WO2010069002A1 - Method, apparatus and system for vehicle detection - Google Patents

Method, apparatus and system for vehicle detection Download PDF

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Publication number
WO2010069002A1
WO2010069002A1 PCT/AU2009/001656 AU2009001656W WO2010069002A1 WO 2010069002 A1 WO2010069002 A1 WO 2010069002A1 AU 2009001656 W AU2009001656 W AU 2009001656W WO 2010069002 A1 WO2010069002 A1 WO 2010069002A1
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WO
WIPO (PCT)
Prior art keywords
vehicle
sensor
magnetic field
infra
sensors
Prior art date
Application number
PCT/AU2009/001656
Other languages
French (fr)
Inventor
Ilan Goodman
Avanindra Utukuri
Kwok Kwong Chan
Jonathan Clarke
Ted Chen
Nick Molo
Original Assignee
Park Assist Pty Ltd
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
Priority claimed from AU2008906551A external-priority patent/AU2008906551A0/en
Application filed by Park Assist Pty Ltd filed Critical Park Assist Pty Ltd
Publication of WO2010069002A1 publication Critical patent/WO2010069002A1/en

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Classifications

    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/042Detecting movement of traffic to be counted or controlled using inductive or magnetic detectors
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/04Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors

Definitions

  • inductive loops are typically quite large, making it difficult to distinguish between individual vehicles within close proximity to each other.
  • Camera-based and other solutions are generally easier to maintain, but suffer from undue complexity, high cost and demanding power requirements.
  • Magnetic detection devices such as those based on a Hall effect sensor, suffer from a high degree of sensitivity which leads to a high rate of false positives (i.e., incorrect detections).
  • Recent advances in low-power wireless networking provide an 5 opportunity to combine radio communications with low-power vehicle detection or sensing technology to produce a self-contained, battery-powered vehicle sensor or sensor node.
  • Potential advantages include: low cost of manufacture, due to the advent of inexpensive radio and battery technologies; io • ease and simplicity of installation and maintenance, due to small size and self-contained packaging; and ease of installation and operation, as wireless networks can be set up virtually anywhere without needing to provide line power to each sensor node or unit. Data may be relayed over long distances, if required.
  • a first aspect of the present invention provides a method for detecting vehicles.
  • the method comprises the steps of: detecting presence of a vehicle based on variations in a magnetic field; checking presence of the vehicle 30 using infra-red detection if presence of the vehicle was detected based on magnetic field variations; and outputting an indication of presence of the vehicle if the infra-red detection confirms presence of the vehicle.
  • the magnetic field may be the earth's magnetic field.
  • the step of outputting an indication of presence of the vehicle may comprise the steps of: activating a wireless transmitter; transmitting, via the wireless transmitter, data representative of presence of the vehicle; waiting a predetermined time period for a signal acknowledging receipt of the data; and de-activating the wireless transmitter after receipt of the acknowledgement signal.
  • the method may comprise the further step of resending the data if the acknowledgement signal is not received within the predetermined time period.
  • the method may be performed by a battery-powered apparatus.
  • Another aspect of the present invention provides an apparatus comprising a first part for permanent installation to a pavement or road surface and a second part housing an apparatus as described hereinbefore.
  • the second part is adapted to be removably attachable to the first part.
  • a parking management system comprising: a plurality of vehicle sensors installed in respective parking bays, the vehicle sensors comprising apparatuses as described hereinbefore; and a computer system coupled to the plurality of vehicle sensors.
  • the computer system is adapted to determine vehicle occupancy of the parking bays in accordance with data received from respective ones of the plurality of vehicle sensors.
  • Fig. 2 is a diagram showing magnetic flux distortions caused by entry of a ferrous object into a static magnetic field
  • Fig. 3 is a high-level circuit diagram of a single channel Anisotropic Magneto-Resistive (AMR) sensor 300 in accordance with an embodiment of the present invention
  • Fig. 7 is a circuit diagram showing the current source 330 in the AMR sensor 300 of Fig. 3;
  • Fig. 8 is a circuit diagram showing the differential 360 and high-gain 370 amplification stages of the AMR sensor 300 of Fig. 3;
  • Fig. 9 is a graph showing sensitivity change of the AMR sensor 300 of Fig. 3 as a function of temperature
  • Fig. 11 is a schematic circuit diagram of an Infra-Red (IR) sensor in accordance with an embodiment of the present invention.
  • Fig. 12 is a schematic block diagram of a vehicle sensor or detector in accordance with an embodiment of the present invention
  • Fig. 13a is a perspective view of a vehicle sensor enclosure in accordance with an embodiment of the present invention
  • Fig. 13b is a cross-sectional view of the vehicle sensor enclosure of Fig. 13a;
  • Figs. 13c and 13d are perspective views of a vehicle sensor enclosure in accordance with another embodiment of the present invention.
  • Fig. 15 is a flowchart of method for detecting vehicles using AMR and IR sensors in accordance with another embodiment of the present invention
  • Fig. 16 is an architectural block diagram of a parking management system in accordance with an embodiment of the present invention.
  • Magneto-resistive sensors are typically operated as threshold detectors in vehicle detection applications.
  • a vehicle moving in the vicinity of a magneto- resistive sensor causes a change in the magnetic field strength around the sensor, which, in turn, causes a corresponding change in resistance of the sensor.
  • a threshold When the magnitude of this resistance change exceeds a threshold, a vehicle is said to be present.
  • a super-threshold resistance change is said to indicate the vehicle's departure. Difficulty lies in selecting a threshold value to both maximise the probability of detection and minimise the probability of false positives (i.e., determining that a vehicle has arrived when it hasn't, or determining that a vehicle has departed when it hasn't).
  • magneto-resistive sensors suffer from a variety of problems: magneto-resistive sensors are extremely sensitive to shifts in the earth's baseline magnetic field, and need continual re-calibration; magneto-resistive sensors are extremely sensitive to temperature drift, and need continual re-calibration.
