System and method for detecting use of a wireless device while driving

Information

  • Patent Grant
  • 8688180
  • Patent Number
    8,688,180
  • Date Filed
    Wednesday, August 6, 2008
    16 years ago
  • Date Issued
    Tuesday, April 1, 2014
    10 years ago
Abstract
A system for detecting the use of wireless devices such as a mobile phone, personal digital assistant (PDA), or pagers in a moving vehicle receives wireless signals inside a vehicle using a radio frequency (RF) sensor(s) and converts the RF signals into voltage signals. The voltage signals are then compared with known waveforms to determine if the wireless signals indicate a received call, if the received call is answered, a transmitted call, an SMS text message, data associated with internet browsing on a wireless device, or Bluetooth activity.
Description
TECHNICAL FIELD

This disclosure relates to a system and method for detecting the use of wireless devices, such as mobile phones, in vehicles.


BACKGROUND

The use of wireless devices, such as cellular telephones or personal digital assistants (PDA), by drivers who talk on the phone or send or read text messages while driving is thought to be a cause of distracted, erratic, and/or aggressive driving, especially among teenage drivers, and is believed to increase the likelihood of accidents. Some cities restrict cellular phone use while driving or require that drivers use hands-free mode on their wireless phone to talk while driving. Other cities are considering restricting the use of text messaging applications while driving.


Additionally, parents desire to monitor their children's driving and cellular phone use, and fleet owners or insurance companies desire to monitor drivers' cellular phone use for liability purposes.


As shown in FIG. 1, using a driving simulator, Ford compared the response of teenage and adult drivers to traffic events happening in front of them. As shown on the left portion of the chart, both groups of drivers missed about 3% of potentially dangerous events under normal simulated driving conditions. When placing a phone call using a handheld device, as shown on the right portion of the chart, the rate of missed events rose to 13.6% for adult drivers and to 53.8% for teenage drivers.


Therefore, there is a need to improve driver behavior and safety with respect to the use of wireless devices in moving vehicles.


SUMMARY

The present invention is directed to a system and method of detecting the use of wireless devices such as a mobile phone, personal digital assistant (PDA), or pager in a moving vehicle. The invention receives wireless signals inside a vehicle using a radio frequency (RF) sensor and converts the RF signals into voltage signals. The voltage signals are then compared with known waveforms to determine if the wireless signals indicate a received call, if the received call is answered, a transmitted call, an SMS text message, data associated with internet browsing on a wireless device, or Bluetooth activity.


In an embodiment of the present invention, the number of passengers in a vehicle is monitored. The number of passengers may be determined by discriminating among multiple wireless signals, or may be determined by using various vehicle sensors, including seat belt sensors, seat weight sensors, airbag sensors, tire pressure sensors, and others.


Further features of the present invention, as well as the structure and operation of various embodiments of the present invention are described in detail below with reference to the accompanying drawings.





BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, like reference numbers indicate identical or functionally similar elements. Additionally, the left-most digit(s) of a reference number identifies the drawing in which the reference number first appears.



FIG. 1 is a chart comparing the percentage of events not detected among adult and teenage drivers while placing a phone call and under regular driving conditions;



FIG. 2 is a block diagram of an RF sensing device for detecting wireless signals in a moving vehicle;



FIG. 3 is a block diagram of a directional RF sensing device for detecting wireless signals in a moving vehicle;



FIG. 4 is a block diagram of multiple RF sensing devices for detecting wireless signals in a moving vehicle;



FIG. 5 is a block diagram of a processor configured to detect wireless signals in a moving vehicle;



FIG. 6 is a state diagram for the detection of wireless signals in a moving vehicle;



FIG. 7 is a flowchart of a method for detecting wireless signals in a moving vehicle;



FIG. 8 is a waveform of a TDMA received voice call;



FIG. 9 is a waveform of a TDMA transmit voice call;



FIG. 10 is a waveform of a TDMA received unanswered voice call;



FIG. 11 is a waveform of a TDMA received and answered voice call;



FIG. 12 is a waveform of a TDMA transmit voice call;



FIG. 13 is a waveform of a TDMA transmit voice call;



FIG. 14 is a waveform of a TDMA SMS text message;



FIG. 15 is a waveform of a TDMA SMS sending text message;



FIG. 16 is a waveform of a TDMA SMS receiving text message;



FIG. 17 is a waveform of a TDMA SMS sending text message;



FIG. 18 is a waveform of a TDMA SMS sending text message;



FIG. 19 is a waveform of a CDMA sending data;



FIG. 20 is a waveform of a CDMA sending data;



FIG. 21 is a waveform of a CDMA sending data;



FIG. 22 is a waveform of a TDMA surfing the web;



FIG. 23 is a waveform of a TDMA surfing the web;



FIG. 24 is a waveform of a TDMA surfing the web;



FIG. 25 is a waveform of a TDMA surfing the web;



FIG. 26 is a waveform of a TDMA surfing the web;



FIG. 27 is a waveform of a TDMA mobile phone at 90° and 0° to sensing antenna;



FIG. 28 is a waveform of Bluetooth discovery mode; and



FIG. 29 is a waveform of Bluetooth discovery mode.





DETAILED DESCRIPTION

A system for detecting the use of wireless devices in a moving vehicle includes an input for receiving signals indicative of wireless transmissions, a processor for characterizing the received signals, and an output for mobile device use notification. Wireless devices include, for example, mobile phones, wireless messaging devices, personal digital assistants (“PDA”), data communication devices, and the like.


Many different strategies may be employed for the detection of wireless transmissions. For example, in some implementations, an antenna is used to receive wireless signals. When wireless signals are received, they are characterized to determine their nature. For example, a mobile phone periodically broadcasts information even when it is not in use. Accordingly, the system is capable of differentiating various transmissions using signal processing techniques, such as the following: (1) filtering the received signals; (2) detecting identifying characteristics of the received signals; (3) performing a statistical analysis to determine the most likely signal characterization; (4) neural networks; (5) and the like. In this manner, actual use can be differentiated from receipt of text messages, receipt of emails, voicemail notification, cell handoffs and control signaling, etc.


When a single antenna is used, it can be difficult to differentiate transmissions from inside the vehicle and transmissions from mobile devices outside the vehicle. Further, a single antenna may make it difficult to determine whether a mobile device is being used by the driver or a passenger. Accordingly, in some embodiments, multiple sensors are used together with signal processing to determine the location of the transmission source. For example, two or more antennas, microphones, or other sensors can be used to each receive the same transmission. Using known signal processing techniques, the differences between the amplitude and phase of the received signals can be used to calculate the location of the transmission source. In this manner, it is possible to differentiate mobile device use by the driver from mobile device use by a passenger or by someone external to the vehicle.


Once cell phone use is detected, appropriate notifications can be made. The notifications sent by the system can be varied depending on the intended implementation. For example, in a teenage driver safety mentoring system, notifications can be sent to parents whenever cell phone is used in a moving car. Implementations may include one or more of the following: (1) notifying the driver of unsafe mobile device utilization in a moving vehicle; and (2) notifying someone other than the driver (e.g., a parent, insurance company, parole officer, police, and the like) of unsafe mobile device utilization in a moving vehicle.


Various implementations of systems and methods for detecting the use of mobile devices are described herein below. In one implementation, a device receives wireless signals inside a vehicle using a radio frequency (RF) sensor and converts the RF signals into voltage signals. The voltage signals are then compared with known waveforms to determine if the wireless signals indicate a received call, if the received call is answered, a transmitted call, an SMS text message, data associated with internet browsing on a wireless device, or Bluetooth activity.


