cellular telephone and radar detector
US7590589B2 (en) * 2004-09-10 2009-09-15 Hoffberg Steven M Game theoretic prioritization scheme for mobile ad hoc networks permitting hierarchal deference
US8099466B2 (en) * 2004-10-05 2012-01-17 Reach Unlimited Corp. System and method for vote-based, interest specific collaboration regarding location of objects
TWM287759U (en) 2005-08-26 2006-02-21 Holux Technology Inc Bluetooth satellite receiving device with lighter plug
US20070109187A1 (en) 2005-11-15 2007-05-17 Murphy Gary L Radar Detection, Tracking and Recording System
US7702044B2 (en) 2005-12-05 2010-04-20 Marvell World Trade, Ltd. Radar detection and dynamic frequency selection
US8169185B2 (en) 2006-01-31 2012-05-01 Mojo Mobility, Inc. System and method for inductive charging of portable devices
US20070216521A1 (en) 2006-02-28 2007-09-20 Guensler Randall L Real-time traffic citation probability display system and method
US7471236B1 (en) 2006-03-01 2008-12-30 Telecommunication Systems, Inc. Cellular augmented radar/laser detector
US7899450B2 (en) 2006-03-01 2011-03-01 Telecommunication Systems, Inc. Cellular augmented radar/laser detection using local mobile network within cellular network
US8255155B1 (en) 2006-07-11 2012-08-28 Navteq B.V. Methods of detecting a speed detection of a vehicle and supporting apparatus, system, and readable medium
US7804886B2 (en) 2007-07-10 2010-09-28 Thetaware, Inc. Wearable system for data transmission and reception and method of using the same
US20100188265A1 (en) 2009-01-23 2010-07-29 Hill Lawrence W Network Providing Vehicles with Improved Traffic Status Information
US8373588B2 (en) 2009-02-20 2013-02-12 Escort Inc. Wireless connectivity in a radar detector
US20120268306A1 (en) 2009-02-20 2012-10-25 Escort Inc. Wireless Connectivity in a Radar Detector
US8624771B2 (en) 2009-02-20 2014-01-07 Escort Inc. Wireless connectivity in a radar detector
US8857408B2 (en) * 2009-03-31 2014-10-14 Peoplenet Communications Corporation Real-time dynamic heavy-vehicle idle alarm
CN102753988A (zh) 2009-12-07 2012-10-24 科布拉电子有限公司 对来自网络化雷达检测器的数据的分析
US9132773B2 (en) 2009-12-07 2015-09-15 Cobra Electronics Corporation Mobile communication system and method for analyzing alerts associated with vehicular travel
CN102763000A (zh) 2009-12-22 2012-10-31 科布拉电子有限公司 与移动通信装置相联系的雷达检测器

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020135504A1 (en) * 2001-04-09 2002-09-26 Neil Singer Networked radar detection system and method
US20030214430A1 (en) * 2002-05-03 2003-11-20 Paul Husted Method and apparatus for physical layer radar pulse detection and estimation
US20040254729A1 (en) * 2003-01-31 2004-12-16 Browne Alan L. Pre-collision assessment of potential collision severity for road vehicles
US20070222639A1 (en) * 2006-03-24 2007-09-27 Wavetronix Llc Monitoring signalized traffic flow