  • Magneto-resistive sensors detect vehicle movements by way of magnetic field changes and can be fooled by other objects that alter magnetic fields such as magnets and large metallic objects (e.g., garbage dumpsters); magneto-resistive sensors are inherently omni-directional and cannot easily be focussed in a particular direction; and • vehicles alter magnetic fields, not only by virtue of their metallic components but also through the magnetic fields generated by their engines and/or other equipment. Depending on the vehicle type, make and model, as well as the vehicle's orientation with respect to the sensor, this can either amplify or reduce the change in detectable magnetic field strength.
  • An active infra-red (IR) sensor comprises an IR light emitting diode (LED), which emits infra-red light, and a photodiode to detect the reflected IR light.
  • LED IR light emitting diode
  • the LED is made to emit short pulses of IR light in a focused beam. If a solid object is located anywhere in the beam's path, some of the IR light gets reflected back towards the emitter.
  • the photodiode detector is situated next to the LED emitter; when reflected IR light coincides with the photodiode, the photodiode detector produces a voltage or current that can be measured.
  • the presence of an object can be inferred; likewise, if no reflected energy is detected, there is no object in the IR sensor's field of view.
  • IR detection method solves many of the problems inherent in magnetic detection: temperature drift has a significantly lower effect on performance; • only objects directly in the IR sensor's field of view are detected.
  • the IR pulse can be focused and aimed to detect objects within a particular region, and thus would not be fooled by vehicles in adjacent spaces; and detection depends on the position of a vehicle only and not on the state of a vehicle (on or off) or it's size.
  • IR sensors are usually operated in pulse mode with a low duty-cycle to minimise power consumption. This results in a loss of temporal resolution, as only vehicle movements lasting longer than one duty cycle (typically 3 seconds minimum) can be detected. In parking applications, particularly, this can result in critical errors; changes in ambient light levels can affect sensitivity, and require continual re-calibration; ambient IR light can trigger a false detection; and
  • IR lenses require continual cleaning, as dirt, debris, and acts of vandalism can all cause the lens to become blocked.
  • Embodiments of the present invention combine a magneto-resistive sensor with an active IR sensor, and provide a set of algorithms that exploit the positive qualities of each, while minimising the effect of the negative qualities. This enables production of a small, self-contained, battery-powered sensor node with high detection accuracy and low latency, and enough battery life to last several years on a single charge.
  • Fig. 1 shows a sensing element 100 for use in an Anisotropic Magneto- Resistive (AMR) sensor.
  • the sensing element 100 comprises a thin layer or thin film of nickel iron (Ni Fe) permalloy 110 having metal contacts 130, 135 at each end and mounted on a silicon substrate 120.
  • Ni Fe nickel iron
  • the sensing element 100 undergoes a directional or anisotropic change in resistance according to the intensity of a magnetic field applied in the directions indicated by arrows 150, which causes current flow in the direction indicated by arrows 140.
  • the sensing element 100 has excellent linearity with magnetic field, along with enough sensitivity to detect vehicles. Linearity is within 0.1 % of fullo scale in a measurement range of +/- 1 Gauss.
  • the sensing element 100 is capable of measuring the earth's magnetic field, which is a static ambient magnetic field of value upwards of 650 milli- Gauss, depending on geographical location. When a large ferrous object enters this static field, it distorts the field and generates a change in resistances in the sensing element 100. This change is in the order of 15 milli-Gauss at a range of about 5ft or about 1.5m.
  • Fig. 2 shows magnetic flux distortions 230 caused by entry of a ferrous object 200 into a static magnetic field 210.
  • the sensitivity of the sensing element 100 to an induced magnetic field varies with temperature.
  • AMR datasheet specifies a -600 parts-per-million temperature coefficient ofo sensitivity.
  • Fig. 3 shows a high-level diagram of a single channel AMR sensor 300. It should be noted that there are two axes of measurement, which are orthogonal to each other.
  • the sensor 300 comprises: an AMR bridge sensor element 310 (similar to or the same as the sensing element 100 of Fig. 1 ), a voltage reference 320, a current source 330, a strap driver 340, a digital potentiometer 350, and two amplifier stages 360 and 370.
  • the voltage reference 320 provides an accurate and low temperature coefficient reference point for the surrounding analog circuitry.
  • the current source 330 provides immunity against sensitivity drift. As temperature increases, the resistance of the bridge sensor element 310 changes, which causes a change in current flow.
  • the differential amplifier 360 minimises common-mode noise generated by the bridge configuration of the bridge sensor element 310 and is selected for low noise, low input offset voltage, and low input offset drift.
  • the function of the differential amplifier stage 360 is to amplify the very small voltage changes generated by the bridge sensor element 310 into larger useable signals.
  • the digital potentiometer 350 and related offset control algorithm enable the amplifier 370 (the final gain stage) to zoom in on the signal (essentially providing a form of automatic gain control), which dramatically increases the dynamic range of the output of the bridge sensor element 310.
  • the sensor element 310 is reset via a strap driver circuit 340 and then an analog-to-digital converter (not shown in Fig. 3) measures the low-gain signal 365 at the output of the differential amplifier 360.
  • a microcontroller (not shown in Fig. 3) uses the measurement from the analog- to-digital converter to determine a value for outputting to the digital potentiometer 350, which offsets the first amplifier stage 360.
  • the second amplifier stage 370 provides a high gain output 375 of a small selected window of the full range of possible signals. The use of high gain and 'zooming in' on the signal enables successful detection of vehicles based on measured changes in the magnetic field.
  • the strap driver circuit 340 utilises an internal resistive strap that toggles the sensing polarity and flushes any remnant flux before/after sensing. By applying a short duration high-current pulse to the strap, accumulated flux can 5 be removed to provide an accurate reading.
  • Fig. 4 is a circuit diagram showing the strap driver circuit 340 of Fig. 3 for applying a set/reset pulse to the bridge sensor element 310.
  • a positive-going current pulse 430 will be generated and applied to the internal strap of the AMR sensor. This pulse typically has amplitude of ⁇ 600mA and decay of 2uS.