Determining Mobile Device Usage


Referring now to FIG. 2, a device is provided to detect the use of mobile devices in a moving vehicle. A driver's cell phone 201 broadcasts and receives wireless signals. Similarly, another cell phone 203 is located nearby, either with a passenger in the same vehicle or in a nearby vehicle. While driver's cell phone 201 and nearby cell phone 203 are both cell phones, one or both could be another wireless communications device, such as a personal digital assistant (PDA). Alternatively, one or both of cell phones 201 and 203 could be a Bluetooth hands-free device that communicates wirelessly with a master cell phone located near the Bluetooth device. Bluetooth, as is known in the art, is a wireless communications standard used in short-range communications.


Referring again to FIG. 2, a power detector 205 receives wireless signals through its antenna, powered by a power supply 207. The antenna is preferably tuned to the quad-band frequencies used by wireless devices, which are 850, 900, 1800, and 1900 MHz, which includes TDMA, GSM, and CDMA standards, as are known in the art. The power detector 205 outputs a voltage waveform 209. The voltage waveforms are used to determine the use of the mobile phone 201 or 203. Received amplitude levels of the wireless signals are used to determine if the mobile phone is that of the driver or that of another nearby user, such as a passenger or a nearby driver or passenger in a different vehicle.


As shown in FIG. 2, the driver cell phone 201 is located within approximately 2 feet of the power detector 205, while the nearby cell phone 203 is located approximately 4-8 feet from the power detector 205.


Using a simplified version of the free space loss equation, the received power for the two different cell phones, 201 and 203, can be calculated. With isotropic (omni-directional) transmit and receive antennas having 0 dBi gain, distance d=2 feet, transmit frequency f=900 MHz, transmit power=4 watts, transmit distance greater than a wavelength thus prompting far-field equations, the free space loss is given as:












Free





space





loss






(
dB
)


=



36.56
+

20





log






(

d
/
5280

)


+

20





log






(
f
)









=



36.56
+

20





log






(

2
/
5280

)


+

20





log






(
900
)









=



27.2





dB










Thus, the received power is calculated as:












Received





antenna





power






(
dB
)


=




20





log






(

transmit





power

)


-

free





space





loss








=




20





log






(
4
)


-
27.2







=




-
15






dB










This decibel level converts to approximately 2V in the log-voltage converter. Doubling the distance to 4 feet results in 6 dB less, or −21 dB, which converts to 1.3V. That is approximately 200 mV per foot of distance from the receiver.


Using an isotropic receive antenna, various other factors affect received power level. Examples of these factors include multi-path effects, the type of radio, the distance from a tower, and phone orientation. More specifically, multi-path effects include reflections off of objects causing standing waves. TDMA (time division multiple access) and CDMA (code division multiple access) cell phones have different transmission power levels. As a cell phone moves away from a cell tower, the cell phone increases transmission power, and vice versa. Also, when a cell phone is held vertically or at an angle, the power transmission level changes, as power radiates mainly away from the head, usually in a cardioid shape. All of these factors combine to make received power levels of a driver's cell phone or of a nearby cell phone difficult to distinguish with an isotropic antenna. With a directional antenna, such as an antenna that attenuates driver side-to-side RF power by at least 10 dBi, many of these conflicting power levels are able to be more easily differentiated. Various power conditions are shown in the table below:
















Effect Description
Typical Variability









Phone orientation
+/−6 dB or +/−0.25 volts



Multi-path effects
+/−6 dB or +/−0.25 volts



Distance from a tower
+/−10 dB or +/−0.4 volts



TDMA/CDMA radio
+/−6 dB or +/−0.25 volts



Driver distance from power detector
+/−5 dB or +/−0.2 volts










A minimum power threshold prevents the power detector from measuring all received signals. Instead, the power detector only converts wireless signals of nearby cell phones into voltage waveforms. The minimum power threshold can be a moving or learning threshold. Additionally, two or more thresholds can be used to discriminate between outside cell phones, passenger cell phones, and driver cell phones.


Referring now to FIG. 3, there is shown a directional antenna illustrating in more detail the concepts described above. In FIG. 3, driver cell phone antenna 301 and passenger cell phone antenna 303 are located a distance d1 and d2 from receive antenna 305, respectively. The receive antenna 305 is directional and favors the driver cell phone signal by at least 10 dBi over the passenger cell phone signal. The output voltage Vd is used to differentiate between the driver signal and the passenger signal. Two thresholds, Vdt and Vpt, are calibrated to detect the driver cell phone voltage and passenger cell phone voltage, respectively. For the driver signal, Vd<Vdt, and for the passenger signal, Vd>Vpt. Thus, the directional antenna 305 can be used to determine whether a received signal is from the driver cell phone 301 or the passenger cell phone 303 by comparing Vd to Vdt and Vpt.


Referring now to FIG. 4, there is shown an alternate antenna design. The driver antenna 401 and the passenger antenna 403 broadcast and are received by a first antenna 405 and a second antenna 407, which are identical antennas located some distance apart. The spacing between first antenna 405 and second antenna 407 allows the two antennas, in combination, to determine the location of various received signals. The driver antenna 401 is located a distance d1 from the two antennas 405 and 407, while the passenger antenna 403 is located a distance d2 from the two antennas 405 and 407. The distance d1 is approximately the same between the driver antenna 401 and the first antenna 405 and the driver antenna 401 and the second antenna 407, because two antennas 405 and 407 are located near enough to each other that the difference between the driver antenna 401 and the first antenna 405 and the driver antenna 401 and the second antenna 407 is negligible.


The output waveform 409 is the difference between the voltage from the first antenna V1 and the voltage from the second antenna V2. As described above with respect to FIG. 3, the output voltage Vd is used to differentiate between the driver signal and the passenger signal. Two thresholds, Vdt and Vpt, are calibrated to detect the driver cell phone voltage and passenger cell phone voltage, respectively. For the driver signal, Vd<Vdt, and for the passenger signal, Vd>Vpt.


Referring now to FIG. 5, there is illustrated therein a processor that uses the voltage waveform 209 as shown in FIG. 2 to determine the exact cell phone usage. In FIG. 5, the input voltage Vd is passed through a low pass filter 501 to a 10-12 bit ADC 503 and a comparator 505. By waveform analysis, a voltage trigger level is created by a 10-12 bit DAC 507 and is passed to a comparator trigger level input 509. The processor may be an FPGA, ASIC, or other logic device, as is known in the art.


In more detail, an input voltage Vd, in the form of pulses, is passed through a low pass filter 501, e.g., a 2nd order Sallen-Key with fc=5 KHz. The voltage waveform Vd as described above of approximately 4 mV per 0.1 dB, ranges from 0.2V or −60 dB to 2.4V or −5 dB. The waveform Vd is passed into comparator 505, and the transitions crossing the comparator trigger level create interrupts on both positive and negative edge crossings. The time between the positive and negative crossing interrupts is the pulse duration. During each active pulse duration, the ADC 503 measures the average pulse amplitude. The average amplitude is used for differentiation between the driver, passenger, and other nearby cell phone signals. The average amplitude is also used for identification of amplitude variations from phone proximity, orientation, and multi-path.


Using a comparator and state machines with stored memory, a table lookup, digital signal processing, neural network processing, or other method, the processor determines whether the voltage waveform indicates a voice call, a text message, internet browsing, Bluetooth activity, or other wireless activity. The processor also uses state-machine confidence counters to determine confidences about waveform determinations. Confidence counter thresholds, which may be set at any level and may be adaptive, represent a “high likeness” level of detection of a certain type or types of waveform. Confidence counters are weighted toward the “no confidence” or “zero confidence” state. Confidence counter outcomes map, in combination with each other, to waveform identification tables. Additionally, over time, the processor learns the particular cell phone voltage pattern and movement.