Cited By (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9132773B2 (en) 2009-12-07 2015-09-15 Cobra Electronics Corporation Mobile communication system and method for analyzing alerts associated with vehicular travel
US10298832B2 (en) 2009-12-07 2019-05-21 Cobra Electronics Corporation Vehicle camera system
US10142535B2 (en) 2009-12-07 2018-11-27 Cobra Electronics Corporation Vehicle camera system
US8842004B2 (en) 2009-12-07 2014-09-23 Cobra Electronics Corporation Analyzing data from networked radar detectors
US9848114B2 (en) 2009-12-07 2017-12-19 Cobra Electronics Corporation Vehicle camera system
US8970422B2 (en) 2009-12-22 2015-03-03 Cobra Electronics Corporation Radar detector that interfaces with a mobile communication device
US9135818B2 (en) 2009-12-22 2015-09-15 Cobra Electronics Corporation Radar detector that interfaces with a mobile communication device
JP2014535189A (ja) * 2011-10-01 2014-12-25 クゥアルコム・インコーポレイテッドＱｕａｌｃｏｍｍ Ｉｎｃｏｒｐｏｒａｔｅｄ コンテキストデータのロケーションベースクラウドソーシングのためのフレキシブルなアーキテクチャ
US9836486B2 (en) 2012-03-07 2017-12-05 Tomtom Traffic B.V. Point of interest database maintenance system
WO2013132031A1 (fr) * 2012-03-07 2013-09-12 Tomtom International B.V. Système de maintenance de base de données de points d'intérêt
WO2013132033A1 (fr) * 2012-03-07 2013-09-12 Tomtom International B.V. Système de maintenance de base de données de points d'intérêt
US9031779B2 (en) 2012-05-30 2015-05-12 Toyota Motor Engineering & Manufacturing North America, Inc. System and method for hazard detection and sharing
WO2014001579A1 (fr) * 2012-06-29 2014-01-03 Tomtom Development Germany Gmbh Procédé et système d'estimation de position
US9763215B2 (en) 2012-06-29 2017-09-12 Tomtom Traffic B.V. Location estimation method and system
CN104584094A (zh) * 2012-06-29 2015-04-29 通腾发展德国公司 位置估计方法及系统
CN104584094B (zh) * 2012-06-29 2016-11-23 通腾发展德国公司 位置估计方法及系统
US10197665B2 (en) 2013-03-12 2019-02-05 Escort Inc. Radar false alert reduction
US10677888B2 (en) 2015-09-28 2020-06-09 Escort Inc. Radar detector with multi-band directional display and enhanced detection of false alerts
US9786171B2 (en) 2016-01-26 2017-10-10 Toyota Motor Engineering & Manufacturing North America, Inc. Systems and methods for detecting and distributing hazard data by a vehicle
US11061108B1 (en) 2017-12-18 2021-07-13 Escort Inc. Sliding window discrete Fourier transform (SWDFT) police signal warning receiver
US20190361116A1 (en) * 2018-05-28 2019-11-28 Electronics And Telecommunications Research Institute Apparatus and method for high-speed tracking of vessel

Also Published As

Publication number Publication date
RU2012123469A (ru) 2014-01-27
US20150123833A1 (en) 2015-05-07
US20130207829A1 (en) 2013-08-15
US8842004B2 (en) 2014-09-23
CN102753988A (zh) 2012-10-24
US20150123834A1 (en) 2015-05-07
RU2515465C2 (ru) 2014-05-10
US20120326889A1 (en) 2012-12-27

Similar Documents

Publication Publication Date Title
US8842004B2 (en) Analyzing data from networked radar detectors
US8970422B2 (en) Radar detector that interfaces with a mobile communication device
US9132773B2 (en) Mobile communication system and method for analyzing alerts associated with vehicular travel
CN110997387B (zh) 具有自主驾驶能力的运载工具的风险处理
US9903733B2 (en) Vehicular communications network and methods of use and manufacture thereof
RU2625522C2 (ru) Система мобильной связи и способ анализа предупреждений, связанных с автомобильным движением
US10832561B2 (en) Real time municipal imminent danger warning system
US11508022B1 (en) Method and apparatus for utilizing estimated patrol properties and historic patrol records
Sattar et al. Recent advances on context-awareness and data/information fusion in ITS
US10109191B2 (en) Method of quickly detecting road distress
WO2023155218A1 (fr) Système et procédé de réduction de fausses alertes dans un système de gestion de route
CN117178309A (zh) 用于创建具有碰撞概率的地图的方法
US11195413B1 (en) Method for relaying event information in a multi-tier V2X system
CA3169567C (fr) Detecteur radar avec dispositif d'affichage directionnel multibande et detection amelioree des fausses alertes
US11781883B1 (en) Method and apparatus for utilizing estimated patrol properties and historic patrol records
CN111801954B (zh) 在多层v2x系统中中继事件信息的方法
US20240053434A1 (en) Radar detector using position detection
US20240053433A1 (en) Radar detector using position detection
CN115968490A (zh) 在道路管理系统中减少错误警报的系统和方法

Legal Events

Date Code Title Description
WWE Wipo information: entry into national phase

Ref document number: 201080063258.6

Country of ref document: CN

121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 10836485

Country of ref document: EP

Kind code of ref document: A1

DPE1 Request for preliminary examination filed after expiration of 19th month from priority date (pct application filed from 20040101)
NENP Non-entry into the national phase

Ref country code: DE

WWE Wipo information: entry into national phase

Ref document number: 2012123469

Country of ref document: RU

WWE Wipo information: entry into national phase

Ref document number: 13514232

Country of ref document: US

122 Ep: pct application non-entry in european phase

Ref document number: 10836485

Country of ref document: EP

Kind code of ref document: A1