  • the AMR_RSP signal 410 and AMR_RSM signal 420 are reversed, the current 'spike' 435 flows in the opposite direction. 5
  • the magnetic domain orientations through set/reset of the bridge sensor element 310 are illustrated in Fig. 5.
  • Fig. 5a shows a permalloy (NiFe) magneto-resistive element 510 exhibiting random magnetic domain orientations 521 , 522, 523 ... o
  • Fig. 5b shows the permalloy (NiFe) magneto-resistive element 510 of Fig
  • the magnetic domain orientations 530 are from left to right along the easy axis 540, which is orthogonal to the sensitive axis
  • Fig. 5c shows the permalloy (NiFe) magneto-resistive element 510 of Fig
  • Fig. 6 is a circuit diagram showing the voltage reference 320 of Fig. 3. Referring to Fig. 6, the output 610 of the voltage reference integrated circuit 620 is divided by the potential divider comprising resistors R101 and R103 to create a half-reference 630, which is buffered by the integrated circuit 640 to provide a buffered output 650. The calculations below show computation of the worst-case deviation of the voltage reference:
  • V ref 2.5V (nominal) Temperature Coefficient: 20 PPM
  • Vref/ 2 1.25V +/- (0.0065V + 0.008125V)
  • V ref can be 2.5V (+/-) 13mV
  • Vre f / 2 can be 1.25V (+/-) 14.625mV
  • Fig. 7 is a circuit diagram showing the current source 330 of Fig. 3, which provides a stable constant current through the bridge sensor element 310. It is instructive to analyse current drift, since sensitivity of the bridge sensor element 310 is proportional to current flow.
  • the operational amplifier (op-amp) 710 uses negative feedback from the emitter of the transistor 720 to set the current flowing from the bridge sensor element 310.
  • the op-amp 710 will attempt to force the voltage at its inverting input to match the voltage at the non-inverting input, thus effecting a constant voltage across resistor 730.
  • a constant voltage across a constant resistance yields a constant current.
  • the calculations below show computation of variation in the non-inverting input, input offset, drift, and the current setting resistor. This yields a current variation over tolerance and temperature, which ultimately yields a sensitivity variation that can be used in the detection algorithm:
  • V + V ref * ( R91 / R88 + R91 )
  • V + (2.5V (+/-) 0.013V) * [(49.9K (+/-) 324.72) / (499K (+/-) 3247.24 + 49.9K (+/-) 324.72]
  • the resistor can be about +/- 1 ohm. Accordingly:
  • the sensitivity of the bridge sensor element is nominally 1 mV / mA / Gauss. It should be noted that this sensitivity rating has its own +/- 20% tolerance, which is significantly higher than the current source variation. This means that there is no way to make sensitivity any more predictable upon start-up. Therefore, a worst-case sensitivity of 0.8mV/mA/Gauss must be assumed for calculating detection at the target range.
  • Fig. 8 is a circuit diagram of the analog front-end of the embodiment shown in Fig. 3.
  • a high gain differential amplifier 360 In order to increase low (typically milli-volt) signal levels, it is necessary to use a high gain differential amplifier 360 to read the bridge sensor element 310. It is important to offset the differential amplifier integrated circuit 810 via the digital potentiometer 350, in order to be able to acquire useable signals off of the high gain stage 370 formed by the integrated circuit 820.
  • the bridge sensor element 310 has two types of offsets: electrical and magnetic. These offsets must not saturate the first gain stage 360, which requires calculation to select an appropriate gain. Firstly, the electrical offset is due to manufacturing tolerances and cannot be avoided; for the HMC1052, this offset is specified at 1.25mV with a temperature coefficient of 10 PPM.
  • the offset can be (+/-) 1.85mV.
  • the magnetic offset induced by the earth's magnetic field must be accounted for. This value is known to be nominally around +/- 650 milli-Gauss. The maximum sensitivity over temperature is assumed (given - 600PPM from specifications) when calculating this offset, as shown:
  • the total possible offset from the bridge sensor element over temperature is +/- 2.92mV.
  • the +/-2.92mV figure can thus be rounded to 3mV for safety.
  • an offset of 1.25V is written to the high gain stage, which enables uni-polar operation of our circuitry.
  • a gain of 200 is thus suitable, yielding a high safety margin. This minimises the risk of possible external magnetic sources saturating the sensor.
  • Filters in the feedback path are optimised for quick start-up, rather than noise immunity.
  • Noise filtering is performed in the digital domain and averaged, since the primary noise source is white.
  • the second gain stage is designed to give a gain of 20, which was determined experimentally by computing the total expected vehicle change at the maximum sensitivity multiplied by a gain to fall within the required analog- to-digital (ADC) range.
  • ADC analog- to-digital
  • Read Low Gain AMR sensor outputs (sample at least 50 times and average value for noise immunity) Calculate the final written offset as [ 2.5V - (#4 value)] for each channel, then write offset into digital potentiometer's volatile and non-volatile memory. This calibration should not be changed unless the sensor is reinstalled at another location, or readings are constantly out of range on the ADC (rare error). Note that the value written can only be precise to 2.5V / 256 steps due to limited resolution of the digital potentiometer. • Read the high gain channels (at least 50 times), then calculate RMS value, store the RMS, axisi and axis2 values.
  • More advanced algorithms that take into account temperature drift are possible, for example, through time domain analysis of the signal.
  • the fact that an incoming vehicle will appear as a transient and temperature change will appear as a slowly changing DC bias will make the algorithm work exceptionally well.
  • a simple moving average filter which is a type of FIR filter, is used to provide a slowly changing value to make comparisons with.
  • Fig. 9 shows the sensitivity change (Y-axis) as a function of temperature
  • X-axis for the sensor.
  • PCB printed circuit board
  • Peltier device digital heat pump
  • Fig. 10 shows high level gain across a broad temperature sweep.
  • the direction of the curve is not of much significance since the direction of the magnetic field is not known a priori.