Referring now to FIG. 6, there is illustrated a state flow diagram of a preferred embodiment of the state machine concept described above. The processor of FIG. 5 measures pulse duration and pulse amplitude. The sampled waveform 601 is then compared to look-up tables 603. The likeliest pulse type 605 is determined by the measured pulse width time, inter-pulse times, and by feedback from other processes. The likeliest pulse group type 607 is determined by timing behind groups of likeliest pulse types 605 and by feedback from other processes. The likeliest pulse group collection type 609 is determined by timing behind a collection of pulse group types 607 and by feedback from other processes. The likeliest waveform decision 611 is determined by the likeliest types that were determined by the other processes. All of these processors include comparator trigger level calculations.


The processor can store local data relating to cell phone usage, as well as store a library of known cell phone wireless signals converted to voltage waveforms. Additionally, the processor may communicate with a remote server in order to update a library of known cell phone wireless signals converted to voltage waveforms. The server may also store information relating to measured cell phone usage, backing up the memory of the processor or replacing the memory. In this way, over time, the library of stored voltage waveforms can be adapted or updated.


Power detector 205 of FIG. 2 can include additional sensors or communication interfaces to receive additional data. For example, power detector 205 may include a directional microphone to monitor voice sounds and other sounds, in order to more precisely determine location and user of a mobile phone. Power detector 205 may additionally include a motion sensor, such as a global positioning (GPS) device, accelerometer, or other motion sensing device, that monitors speed and/or location of the power detector. The speed and/or location may be stored and correlated with the voltage waveforms indicative of mobile phone usage.


Power detector 205 of FIG. 2 can also be used to detect wireless signals emitted from a transmitter attached to the vehicle rather than held by a driver or passenger. Some vehicles include docking or mounting stations for mobile devices and control the operation of the mobile device upon receiving directions from the driver or passenger.


The power detector 205, as well as additional sensors, and power supply 207, voltage output 209, and other components are preferably located in a single housing, or may be located in multiple housings. The single housing may be preferably affixed to the windshield of a vehicle, or may be located above or below the driver.


Indirect Mobile Device Usage Detection


In some implementations, mobile phone usage may be determined indirectly. A camera sensor similar to a blink rate sensor may be used to look for a driver's hand to either ear. Another embodiment for detecting cell phone use would be to monitor the vehicle's average path deviation per a given time and/or distance interval using a high precision positioning system, i.e., DGPS, WAAS, RTK or other equivalent. The positioning system would be used to compare normal driving without communication use to the driving performance while using a communication device, e.g., monitor weaving and lane departure.


Determining Passenger Numbers


Referring again to FIG. 2, the power detector 205 can be used to measure two or more wireless signals and convert the signals to voltage waveforms. Using the voltage waveforms, the number of nearby cell phones can be determined.


Referring now to FIG. 7, there is shown a flowchart describing an overall method of using the system described above with reference to FIGS. 2-6. Initially, an antenna receives wireless signals 701. Then the wireless signals are converted to a voltage waveform 703. Next, the voltage waveform is analyzed to determine the location and number of discrete wireless signals 705. Finally, a number of mobile phone users in a vehicle is determined using the analyzed voltage waveform 707.


Additionally, other sensors can be used to determine number of passengers in a vehicle. Each vehicle includes a sensing bus that communicates with various vehicle sensors, including a seat belt sensor, a weight sensor in a passenger seat used for air bag deployment, and other sensors.


The power detector 205 can also store passenger number data and correlate this information with speed and/or location data received from the motion sensor. In this way, a vehicle with a restricted number of passengers, such as a vehicle driven by a teenage or a vehicle driven by a driver in fleet with passenger restrictions, can be monitored.


Determining Waveforms


Received wireless signals converted into waveforms distinctly show the type of cell phone usage. Measured voltage waveforms are shown below in FIGS. 8-29, illustrating various voltage waveforms in TDMA, GSM, and CDMA wireless systems under various circumstances, including received and transmitted calls, answered and unanswered calls, text messaging, internet browsing, and Bluetooth activity. Voltage waveforms for other frequency wireless signals including satellite band, handheld radios, etc., may also be measured.


In FIGS. 8-29, a Q-wave antenna tuned to 1370 MHz, midway between 800 and 1900 MHz, is connected with an SMA connector to a Linear Tech 748A RF power log-voltage detector powered by a 5V power supply. The power detector has a 0 to 60 dB dynamic range, which corresponds to a minimum measurable signal level of −60 dB converted to 0.2 volts and a maximum measurable level of 0 dB converted to 3 volts.


As shown in FIGS. 8-29, answered and unanswered received calls have different waveforms, while data waveforms for text messages and internet browsing are distinguishable from voice calls. Thus, by comparing received voltage waveforms to known voltage waveforms, exact mobile phone usage can be determined.


Referring now to FIGS. 8 and 9, the waveform for a TDMA voice call is shown. In FIG. 8, a received voice call has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is approximately 4.5 ms between short peaks and approximately 9 ms between tall peaks. In FIG. 9, a transmitted voice call has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is approximately 4.5 ms between short peaks and approximately 9 ms between tall peaks.


Referring now to FIGS. 10 and 11, the waveform for a TDMA received voice call is shown. In FIG. 10, a received but not answered voice call has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a regular non-bursting pattern with approximately 4.5 ms between short peaks and approximately 9 ms between tall peaks. In FIG. 11, a received and answered voice call has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a coarse bursting pattern with approximately 4.5 ms between short peaks and approximately 9 ms between tall peaks.


Referring now to FIGS. 12 and 13, the waveform for a TDMA transmitted voice call is shown. In FIG. 12, a transmitted voice call has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a fine bursting pattern with approximately 4.5 ms between short peaks and approximately 9 ms between tall peaks. In FIG. 13, a transmitted voice call has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a fine bursting pattern with approximately 4.5 ms between short peaks and approximately 9 ms between tall peaks.


Referring now to FIGS. 14-18, the waveform for a TDMA SMS text message is shown. In FIG. 14, a sent text message has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a coarse bursting pattern with approximately 4.5 ms between short peaks and approximately 9 ms between tall peaks. In FIG. 15, a sent text message has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a coarse bursting pattern with approximately 4.5 ms between short peaks and approximately 9 ms between tall peaks. In FIG. 16, a received text message has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a coarse bursting pattern with approximately 4.5 ms between short peaks and approximately 9 ms between tall peaks. In FIG. 17, a sent text message has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a coarse bursting pattern with approximately 4.5 ms between short peaks and approximately 9 ms between tall peaks. In FIG. 18, a sent text message has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a coarse bursting pattern with approximately 4.5 ms between short peaks and approximately 9 ms between tall peaks.


Referring now to FIGS. 19-21, the waveform for a CDMA text message is shown. In FIG. 19, a sent text message has a voltage above the threshold, with voltage peaks. There is a coarse bursting pattern with approximately 3 ms between peaks. In FIG. 20, a sent text message has a voltage above the threshold, with voltage peaks. There is a coarse bursting pattern with approximately 3 ms between peaks. In FIG. 21, a sent text message has a voltage above the threshold, with voltage peaks. There is a coarse bursting pattern with approximately 3 ms between peaks.


Referring now to FIGS. 22-26, the waveform for a TDMA data transmission during internet browsing is shown. In FIG. 22, a sent text message has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a coarse bursting pattern with approximately 4.5 ms between large peaks. In FIG. 23, a sent text message has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a coarse bursting pattern with approximately 4.5 ms between large peaks. In FIG. 24, a sent text message has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a coarse bursting pattern with approximately 4.5 ms between large peaks. In FIG. 25, a sent text message has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a coarse bursting pattern with approximately 4.5 ms between large peaks. In FIG. 26, a sent text message has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a coarse bursting pattern with approximately 4.5 ms between large peaks.


Referring now to FIG. 27, there is shown a TDMA waveform when a phone is used at 90° and at 0° to the sensing antenna. As shown, there is a 5-10 dB amplitude variation in signal strength, translated to a voltage change, depending upon the orientation of the mobile phone to the sensing antenna.


Referring now to FIGS. 28 and 29, the waveform for Bluetooth discovery mode is shown. In FIG. 28, the Bluetooth discovery mode has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a bursting pattern with 4-5 large peaks every 40 ms with approximately 5 ms between peaks. In FIG. 29, the Bluetooth discovery mode has a voltage above the threshold, with short voltage peaks and tall voltage peaks. There is a bursting pattern with 4-5 large peaks every 40 ms with approximately 5 ms between peaks.


While various embodiments of the present invention have been described above, it should be understood that they have been presented by way of example only and not limitation. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined in the appended claims. Thus, the breadth and scope of the present invention should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents.

Claims
  • 1. A system installed in a vehicle configured to detect use of a cell phone by one or more persons during operation of the vehicle comprising: an antenna for receiving RF signals from one or more cell phones when used by at least one of a driver of the vehicle, and a passenger in the vehicle;a power detector coupled to the antenna, the power detector being configured to measure received RF signals from the antenna that are above a defined minimum power threshold, the power detector outputting a voltage waveform that corresponds to the received RF signals above the defined minimum power threshold; andsignal processing circuitry that receives each voltage waveform output by the power detector and analyzes each output voltage waveform to determine: received power which corresponds to the received RF signals for which the voltage waveform is output by the power detector;when the received power for a received RF signal is above a first threshold, identifying the received RF signal as a driver signal; andwhen the received power for the received RF signal is above a second threshold, identifying the received RF signal as a passenger signal.
  • 2. The system of claim 1, further comprising: a low pass filter coupled to the power detector that receives as an input each voltage waveform output by the power detector, the low pass filter being configured to screen out frequencies other than quad-band frequencies used by the one or more cell phones, and to output a filtered voltage waveform for each measured signal output by the power detector;an analog to digital convert (ADC) that receives each filtered signal from the low pass filter and converts the filtered signal to a digital waveform that corresponds to each voltage waveform output by the power detector; anda digital processor that receives each digital waveform output from the ADC and analyzes each digital waveform.
  • 3. The system of claim 2, wherein the digital processor that receives each digital waveform output from the ADC analyzes each digital waveform to determine (i) a value that represents the received power which corresponds to each RF signal for which a voltage waveform is output by the power detector;(ii) when the value for the received power for an RF signal is above a first threshold value, identifying the RF signal for that value as a driver signal; and(iii) when the value for the received power for the RF signal is above a second threshold value, identifying the RF signal for that value as a passenger signal.
  • 4. The system of claim 3, further comprising system memory which contains data storage of information used to identify certain waveform characteristics that determine one or more types of cell phone use, including at least sending or receiving a voice call, sending or receiving text messages, or sending or receiving web browsing information, or using a hand-free connection to the cell phone, andwherein the digital processor that receives each digital waveform output from the ADC comprises a comparator that analyzes each digital waveform using the stored information from system memory used to identify the certain waveform characteristics for types of cell phone use, thus determining for an RF signal for which a voltage waveform is output by the power detector a type of use being made for a cell phone for that RF signal.
  • 5. The system of claim 4, wherein the comparator that analyzes each digital waveform uses a bursting pattern to characterize the nature of the waveform as belonging to a particular type of use.
  • 6. The system of claim 2, further comprising system memory which contains data storage of information used to identify certain waveform characteristics that determine one or more types of cell phone use, including at least sending or receiving a voice call, sending or receiving text messages, or sending or receiving web browsing information, or using a hand-free connection to the cell phone, andwherein the digital processor that receives each digital waveform output from the ADC comprises a comparator that analyzes each digital waveform using the stored information from system memory used to identify the certain waveform characteristics for types of cell phone use, thus determining for an RF signal for which a voltage waveform is output by the power detector a type of use being made for a cell phone for that RF signal.
  • 7. The system of claim 2, further comprising an additional sensor in communication with the digital processor.
  • 8. The system of claim 7, wherein the additional sensor includes a directional microphone and the digital processor receives directional sound data from the additional sensor and correlates the directional sound data with the detected use of a cell phone.
  • 9. The system of claim 7, wherein the additional sensor includes a seat belt sensor and the digital processor receives seat belt sensor data from the additional sensor and correlates the seat belt sensor data with the detected use of a cell phone.
  • 10. The system of claim 7, wherein the additional sensor includes a weight sensor in a passenger seat and the digital processor receives data from the additional sensor and correlates the data with the detected use of a cell phone.