  • the IR technology provides a simpler and cheaper way to minimise both missed detections and false alarm errors. There are, however, some limitations for outdoor applications using IR technology.
  • the composition of sunlight includes visible light, waves in the UVA, UVB and UVC ranges, and waves in IR range. Therefore, sunlight may falsely trigger an IR receiver.
  • Embodiments of the present invention use a special IR transmitter with pulse-width modulation (PWM) at a centre frequency of 455 KHz.
  • PWM pulse-width modulation
  • the received IR signal is then filtered to that the IR receiver is triggered only by light at 850 nm wavelength and modulated IR at 455 KHz through the use of a tuned band-pass filter, automatic gain control, and a demodulator.
  • Other protection mechanisms are also included, such as only triggering the IR receiver for a specified period of time (70 us after IR LED is driven). These measures prevent or reduce false triggering of the IR receiver due to ambient IR light.
  • Fig. 11 is a schematic circuit diagram of an Infra-Red (IR) sensor or detection circuit.
  • IR Infra-Red
  • the IR receiver comprises a PIN photo diode D9, with an initial trans-impedance stage followed by a third-order bandpass filter tuned to 455 KHz.
  • PWM pulse-width modulation
  • a bank of capacitors C26, C19, C20 and C22 act as short-term storage devices for supplying the required current.
  • the capacitors C26, C19, C20 and C22 store energy from the battery and provide power for driving the IR LED at high current.
  • current has to be pulse-width modulated into transistor Q2 to charge the capacitors C26, C19, C20 and C22. Then transistor Q2 is switched off, and the IR LED transmitter D12, D12 is driven for 25us at 455 KHz.
  • Switch on Q2 charge capacitors for providing power to drive IR LED Once capacitors are fully charged, switch Q3 for powering IR receiver Drive the IR LED 70us at 455 KHz
  • Performance of the individual magneto-resistive (AMR) and infra-red (IR) sensors has been optimised for vehicle detection by careful design, as described hereinbefore.
  • AMR magneto-resistive
  • IR infra-red
  • Performance of the individual magneto-resistive (AMR) and infra-red (IR) sensors has been optimised for vehicle detection by careful design, as described hereinbefore.
  • the performance of each type of sensor operating alone is considered insufficient for effective commercial deployment of battery powered vehicle detection sensors or nodes.
  • the AMR sensor suffers from high sensitivity and is prone either to a relatively high false alarm rate (i.e., a high rate of false positives) or a high miss rate.
  • the IR sensor while providing a highly accurate detection rate, suffers from high current consumption resulting in reduced battery life of the sensor.
  • the present inventors have combined the two sensors to provide a method and apparatus for detecting vehicles with high accuracy and low average current consumption.
  • Fig. 12 shows a block diagram of a vehicle sensor or vehicle sensor node 1200 in accordance with an embodiment of the present invention.
  • the vehicle sensor 1200 is a completely self-contained, battery-operated apparatus capable of communicating to an external access point via a secure wireless network.
  • Vehicle detection is performed using two main sensors (AMR and IR), as described hereinbefore, with optional auxiliary sensors used to calibrate and refine the detection routines.
  • the vehicle sensor 1200 comprises a circuit board and the following main components:
  • the Semtech XE1203F RF transceiver was selected for this particular embodiment and is operated at 868 / 915 MHz (Frequency Hopping Spread Spectrum).
  • a separate RF or wireless transmitter and receiver may be practiced in alternative embodiments.
  • a RF antenna 1220 A circuit board-mounted Splatch quarter-wave monopole antenna was selected for this embodiment.
  • a microcontroller 1220 with on-board memory with on-board memory.
  • An AMR sensor 1240 such as the AMR sensor described hereinbefore with reference to Fig. 3.
  • the two-axis Honeywell HMC1022 sensor was selected as the bridge sensor in this embodiment.
  • a light sensor 1280 is provided.
  • FIGs. 13a and 13b One embodiment of the sensor enclosure is shown in Figs. 13a and 13b.
  • the enclosure was designed with a particular focus on easing installation effort and reducing labour costs.
  • the sensor comprises a two-part assembly: a base 1310, which is installed in a pre-drilled hole in the pavement and adhered to the pavement using hot asphalt / bitumen or other adhesives; and a dome 1320, which fits to the base 1310 and is secured with a tamper-proof screw down the centre 1330.
  • a base 1310 which is installed in a pre-drilled hole in the pavement and adhered to the pavement using hot asphalt / bitumen or other adhesives
  • a dome 1320 which fits to the base 1310 and is secured with a tamper-proof screw down the centre 1330.
  • an entire car park could be installed with sensor bases 1310 in advance, and the more expensive sensor domes containing all the electronics could be installed at a later date.
  • the two part assembly advantageously assists maintenance when compared to existing sensors, which must be removed from the pavement by digging the sensor out the asphalt itself.
  • the two-part assembly enables
  • the sensor enclosure avoids the use of a centre screw entirely, by shaping the dome and base in such a way that the dome screws or locks into the base directly by simply twisting the dome.
  • the dome shaft may be shaped with corkscrew grooves around the perimeter, with the base having complementary protrusions or shapes.
  • the dome can be designed to be removed only by means of a proprietary tool to generally restrict removal of the dome. However, the shape would still need to provide a high degree of strength and impact resistance.
  • a pattern of holes on the top of the dome could be used as a receptacle for a proprietary torque-wrench tool.
  • a different "surface-mounted" base 1340 has been developed that accommodates the same dome 1320, as shown in the embodiment of Figs. 13c and 13d.
  • the surface mounted base 1340 is mounted on the pavement surface, and is secured using concrete bolts and/or adhesive.
  • the dome assembly 1320 is identical to that for the in-ground base 1310.
  • Fig. 14 is a flowchart of a method for detecting vehicles using an AMR sensor and an IR sensor. The method of Fig. 14 is described assuming an initially vacant parking bay. However, operation beginning with a parking bay in the occupied state is substantially similar.
  • the output of the AMR sensor is sampled at step 1410 to detect occupancy or presence of a vehicle based on variations in a magnetic field, in this instance, the earth's magnetic field.