  • 11. The system of claim 1 further comprising: a second antenna for receiving RF signals from one or more cell phones when used by one or more of a driver of a vehicle, or a passenger in the vehicle;a second power detector coupled to the second antenna, the power detector being configured to measure all received RF signals from the antenna that are above a defined minimum power threshold, the power detector outputting a voltage waveform that corresponds to each RF signal above the defined minimum power threshold; andsignal processing circuitry that receives each voltage waveform output by the first and second power detectors and analyzes each output voltage waveform to determine: the received power which corresponds to each RF signal for which a voltage waveform is output by the first and second power detectors,the difference between the received power for each RF signal for the first and second power detectors, andwhen the difference from the first and second power detectors for the received power for an RF signal is negligible, identifying the RF signal for that value as a driver signal, andwhen the difference from the first and second power detectors for the received power for an RF signal is not negligible, identifying the RF signal for that value as a passenger signal.
  • 12. The system of claim 1 wherein the power detector further comprises a motion sensor that monitors at least one of speed or location of the power detector within the vehicle, to provide speed or location correlation with a detected use of a cell phone.
  • 13. The system of claim 11 wherein the power detector further comprises a motion sensor that monitors at least one of speed or location of the power detector within the vehicle, to provide speed or location correlation with a detected use of a cell phone.
  • 14. The system of claim 13, wherein the motion sensor is a GPS sensor.
  • 15. A method of detecting use of a cell phone by one or more persons during operation of a vehicle comprising: receiving at an antenna RF signals from any of a plurality of cell phones when used by at least one of a driver of the vehicle, and a passenger in the vehicle;measuring at a power detector received RF signals from the antenna that are above a defined minimum power threshold, the power detector outputting a voltage waveform that corresponds to the received RF signals above the defined minimum power threshold; andanalyzing with signal processing circuitry each voltage waveform output by the power detector to determine: received power which corresponds to the received RF signals for which the voltage waveform is output by the power detector;when the received power for a received RF signal is above a first threshold, identifying the received RF signal as a driver signal; andwhen the received power for the received RF signal is above a second threshold, identifying the received RF signal as a passenger signal.
  • 16. The method of claim 15, further comprising: filtering with a low pass filter coupled to the power detector each voltage waveform output by the power detector, the low pass filter screening out frequencies other than quad-band frequencies used by the one or more cell phones, and outputting a filtered voltage waveform for each measured signal output by the power detector;converting with an analog to digital converter (ADC) each filtered signal from the low pass filter to a digital waveform that corresponds to each voltage waveform output by the power detector; andanalyzing with a digital processor each digital waveform output from the ADC.
  • 17. The method of claim 16, wherein analyzing with the digital processor each digital waveform comprises determining (i) a value that represents the received power which corresponds to each RF signal for which a voltage waveform is output by the power detector;(ii) when the value for the received power for an RF signal is above a first threshold value, identifying the RF signal for that value as a driver signal; and(iii) when the value for the received power for the RF signal is above a second threshold value, identifying the RF signal for that value as a passenger signal.
  • 18. The method of claim 17, further comprising storing in system memory data representing information used to identify certain waveform characteristics that determine one or more types of cell phone use, including at least sending or receiving a voice call, sending or receiving text messages, or sending or receiving web browsing information, or using a hand-free connection to the cell phone, andwherein analyzing with the digital processor each digital waveform comprises determining using the stored information from system memory to identify certain waveform characteristics, thus determining for an RF signal for which a voltage waveform is output by the power detector a type of use being made for a cell phone for that RF signal.
  • 19. The method of claim 18 wherein the power detector further comprises a motion sensor that monitors at least one of speed or location of the power detector within the vehicle, and wherein the method further comprises providing speed or location correlation with a detected use of a cell phone.
  • 20. The method of claim 16, further comprising storing in system memory data representing information used to identify certain waveform characteristics that determine one or more types of cell phone use, including at least sending or receiving a voice call, sending or receiving text messages, or sending or receiving web browsing information, or using a hand-free connection to the cell phone, andwherein analyzing with the digital processor each digital waveform comprises determining using the stored information from system memory to identify certain waveform characteristics, thus determining for an RF signal for which a voltage waveform is output by the power detector a type of use being made for a cell phone for that RF signal.
  • 21. The method of claim 20, wherein the processor includes a comparator, and wherein the method further comprises analyzing each digital waveform with the comparator by using a bursting pattern to characterize the nature of the waveform as belonging to a particular type of use by comparing it to data stored in system memory that represents identification of certain waveform characteristics depending on the type cell phone use.
  • 22. The method of claim 15 further comprising: receiving at a second antenna RF signals from one or more cell phones when used by one or more of a driver of a vehicle, or a passenger in the vehicle;measuring at a second power detector all received RF signals from the second antenna that are above a defined minimum power threshold, and outputting from the second power detector a voltage waveform that corresponds to each RF signal above the defined minimum power threshold; andprocessing with signal processing circuitry each voltage waveform output by the first and second power detectors and analyzing each output voltage waveform to determine: the received power which corresponds to each RF signal for which a voltage waveform is output by the first and second power detectors,the difference between the received power for each RF signal for the first and second power detectors, andwhen the difference from the first and second power detectors for the received power for an RF signal is negligible, identifying the RF signal for that value as a driver signal, andwhen the difference from the first and second power detectors for the received power for an RF signal is not negligible, identifying the RF signal for that value as a passenger signal.
  • 23. The method of claim 15 wherein the power detector further comprises a motion sensor that monitors at least one of speed or location of the power detector within the vehicle, and wherein the method further comprises providing speed or location correlation with a detected use of a cell phone.
  • 24. The method of claim 15, wherein the power detector further comprises an additional sensor that includes a directional microphone and wherein the digital processor receives directional sound data from the additional sensor, and wherein the method further comprises correlating the directional sound data with the detected use of a cell phone.
  • 25. The method of claim 15, wherein the power detector further comprises an additional sensor that includes a seat belt sensor and wherein the digital processor receives seat belt sensor data from the additional sensor, and wherein the method further comprises correlating the seat belt sensor data with the detected use of a cell phone.
  • 26. The method of claim 15, wherein the power detector further comprises an additional sensor that includes a weight sensor in a passenger seat and the digital processor receives data from the additional sensor, and wherein the method further comprises correlating the data with the detected use of a cell phone.
  • 27. The method of claim 15 wherein detected cell phone use by a driver of the vehicle causes a notification to be sent to the driver.
  • 28. The method of claim 15 wherein detected cell phone use by a driver of the vehicle causes a notification to be sent to a person other than the driver.
  • 29. A hardware storage device containing computer executable instructions which cause one or more processors to implement a method for detecting use of a cell phone by one or more persons during operation of a vehicle, and wherein the implemented method comprises: analyzing with a digital processor each voltage waveform output by a power detector to determine received power which corresponds to each detected RF signals from one or more cell phones in the vehicle, in order to determine:(i) a value that represents the received power which corresponds to the each detected RF signals for which a voltage waveform is output by the power detector;(ii) when the value for the received power for one of the detected RF signals is above a first threshold, identifying the one of the detected RF signals as a driver signal; and(iii) when the value for the received power for the one of the detected RF signals is above a second threshold, identifying the one of the detected RF signals as a passenger signal.
  • 30. The hardware storage device of claim of claim 29, wherein the computer executable instructions causing the one or more processors to implement the method, further include as part of the implemented method: storing in system memory data representing information used to identify certain waveform characteristics that determine one or more types of cell phone use, including at least sending or receiving a voice call, sending or receiving text messages, or sending or receiving web browsing information, or using a hand-free connection to the cell phone, andwherein analyzing with the digital processor each digital waveform comprises using the stored information from system memory to identify certain waveform characteristics, thus determining for an RF signal for which a voltage waveform is output by the power detector a type of use being made for a cell phone for that RF signal.
US Referenced Citations (505)
Number Name Date Kind
3975708 Lusk Aug 1976 A
4369427 Drebinger et al. Jan 1983 A
4395624 Wartski Jul 1983 A
4419654 Funk Dec 1983 A
4458535 Juergens Jul 1984 A
4785280 Fubini Nov 1988 A
4843578 Wade Jun 1989 A
4926417 Futami May 1990 A
4939652 Steiner Jul 1990 A
5032821 Domanico Jul 1991 A
5074144 Krofchalk et al. Dec 1991 A
5119504 Durboraw, III Jun 1992 A
5223844 Mansell et al. Jun 1993 A
5225842 Brown et al. Jul 1993 A
5266922 Smith et al. Nov 1993 A
5303163 Ebaugh et al. Apr 1994 A
5305214 Komatsu Apr 1994 A
5309139 Austin May 1994 A
5311197 Sorden et al. May 1994 A
5325082 Rodriguez Jun 1994 A
5347260 Ginzel Sep 1994 A
5359528 Haendel Oct 1994 A
5365114 Tsurushima Nov 1994 A
5365451 Wang et al. Nov 1994 A
5394136 Lammers Feb 1995 A
5400018 Scholl Mar 1995 A
5414432 Penny, Jr. et al. May 1995 A
5422624 Smith Jun 1995 A
5424584 Matsuda Jun 1995 A
5430432 Camhi Jul 1995 A
5436612 Aduddell Jul 1995 A
5436837 Gerstung Jul 1995 A
5446659 Yamawaki Aug 1995 A
5453939 Hoffman Sep 1995 A
5457439 Kuhn Oct 1995 A
5475597 Buck Dec 1995 A
5485161 Vaughn Jan 1996 A
5499182 Ousborne Mar 1996 A
5521579 Bernhard May 1996 A
5521580 Kaneko May 1996 A
5525960 McCall Jun 1996 A
5546305 Kondo Aug 1996 A
5548273 Nicol Aug 1996 A
5581464 Woll Dec 1996 A
5586130 Doyle Dec 1996 A
5600558 Mearek Feb 1997 A
5612875 Haendel Mar 1997 A
5625337 Medawar Apr 1997 A
5642284 Parupalli Jun 1997 A
5648755 Yagihashi Jul 1997 A
5659289 Zonkoski Aug 1997 A
5689067 Klein Nov 1997 A
5708417 Tallman Jan 1998 A
5717374 Smith Feb 1998 A
5719771 Buck Feb 1998 A
5723768 Ammon Mar 1998 A
5740548 Hudgens Apr 1998 A
5742915 Stafford Apr 1998 A
5751245 Janky et al. May 1998 A
5764139 Nojima Jun 1998 A
5767767 Lima Jun 1998 A
5777580 Janky et al. Jul 1998 A
5795997 Gittins Aug 1998 A
5797134 McMillan et al. Aug 1998 A
5801618 Jenkins Sep 1998 A
5801948 Wood Sep 1998 A
5815071 Doyle Sep 1998 A
5825283 Camhi Oct 1998 A
5825284 Dunwoody Oct 1998 A
5844475 Horie Dec 1998 A
5847271 Poublon Dec 1998 A
5862500 Goodwin Jan 1999 A
5867093 Dodd Feb 1999 A
5877678 Donoho Mar 1999 A
5880674 Ufkes Mar 1999 A
5880958 Helms et al. Mar 1999 A
5883594 Lau Mar 1999 A
5892434 Carlson Apr 1999 A
5907277 Tokunaga May 1999 A
5914654 Smith Jun 1999 A
5918180 Dimino Jun 1999 A
5926087 Busch Jul 1999 A
5928291 Jenkins et al. Jul 1999 A
5941915 Federle et al. Aug 1999 A
5945919 Trask Aug 1999 A
5949330 Hoffman Sep 1999 A
5949331 Schofield Sep 1999 A
5954781 Slepian Sep 1999 A
5955942 Slifkin Sep 1999 A
5957986 Coverdill Sep 1999 A
5964816 Kincaid Oct 1999 A
5969600 Tanguay Oct 1999 A
5974356 Doyle et al. Oct 1999 A
5978737 Pawlowski Nov 1999 A
5982278 Cuvelier Nov 1999 A
5987976 Sarangapani Nov 1999 A
5999125 Kurby Dec 1999 A
6002327 Boesch Dec 1999 A
6008724 Thompson Dec 1999 A
6018293 Smith Jan 2000 A