  • a predetermined threshold compared to the previous sampled value or a combination of previously sampled values (e.g., a moving average). If not (NO), processing returns to step 1410 after a predetermined time delay (sleep interval) at step 1425. On the other hand, if the sampled value has changed by more than the predetermined threshold (YES), thus indicating presence of a vehicle, the IR sensor is activated at step 1430.
  • Activation of the IR sensor at step 1430 is preferably performed immediately prior to checking occupancy or presence of the vehicle using infra-red detection to conserve power.
  • deactivation of the IR sensor at step 1445 is preferably performed immediately after checking occupancy or presence of the vehicle using infra-red detection to conserve power.
  • a continuum of operating set points can be achieved that trade off between detection accuracy, latency, and battery life. For example, with a low AMR threshold, detection accuracy can be improved by operating the IR detector more frequently (i.e., a shorter time delay or sleep interval). However, the trade-off for this increased level of detection accuracy is a reduction in battery life. Similarly, reducing the sleep interval can improve latency, but also at the expense of battery life. However, providing a long sleep interval with low AMR threshold can result in high accuracy and long battery life, at the expense of latency. Which operating point to use depends on the specific application. For example, a local parking guidance application might require extremely low latency with medium battery life and accuracy, whereas a parking enforcement application would require extremely high accuracy, with only moderate latency.
  • Fig. 15 is a flowchart of another method for detecting vehicles using an
  • AMR sensor and an IR sensor The method of Fig. 15 is described assuming an initially occupied parking bay. However, operation beginning with a parking bay in the vacant state is substantially similar. Furthermore, in the method of Fig. 15, a discrepancy between the AMR and IR sensors is identified as an "error" state. This could be useful in cases where there is a high risk of vandalism or interference, wherein one of the two sensors is unable to function accurately. For example, the IR lens could become covered, causing a vehicle exit to go undetected. With the method of Fig. 15, the error would be detected, and an enforcement officer or other person could be dispatched to clean the lens.
  • the output of the AMR sensor is sampled at step 1510.
  • a predetermined threshold compared to the previous sampled value or a combination of previously sampled values (e.g., a moving average). If not (NO), processing returns to step 1510 after a predetermined time delay (sleep interval) at step 1525. On the other hand, if the sampled value has changed by more than the predetermined threshold (YES), thus indicating absence of a vehicle, operation of the IR sensor is activated at step 1530 to confirm absence of the vehicle (vacancy).
  • step 1540 a determination is made whether a reflected IR message is successfully detected. If so (YES), the IR sensor is deactivated and an error condition is output at step 1645 to indicate that the AMR and IR sensors have output a differing detection result. Thereafter, processing returns to step 1510 after a predetermined time delay (sleep interval) at step 1525.
  • the IR sensor is deactivated at step 1550 and vehicle vacancy status is confirmed and/or output at step 1560.
  • a broad embodiment of the present invention provides a method for detecting vehicles that comprises the steps of: detecting presence of a vehicle based on variations in a magnetic field; checking presence of the vehicle using infra-red detection if presence of the vehicle was detected based on magnetic field variations; and outputting an indication of presence of the vehicle if the infra-red detection confirms presence of the vehicle.
  • the magnetic field may be the earth's magnetic field. Presence of the vehicle may be detected if a variation in the magnetic field exceeds a predetermined threshold.
  • the method may comprise the further steps of: activating the infrared detection immediately prior to checking presence of the vehicle; and deactivating the infra-red detection immediately after checking presence of the vehicle to conserve power.
  • the step of outputting an indication of presence of the vehicle may comprise the steps of: activating a wireless transmitter; transmitting, via the wireless transmitter, data representative of presence of the vehicle; waiting a predetermined time period for a signal acknowledging receipt of the data; and de-activating the wireless transmitter after receipt of the acknowledgement signal.
  • the method may comprise the further step of resending the data if the acknowledgement signal is not received within the predetermined time period.
  • the method may be performed by a battery- powered apparatus.
  • the magneto-optical vehicle sensors and methods described herein are useful for many applications where vehicle detection is required. Such applications include, but are not limited to: Parking guidance: Real-time parking information can be displayed on electronic maps such as Google Maps or on satellite navigation devices, directing motorists to nearby available spaces, whether on-street or in an off-street parking area. Once in a parking structure or area, variable message signs and LED indicator lights can be used to direct motorists to unoccupied parking bays quickly and efficiently.
  • Policy enforcement Real-time information can be used to identify vehicles that are in violation of parking policies. This includes: vehicles that overstay a set time limit; vehicles that fail to pay a parking fee; and vehicles that do not have a required permit. In addition, strict access control can be implemented by the additional use of electronic ID tags.
  • Traffic management The magneto-optical vehicle sensors and methods described herein can be used to monitor the speed, volume and direction of traffic in laneways, streets, and highways. Data from the sensors can be used to support traffic analysis, and variable message signs and other displays can be used to manage traffic flows and provide real-time feedback to drivers. Electronic ID tags can be used to allow drivers to pay tolls according to driving distance, which can be measured on a very precise scale. Yield management: Analysis of historical trends can help owners of a parking asset maximise the return on the cost of the asset by optimising its ongoing revenue and cost streams. Analysis can include evaluation of and extrapolation from historical trends, as well as more advanced prediction modelling that takes into account complex relationships between multiple variables.
  • Labour force management Analysis of historical trends can aid in the efficient deployment of labour to reduce costs while maximising revenues.
  • labour and other resources can be allocated efficiently by extrapolating and predicting needs from historical trends; in addition, predicted needs can be compared to actual deployments to determine labour force efficiency.
  • Operational management Real-time information can help parking managers and traffic analysts make quick, well-informed operational decisions. Models based on historical trends can enhance these decisions by providing recommendations based on optimal desired outcomes. Managers can also remotely monitor operations from offsite locations (through the web service), and set up real-time alerts through email, SMS, and other communication devices. Finally, managers can also control some operations remotely, such as updating variable message signs and reassigning enforcement policies.