6026292 Coppinger et al. Feb 2000 A
6028508 Mason Feb 2000 A
6028510 Tamam Feb 2000 A
6037861 Ying Mar 2000 A
6037862 Ying Mar 2000 A
6038496 Dobler Mar 2000 A
6044315 Honeck Mar 2000 A
6059066 Lary May 2000 A
6064886 Perez et al. May 2000 A
6064928 Wilson May 2000 A
6064970 McMillan et al. May 2000 A
6067008 Smith May 2000 A
6067009 Hozuka May 2000 A
6072388 Kyrtsos Jun 2000 A
6073007 Doyle Jun 2000 A
6075458 Ladner et al. Jun 2000 A
6078853 Ebner Jun 2000 A
6081188 Kutlucinar Jun 2000 A
6084870 Wooten et al. Jul 2000 A
6094149 Wilson Jul 2000 A
6098048 Dashefsky Aug 2000 A
6100792 Ogino Aug 2000 A
6104282 Fragoso Aug 2000 A
6108591 Segal et al. Aug 2000 A
6121922 Mohan Sep 2000 A
6130608 McKeown Oct 2000 A
6131067 Girerd et al. Oct 2000 A
6133827 Alvey Oct 2000 A
6141610 Rothert Oct 2000 A
6147598 Murphy Nov 2000 A
6172602 Hasfjord Jan 2001 B1
6178374 Mohlenkamp et al. Jan 2001 B1
6184784 Shibuya Feb 2001 B1
6185501 Smith Feb 2001 B1
6188315 Herbert et al. Feb 2001 B1
6195015 Jacobs et al. Feb 2001 B1
6198995 Settles Mar 2001 B1
6204756 Senyk Mar 2001 B1
6204757 Evans Mar 2001 B1
6208240 Ledesma Mar 2001 B1
6212455 Weaver Apr 2001 B1
6216066 Goebel Apr 2001 B1
6222458 Harris Apr 2001 B1
6225898 Kamiya May 2001 B1
6227862 Harkness May 2001 B1
6229438 Kutlucinar May 2001 B1
6232873 Dilz May 2001 B1
6246933 Bague Jun 2001 B1
6247360 Anderson Jun 2001 B1
6249219 Perez Jun 2001 B1
6253129 Jenkins et al. Jun 2001 B1
6255892 Gartner Jul 2001 B1
6255939 Roth Jul 2001 B1
6256558 Sugiura et al. Jul 2001 B1
6262658 O'Connor Jul 2001 B1
6265989 Taylor Jul 2001 B1
6266588 McClellan Jul 2001 B1
6278361 Magiawala Aug 2001 B1
6285931 Hattori Sep 2001 B1
6289332 Menig Sep 2001 B2
6294988 Shomura Sep 2001 B1
6294989 Schofield Sep 2001 B1
6295492 Lang Sep 2001 B1
6297768 Allen, Jr. Oct 2001 B1
6301533 Markow Oct 2001 B1
6306063 Horgan et al. Oct 2001 B1
6308120 Good Oct 2001 B1
6308134 Croyle et al. Oct 2001 B1
6313742 Larson Nov 2001 B1
6320497 Fukumoto Nov 2001 B1
6331825 Ladner et al. Dec 2001 B1
6333686 Waltzer Dec 2001 B1
6337653 Buchler Jan 2002 B1
6339739 Folke Jan 2002 B1
6339745 Novik Jan 2002 B1
6344805 Yasui Feb 2002 B1
6351211 Bussard Feb 2002 B1
6353778 Brown Mar 2002 B1
6356188 Meyers Mar 2002 B1
6356822 Diaz Mar 2002 B1
6356833 Jeon Mar 2002 B2
6356836 Adolph Mar 2002 B1
6359554 Skibinski Mar 2002 B1
6362730 Razavi Mar 2002 B2
6362734 McQuade Mar 2002 B1
6366199 Osborn Apr 2002 B1
6378959 Lesesky Apr 2002 B2
6389340 Rayner May 2002 B1
6393348 Ziegler May 2002 B1
6404329 Hsu Jun 2002 B1
6405112 Rayner Jun 2002 B1
6405128 Bechtolsheim et al. Jun 2002 B1
6415226 Kozak Jul 2002 B1
6424268 Isonaga Jul 2002 B1
6427687 Kirk Aug 2002 B1
6430488 Goldman Aug 2002 B1
6433681 Foo Aug 2002 B1
6441732 Laitsaari Aug 2002 B1
6449540 Rayner Sep 2002 B1
6459367 Green Oct 2002 B1
6459369 Wang Oct 2002 B1
6459961 Obradovich Oct 2002 B1
6459969 Bates Oct 2002 B1
6462675 Humphrey Oct 2002 B1
6472979 Schofield Oct 2002 B2
6476763 Allen, Jr. Nov 2002 B2
6480106 Crombez Nov 2002 B1
6484035 Allen, Jr. Nov 2002 B2
6484091 Shibata Nov 2002 B2
6493650 Rodgers Dec 2002 B1
6512969 Wang Jan 2003 B1
6515596 Awada Feb 2003 B2
6519512 Haas Feb 2003 B1
6525672 Chainer Feb 2003 B2
6526341 Bird et al. Feb 2003 B1
6529159 Fan et al. Mar 2003 B1
6535116 Zhou Mar 2003 B1
6542074 Tharman Apr 2003 B1
6542794 Obradovich Apr 2003 B2
6549834 McClellan Apr 2003 B2
6552682 Fan Apr 2003 B1
6556905 Mittelsteadt Apr 2003 B1
6559769 Anthony May 2003 B2
6564126 Lin May 2003 B1
6567000 Slifkin May 2003 B2
6571168 Murphy May 2003 B1
6577946 Myr Jun 2003 B2
6587759 Obradovich Jul 2003 B2
6594579 Lowrey Jul 2003 B1
6599243 Woltermann Jul 2003 B2
6600985 Weaver Jul 2003 B2
6604033 Banet Aug 2003 B1
6609063 Bender et al. Aug 2003 B1
6609064 Dean Aug 2003 B1
6611740 Lowrey Aug 2003 B2
6611755 Coffee Aug 2003 B1
6622085 Amita et al. Sep 2003 B1
6629029 Giles Sep 2003 B1
6630884 Shanmugham Oct 2003 B1
6631322 Arthur et al. Oct 2003 B1
6636790 Lightner Oct 2003 B1
6639512 Lee Oct 2003 B1
6643578 Levine Nov 2003 B2
6651001 Apsell Nov 2003 B2
6654682 Kane et al. Nov 2003 B2
6657540 Knapp Dec 2003 B2
6662013 Takiguchi et al. Dec 2003 B2
6662141 Kaub Dec 2003 B2
6664922 Fan Dec 2003 B1
6665613 Duvall Dec 2003 B2
6674362 Yoshioka Jan 2004 B2
6675085 Straub Jan 2004 B2
6677854 Dix Jan 2004 B2
6678612 Khawam Jan 2004 B1
6696932 Skibinski Feb 2004 B2
6701234 Vogelsang Mar 2004 B1
6703925 Steffel Mar 2004 B2
6714894 Tobey et al. Mar 2004 B1
6718235 Borugian Apr 2004 B1
6718239 Rayner Apr 2004 B2
6727809 Smith Apr 2004 B1
6728542 Meda Apr 2004 B2
6728605 Lash Apr 2004 B2
6732031 Lightner May 2004 B1
6732032 Banet May 2004 B1
6737962 Mayor May 2004 B2
6741169 Magiawala May 2004 B2
6741170 Alrabady May 2004 B2
6745153 White Jun 2004 B2
6748322 Fernandez Jun 2004 B1
6750761 Newman Jun 2004 B1
6750762 Porter Jun 2004 B1
6756916 Yanai Jun 2004 B2
6759952 Dunbridge Jul 2004 B2
6766244 Obata et al. Jul 2004 B2
6768448 Farmer Jul 2004 B2
6775602 Gordon Aug 2004 B2
6778068 Wolfe Aug 2004 B2
6778885 Agashe et al. Aug 2004 B2
6784793 Gagnon Aug 2004 B2
6784832 Knockeart et al. Aug 2004 B2
6788196 Ueda Sep 2004 B2
6788207 Wilkerson Sep 2004 B2
6792339 Basson Sep 2004 B2
6795017 Puranik et al. Sep 2004 B1
6798354 Schuessler Sep 2004 B2
6803854 Adams et al. Oct 2004 B1
6807481 Gastelum Oct 2004 B1
6810321 Cook Oct 2004 B1
6813549 Good Nov 2004 B2
6819236 Kawai Nov 2004 B2
6822557 Weber Nov 2004 B1
6832141 Skeen Dec 2004 B2
6845314 Fosseen Jan 2005 B2
6845316 Yates Jan 2005 B2
6845317 Craine Jan 2005 B2
6847871 Malik et al. Jan 2005 B2
6847872 Bodin Jan 2005 B2
6847873 Li Jan 2005 B1
6847887 Casino Jan 2005 B1
6850841 Casino Feb 2005 B1
6859039 Horie Feb 2005 B2
6859695 Klausner Feb 2005 B2
6865457 Mittelsteadt Mar 2005 B1
6867733 Sandhu et al. Mar 2005 B2
6868386 Henderson Mar 2005 B1
6870469 Ueda Mar 2005 B2
6873253 Veziris Mar 2005 B2
6873261 Anthony Mar 2005 B2
6879894 Lightner Apr 2005 B1
6885293 Okumura Apr 2005 B2
6892131 Coffee May 2005 B2
6894606 Forbes et al. May 2005 B2
6895332 King May 2005 B2
6909398 Knockeart et al. Jun 2005 B2
6909947 Douros et al. Jun 2005 B2
6914523 Munch Jul 2005 B2
6922133 Wolfe Jul 2005 B2
6922571 Kinoshita Jul 2005 B1
6922616 Obradovich Jul 2005 B2
6922622 Dulin Jul 2005 B2
6925425 Remboski Aug 2005 B2
6928348 Lightner Aug 2005 B1
6937162 Tokitsu Aug 2005 B2
6950013 Scaman Sep 2005 B2
6954140 Holler Oct 2005 B2
6958976 Kikkawa Oct 2005 B2
6965827 Wolfson Nov 2005 B1
6968311 Knockeart et al. Nov 2005 B2
6970075 Cherouny Nov 2005 B2
6970783 Knockeart et al. Nov 2005 B2
6972669 Saito Dec 2005 B2
6980131 Taylor Dec 2005 B1
6981565 Gleacher Jan 2006 B2
6982636 Bennie Jan 2006 B1
6983200 Bodin Jan 2006 B2
6988033 Lowrey Jan 2006 B1
6988034 Marlatt et al. Jan 2006 B1
6989739 Li Jan 2006 B2
7002454 Gustafson Feb 2006 B1