  • Such systems generally comprise: apparatus and a method to communicate data to and from multiple vehicle sensors to a common location; • apparatus and a method to process the data at the common location, and generate control signals and/or provide other required interfaces for the vehicle sensor data; and peripheral devices and apparatus and a method for communicating between the peripheral devices, the vehicle sensors, and the common location.
  • Fig. 16 shows a schematic block diagram of a parking management system 1600 that includes vehicle sensors according to an embodiment of the present invention.
  • the parking management system comprises a Local Facilities Management Computer 1610, LEDs 1622, 1624..., message signs 1632,
  • the LEDs 1622 and 1624, message signs 1632 and 1634 and vehicle sensors 1642 and 1644 are electrically and communicatively coupled to the Local Facilities Management Computer 1610 by way of an LED bridge 1620, a message sign bridge 1630 and a vehicle sensor bridge 1640, respectively.
  • the various bridges provide an intermediate level of sub-system device management and may comprise programmable logic controllers.
  • the Local Facilities Management Computer 1610 is adapted to control the LEDs 1622, 1624... in accordance with data received from the vehicle sensors 1642, 1644... to indicate occupancy status of individual parking bays (i.e., occupied or vacant).
  • Those skilled in the art will appreciate that other indicator lights (e.g., incandescent, fluorescent or halogen lights) may be alternatively used in place of LEDs.
  • the Local Facilities Management Computer 1610 may further be adapted to control the message signs 1632, 1634... in accordance with data received from the vehicle sensors 1642, 1644....
  • message signs may, for example, comprise LED or incandescent bulb panels, LCD displays, back- lit projection boxes, organic LED displays, cathode ray tube screens, digital light projected displays, or any other programmable electronic variable message display.
  • the Local Facilities Management Computer 1610 may be communicatively coupled to other systems 1650.
  • Such other systems may include, but are not limited to: billing and reporting systems, GPS navigation systems, mapping information systems such as Google Maps ® , mobile information systems such as XM satellite radio, portable digital information systems such as mobile telephones and personal digital assistants (PDAs), desktop computers, remote displays such as off-site message signs, on- and off-site payment systems such as parking meters, pay and display terminals, telephone billing systems, online payment systems and online space reservation systems.
  • Such coupling may, for example, be via a dedicated connection or a network such as a local area network (LAN), a Wide Area Network (WAN) or the Internet.
  • LAN local area network
  • WAN Wide Area Network
  • ID tags 1660 such as Radio Frequency Identification Tags, may be detected and read by the vehicle sensors 1642, 1644 to uniquely identify vehicles or occupants of vehicles.
  • the vehicle sensors 1642 and 1644 communicate with the sensor bridge 1640 via a wireless communication link in a star topology. In other words, each of the sensors 1642 and 1644 communicate directly with the sensor bridge 1640, but the sensors 1642 and 1644 never communicate directly with each other. Since the sensors 1642 and 1644 are battery operated and are required to last for more than 5 years on a single charge, the communication is necessarily performed using extremely low power. To save power, the radio sub-system is turned off when not in use.
  • the sensors use a contention-based "push only" protocol, in which each sensor transmits data packets whenever it has new information to communicate.
  • a contention-based "push only" protocol in which each sensor transmits data packets whenever it has new information to communicate.
  • only a sensor can initiate a communication - the sensor bridge cannot communicate with a sensor at will, rather only in response to a message from the sensor.
  • embodiments of the parking management system may be implemented without the LEDs 1622, 1624... and/or the message signs 1632, 1634... Furthermore, embodiments of the parking management system may be implemented without one or more of the message sign bridge 1630, the LED bridge 1620, and/or the vehicle sensor bridge 1640.
  • Fig. 17 is a flowchart of a method for a sensor to communicate via a wireless network.
  • the vehicle sensors 1642 and 1644 may wirelessly communicate with the Local Facilities Management
  • a sensor activates its internal radio transceiver when wanting to communicate at step 1710.
  • the sensor transmits a data packet at step 1720 and then waits a predetermined time at step 1730 for receipt of an acknowledge (ACK) signal. If an acknowledge (ACK) signal is not received (NO) at step 1740, the sensor waits for a random time delay period at step 1745 before returning to step 1720 to re-transmit the current data packet.
  • ACK acknowledge
  • the sensor de-activates the radio transceiver at step 17850 until another data packet needs to be sent.
  • a designated sensor node acts as a coordinator node, and communicates with all other nodes.
  • a specially designed "access point” communicates with all sensors in its vicinity, and possesses extra computing power and memory to perform advanced coordination functions.
  • This node could be battery powered or line powered and could be situated in the pavement, or mounted on a light pole or on the side of a building, or inside a building.
  • a computer system e.g. a PC inside a building or other structure, with a radio device capable of communicating with sensors in its vicinity
  • a mesh or star or other network of such devices (1-3)
  • the local facilities management computer coordinates peripheral devices and other data interfaces.
  • This device could be a personal computer (PC) running application-specific software, and could have a multitude of devices connected to it.
  • PC personal computer
  • the Local Facilities Management Computer 1610 could be coupled directly to the vehicle sensor bridge 1640 as a single device.
  • indicator lights in each bay could be used to convey the occupancy of the bay from a distance (e.g., red for occupied, green for vacant).
  • LED lights could be powered by batteries and communicate with the local facilities management computer through a wireless network, or the LED lights could receive line power and communicate through a wireline network via some kind of bus or daisy chain.
  • the vehicle sensors could communicate directly with the LEDs through a wireless or wireline link.
  • electronic displays can be used to provide real-time updates about space occupancy and/or other information, and can communicate wirelessly or through a wireline network.
  • Other peripherals such as handheld devices, satellite navigation devices, mobile phones, and numerous others could be similarly implemented. Such devices could utilise existing networks, for example the mobile phone cellular network, or WiFi for WiFi enabled devices.
  • ID tags could be implemented in a variety of ways, including the use of off-the- shelf available RFID tags and readers, or the use of ID tags as devices that can communicate and pair directly with a wireless sensor.