7002579 Olson Feb 2006 B2
7005975 Lehner Feb 2006 B2
7006820 Parker et al. Feb 2006 B1
7019641 Lakshmanan Mar 2006 B1
7023321 Brillon et al. Apr 2006 B2
7023332 Saito Apr 2006 B2
7024318 Fischer Apr 2006 B2
7027808 Wesby Apr 2006 B2
7034705 Yoshioka Apr 2006 B2
7038578 Will May 2006 B2
7042347 Cherouny May 2006 B2
7047114 Rogers May 2006 B1
7049941 Rivera-Cintron May 2006 B2
7054742 Khavakh et al. May 2006 B2
7059689 Lesesky Jun 2006 B2
7065349 Nath et al. Jun 2006 B2
7069126 Bernard Jun 2006 B2
7069134 Williams Jun 2006 B2
7072753 Eberle Jul 2006 B2
7081811 Johnston Jul 2006 B2
7084755 Nord Aug 2006 B1
7088225 Yoshioka Aug 2006 B2
7089116 Smith Aug 2006 B2
7091880 Sorensen Aug 2006 B2
7098812 Hirota Aug 2006 B2
7099750 Miyazawa Aug 2006 B2
7099774 King Aug 2006 B2
7102496 Ernst Sep 2006 B1
7109853 Mattson Sep 2006 B1
7113081 Reichow Sep 2006 B1
7113107 Taylor Sep 2006 B2
7117075 Larschan Oct 2006 B1
7119696 Borugian Oct 2006 B2
7124027 Ernst Oct 2006 B1
7124088 Bauer et al. Oct 2006 B2
7129825 Weber Oct 2006 B2
7132934 Allison Nov 2006 B2
7132937 Lu Nov 2006 B2
7132938 Suzuki Nov 2006 B2
7133755 Salman Nov 2006 B2
7135916 Schmidt Nov 2006 B2
7135983 Filippov Nov 2006 B2
7139661 Holze Nov 2006 B2
7145442 Wai Dec 2006 B1
7149206 Pruzan Dec 2006 B2
7155259 Bauchot et al. Dec 2006 B2
7155321 Bromley et al. Dec 2006 B2
7161473 Hoshal Jan 2007 B2
7164986 Humphries Jan 2007 B2
7170390 Quiñones Jan 2007 B2
7170400 Cowelchuk Jan 2007 B2
7174243 Lightner Feb 2007 B1
7180407 Guo Feb 2007 B1
7180409 Brey Feb 2007 B2
7187271 Nagata Mar 2007 B2
7196629 Ruoss Mar 2007 B2
7197500 Israni et al. Mar 2007 B1
7216022 Kynast et al. May 2007 B2
7216035 Hörtner May 2007 B2
7218211 Ho May 2007 B2
7222009 Hijikata May 2007 B2
7225065 Hunt May 2007 B1
7228211 Lowrey Jun 2007 B1
7233235 Pavlish Jun 2007 B2
7236862 Kanno Jun 2007 B2
7239948 Nimmo Jul 2007 B2
7256686 Koutsky Aug 2007 B2
7256700 Ruocco Aug 2007 B1
7256702 Isaacs Aug 2007 B2
7260497 Watabe Aug 2007 B2
RE39845 Hasfjord Sep 2007 E
7269507 Cayford Sep 2007 B2
7269530 Lin Sep 2007 B1
7271716 Nou Sep 2007 B2
7273172 Olsen Sep 2007 B2
7280046 Berg Oct 2007 B2
7283904 Benjamin Oct 2007 B2
7286917 Hawkins Oct 2007 B2
7286929 Staton Oct 2007 B2
7289024 Sumcad Oct 2007 B2
7289035 Nathan Oct 2007 B2
7292152 Torkkola Nov 2007 B2
7292159 Culpepper Nov 2007 B2
7298248 Finley Nov 2007 B2
7298249 Avery Nov 2007 B2
7301445 Moughler Nov 2007 B2
7308247 Thompson et al. Dec 2007 B2
7317383 Ihara Jan 2008 B2
7317392 DuRocher Jan 2008 B2
7317927 Staton Jan 2008 B2
7319848 Obradovich Jan 2008 B2
7321294 Mizumaki Jan 2008 B2
7321825 Ranalli Jan 2008 B2
7323972 Nobusawa Jan 2008 B2
7323974 Schmid Jan 2008 B2
7323982 Staton Jan 2008 B2
7327239 Gallant Feb 2008 B2
7327258 Fast Feb 2008 B2
7333883 Geborek Feb 2008 B2
7339460 Lane Mar 2008 B2
7349782 Churchill Mar 2008 B2
7352081 Taurasi Apr 2008 B2
7355508 Mian Apr 2008 B2
7365639 Yuhara Apr 2008 B2
7366551 Hartley Apr 2008 B1
7375624 Hines May 2008 B2
7376499 Salman May 2008 B2
7378946 Lahr May 2008 B2
7378949 Chen May 2008 B2
7386394 Shulman Jun 2008 B2
7421334 Dahlgren et al. Sep 2008 B2
7433889 Barton Oct 2008 B1
7447509 Cossins et al. Nov 2008 B2
7474264 Bolduc et al. Jan 2009 B2
7474269 Mayer et al. Jan 2009 B2
7499949 Barton Mar 2009 B2
7565230 Gardner et al. Jul 2009 B2
7697917 Camp et al. Apr 2010 B2
7876205 Catten Jan 2011 B2
7880642 Gueziec Feb 2011 B2
7898388 Ehrman et al. Mar 2011 B2
7941258 Mittelsteadt et al. May 2011 B1
20010018628 Jenkins et al. Aug 2001 A1
20020024444 Hiyama et al. Feb 2002 A1
20020111725 Burge Aug 2002 A1
20020128000 do Nascimento Sep 2002 A1
20030013460 Papadias et al. Jan 2003 A1
20030055555 Knockeart et al. Mar 2003 A1
20030069000 Kindo et al. Apr 2003 A1
20030134660 Himmel et al. Jul 2003 A1
20040039504 Coffee et al. Feb 2004 A1
20040066330 Knockeart et al. Apr 2004 A1
20040077339 Martens Apr 2004 A1
20040083041 Skeen et al. Apr 2004 A1
20040142672 Stankewitz Jul 2004 A1
20040176083 Shiao et al. Sep 2004 A1
20040210353 Rice Oct 2004 A1
20040236474 Chowdhary et al. Nov 2004 A1
20040236475 Chowdhary Nov 2004 A1
20050064835 Gusler Mar 2005 A1
20050070245 Nath et al. Mar 2005 A1
20050091018 Craft Apr 2005 A1
20050096809 Skeen et al. May 2005 A1
20050137757 Phelan et al. Jun 2005 A1
20050184860 Taruki et al. Aug 2005 A1
20050255874 Stewart-Baxter et al. Nov 2005 A1
20060121951 Perdomo et al. Jun 2006 A1
20060154687 McDowell Jul 2006 A1
20060212195 Veith et al. Sep 2006 A1
20060220905 Hovestadt Oct 2006 A1
20060234711 McArdle Oct 2006 A1
20060281495 Yang Dec 2006 A1
20060284769 Bolduc et al. Dec 2006 A1
20070202929 Satake Aug 2007 A1
20070229234 Smith Oct 2007 A1
20070293206 Lund Dec 2007 A1
20080064413 Breed Mar 2008 A1
20080064446 Camp et al. Mar 2008 A1
20080255722 McClellan et al. Oct 2008 A1
20080255888 Berkobin Oct 2008 A1
20080262670 McClellan et al. Oct 2008 A1
20090085728 Catten Apr 2009 A1
20100130182 Rosen May 2010 A1
20100134182 Kapoor et al. Jun 2010 A1
20110115618 Catten May 2011 A1
Foreign Referenced Citations (7)
Number Date Country
2071931 Dec 1993 CA
197 00 353 Jul 1998 DE
2007235530 Sep 2007 JP
WO 2004019646 Mar 2004 WO
WO 2005003885 Jan 2005 WO
WO2005109369 Nov 2005 WO
WO2008109477 Sep 2008 WO
Non-Patent Literature Citations (17)
Entry
International Search Report, Sep. 30, 2009, WIPO.
Ogle, et al.; Accuracy of Global Positioning System for Determining Driver Performance Parameters; Transportation Research Record 1818; Paper No. 02-1063; pp. 12-24.
Shen, et al.; A computer Assistant for Vehicle Dispatching with Learning Capabilities; Annals of Operations Research 61; pp. 189-211, 1995.
Tijerina, et al.; Final Report Supplement; Heavy Vehicle Driver Workload Assessment; Task 5: Workload Assessment Protocol; U.S. Department of Transportation; 69 pages, Oct. 1996.
Myra Blanco; Effects of In-Vehicle Information System (IVIS) Tasks on the Information Processing Demands of a Commercial Vehicle Operations (CVO) Driver; 230 pages, 1999.
U.S. Appl. No. 11/755,556, filed Sep. 1, 2009, Office Action.
U.S. Appl. No. 11/866,247, filed Sep. 29, 2009, Office Action.
U.S. Appl. No. 11/755,556, filed May 4, 2010, Office Action.
U.S. Appl. No. 11/866,247, filed Jun. 25, 2010, Notice of Allowance.
U.S. Appl. No. 11/866,247, filed Nov. 29, 2010, Notice of Allowance.
U.S. Appl. No. 13/012,660, filed Feb. 16, 2011, Office Action.
U.S. Appl. No. 13/012,660, filed Nov. 14, 2011, Office Action.
U.S. Appl. No. 13/012,660, filed Apr. 11, 2012, Office Action.
U.S. Appl. No. 13/012,660, filed Aug. 1, 2012, Office Action.
U.S. Appl. No. 13/012,660, filed Nov. 26, 2012, Office Action.
U.S. Appl. No. 13/012,660, filed Mar. 18, 2013, Office Action.
U.S. Appl. No. 13/012,660, filed Jul. 8, 2013, Office Action.
Related Publications (1)
Number Date Country
20100035632 A1 Feb 2010 US