  • the ID tags comprise a wireless transceiver of the same type as used in the wireless sensor nodes (i.e., to simplify implementation).
  • the sensor node Upon detecting a vehicle, the sensor node transmits an ID tag request message.
  • the ID tags "listen" at regular intervals, and upon receiving a request, an ID tag transmits its unique ID message to the wireless sensor node.
  • the ID tags comprise a wake-up detection circuit that, when excited with RF energy in a particular band, causes the transceiver in the ID tag to power on and transmit its ID message to the sensor node.
  • the wireless sensor node transmits the requisite excitation RF energy upon detecting a vehicle.
  • the wireless sensor node forwards the ID message to the local facilities management computer.

Abstract

Embodiments of a method, apparatus and system for detecting vehicles are disclosed. One such method comprises the steps of: detecting presence of a vehicle based on variations in a magnetic field; checking presence of the vehicle using infra-red detection if presence of the vehicle was detected based on magnetic field variations; and outputting an indication of presence of the vehicle if the infra-red detection confirms presence of the vehicle.

Description

METHOD, APPARATUS AND SYSTEM FOR VEHICLE
DETECTION
Related Applications The present application claims the benefit of the filing date of Australian
Provisional Patent Application No. 2008906551 , filed 19 December 2008, hereby incorporated by reference in its entirety as if fully set forth herein.
Field of the Invention The present invention relates generally to detection of the presence and/or absence of vehicles in specific locations and more specifically to the detection of vehicles for parking and traffic applications.
Background Numerous methods and devices for detecting vehicles have been built and/or employed to measure and monitor traffic flows, control vehicle boom gates and other systems for restricting vehicle access, and monitor parking facilities for guidance and enforcement purposes. Such methods and devices include video and acoustic processing, detecting and measuring changes in pressure, electromagnetic induction, and ultrasonic/radio-frequency/optical reflection. The most widely used of these, electromagnetic induction, has been in use (in the form of inductive loop sensors) in the transportation industry for decades, notwithstanding several undesirable properties. Firstly, inductive loops are costly to install and maintain, and are susceptible to damage during resurfacing of road surfaces or pavements. Secondly, inductive loop sensor equipment generally requires line power to operate. Thirdly, inductive loops are typically quite large, making it difficult to distinguish between individual vehicles within close proximity to each other. Camera-based and other solutions are generally easier to maintain, but suffer from undue complexity, high cost and demanding power requirements. Magnetic detection devices, such as those based on a Hall effect sensor, suffer from a high degree of sensitivity which leads to a high rate of false positives (i.e., incorrect detections).
Recent advances in low-power wireless networking provide an 5 opportunity to combine radio communications with low-power vehicle detection or sensing technology to produce a self-contained, battery-powered vehicle sensor or sensor node. Potential advantages include: low cost of manufacture, due to the advent of inexpensive radio and battery technologies; io • ease and simplicity of installation and maintenance, due to small size and self-contained packaging; and ease of installation and operation, as wireless networks can be set up virtually anywhere without needing to provide line power to each sensor node or unit. Data may be relayed over long distances, if required.
I 5
Since both detection accuracy and robustness/range of communications are typically directly proportional to power consumption, a need exists for vehicle detection methods and apparatuses having a suitable trade-off between accuracy, reliability, and battery longevity. Additional considerations
20 include: cost and complexity of installation; cost and complexity of deployment and configuration; and ability to reuse the communication component for other data and/or uses
(for example, communication of ID tag information).
25
Summary
A first aspect of the present invention provides a method for detecting vehicles. The method comprises the steps of: detecting presence of a vehicle based on variations in a magnetic field; checking presence of the vehicle 30 using infra-red detection if presence of the vehicle was detected based on magnetic field variations; and outputting an indication of presence of the vehicle if the infra-red detection confirms presence of the vehicle. The magnetic field may be the earth's magnetic field.
Presence of the vehicle may be detected if a variation in the magnetic field exceeds a predetermined threshold.
The method may comprise the further steps of: activating the infra-red detection immediately prior to checking presence of the vehicle; and deactivating the infra-red detection immediately after checking presence of the vehicle to conserve power.
The step of outputting an indication of presence of the vehicle may comprise the steps of: activating a wireless transmitter; transmitting, via the wireless transmitter, data representative of presence of the vehicle; waiting a predetermined time period for a signal acknowledging receipt of the data; and de-activating the wireless transmitter after receipt of the acknowledgement signal.
The method may comprise the further step of resending the data if the acknowledgement signal is not received within the predetermined time period.
The method may be performed by a battery-powered apparatus.
Another aspect of the present invention provides an apparatus for detecting vehicles. The apparatus comprises: a magneto-resistive sensor for detecting presence of a vehicle; an infra-red sensor for checking presence of the vehicle; and a controller coupled to the magneto-resistive sensor and the infra-red sensor; wherein the controller is adapted to: detect presence of a vehicle based on variations in a magnetic field; check presence of the vehicle using infra-red detection if presence of the vehicle was detected based on magnetic field variations; and output an indication of presence of the vehicle if the infra-red detection confirms presence of the vehicle.
Another aspect of the present invention provides an apparatus comprising a first part for permanent installation to a pavement or road surface and a second part housing an apparatus as described hereinbefore. The second part is adapted to be removably attachable to the first part. - A -
Another aspect of the present invention provides a parking management system comprising: a plurality of vehicle sensors installed in respective parking bays, the vehicle sensors comprising apparatuses as described hereinbefore; and a computer system coupled to the plurality of vehicle sensors. The computer system is adapted to determine vehicle occupancy of the parking bays in accordance with data received from respective ones of the plurality of vehicle sensors.
The parking management system may further comprise a plurality of indicator lights with each indicator light adapted to indicate vehicle occupancy status of a respective parking bay. The computer system may further be adapted to control the plurality of indicator lights in accordance with data received from respective ones of the plurality of vehicle sensors.
The parking management system may further comprise at least one message sign coupled to the computer system. In this case, the computer system is adapted to control the message sign in accordance with data received from one or more of the plurality of vehicle sensors.
Brief Description of the Drawings
A small number of embodiments are described hereinafter, by way of example only, with reference to the accompanying drawings in which: Fig. 1 is a diagram of a sensing element used in an Anisotropic Magneto-
Resistive (AMR) sensor;
Fig. 2 is a diagram showing magnetic flux distortions caused by entry of a ferrous object into a static magnetic field;
Fig. 3 is a high-level circuit diagram of a single channel Anisotropic Magneto-Resistive (AMR) sensor 300 in accordance with an embodiment of the present invention;
Fig. 4 is a circuit diagram showing the strap driver circuit 340 in the AMR sensor 300 of Fig. 3;
Figs. 5a, 5b and 5c show magnetic domain orientations in a permalloy (NiFe) magneto-resistive element; Fig. 6 is a circuit diagram showing the voltage reference 320 in the AMR sensor 300 of Fig. 3;
Fig. 7 is a circuit diagram showing the current source 330 in the AMR sensor 300 of Fig. 3; Fig. 8 is a circuit diagram showing the differential 360 and high-gain 370 amplification stages of the AMR sensor 300 of Fig. 3;
Fig. 9 is a graph showing sensitivity change of the AMR sensor 300 of Fig. 3 as a function of temperature;
Fig. 10 is a graph showing high level gain of the AMR sensor 300 of Fig. 3 across a broad temperature sweep;
Fig. 11 is a schematic circuit diagram of an Infra-Red (IR) sensor in accordance with an embodiment of the present invention;
Fig. 12 is a schematic block diagram of a vehicle sensor or detector in accordance with an embodiment of the present invention; Fig. 13a is a perspective view of a vehicle sensor enclosure in accordance with an embodiment of the present invention;
Fig. 13b is a cross-sectional view of the vehicle sensor enclosure of Fig. 13a;
Figs. 13c and 13d are perspective views of a vehicle sensor enclosure in accordance with another embodiment of the present invention;
Fig. 14 is a flowchart of a method for detecting vehicles using AMR and IR sensors in accordance with an embodiment of the present invention;
Fig. 15 is a flowchart of method for detecting vehicles using AMR and IR sensors in accordance with another embodiment of the present invention; Fig. 16 is an architectural block diagram of a parking management system in accordance with an embodiment of the present invention; and
Fig. 17 is a flowchart of a method for sensor communications in a wireless network in accordance with an embodiment of the present invention.
Detailed Description
Embodiments of the present invention relate to a particular solution of the detection accuracy/battery life trade-off in vehicle detection methods and systems. Of the various miniature, battery-operated technologies that are available to sense or detect vehicles, two candidates have emerged as most suitable: magneto-resistive sensors and active ("lidar") infra-red detectors.
Magneto-resistive sensors comprise silicon chips having a thin-film resistive strip of nickel-iron alloy. When a magnetic field is applied to the sensor, the resistance of the strip changes, which can be measured as a change in an applied voltage or current (depending on circuit configuration). Magneto-resistive sensors exhibit several advantages, including: • magneto-resistive sensors can be produced cheaply and efficiently as silicon chips, using standard silicon manufacturing processes; magneto-resistive sensors are highly sensitive and, when configured correctly, can detect even subtle changes in an applied magnetic field; magneto-resistive sensors can be operated with very little current and thus provide a very good battery life operation.
Magneto-resistive sensors are typically operated as threshold detectors in vehicle detection applications. A vehicle moving in the vicinity of a magneto- resistive sensor causes a change in the magnetic field strength around the sensor, which, in turn, causes a corresponding change in resistance of the sensor. When the magnitude of this resistance change exceeds a threshold, a vehicle is said to be present. Conversely, when a vehicle is known to be present, a super-threshold resistance change is said to indicate the vehicle's departure. Difficulty lies in selecting a threshold value to both maximise the probability of detection and minimise the probability of false positives (i.e., determining that a vehicle has arrived when it hasn't, or determining that a vehicle has departed when it hasn't). Furthermore, magneto-resistive sensors suffer from a variety of problems: magneto-resistive sensors are extremely sensitive to shifts in the earth's baseline magnetic field, and need continual re-calibration; magneto-resistive sensors are extremely sensitive to temperature drift, and need continual re-calibration. Temperature calibration is non-trivial, since the relationship is highly non-linear, magneto-resistive sensors detect vehicle movements by way of magnetic field changes and can be fooled by other objects that alter magnetic fields such as magnets and large metallic objects (e.g., garbage dumpsters); magneto-resistive sensors are inherently omni-directional and cannot easily be focussed in a particular direction; and • vehicles alter magnetic fields, not only by virtue of their metallic components but also through the magnetic fields generated by their engines and/or other equipment. Depending on the vehicle type, make and model, as well as the vehicle's orientation with respect to the sensor, this can either amplify or reduce the change in detectable magnetic field strength.
Because of these and/or other problems, in spite of application of advanced signal processing techniques, it is doubtful whether the magneto- resistive sensor can ever achieve the detection accuracy levels necessary for commercial success.
In contrast, vehicle detection using active infra-red sensors is relatively simple and effective. An active infra-red (IR) sensor comprises an IR light emitting diode (LED), which emits infra-red light, and a photodiode to detect the reflected IR light. To detect a vehicle (or any solid object), the LED is made to emit short pulses of IR light in a focused beam. If a solid object is located anywhere in the beam's path, some of the IR light gets reflected back towards the emitter. The photodiode detector is situated next to the LED emitter; when reflected IR light coincides with the photodiode, the photodiode detector produces a voltage or current that can be measured. Hence, whenever a significant amount of IR light is detected following an emitted pulse, the presence of an object (vehicle) can be inferred; likewise, if no reflected energy is detected, there is no object in the IR sensor's field of view.
Active IR detection method solves many of the problems inherent in magnetic detection: temperature drift has a significantly lower effect on performance; • only objects directly in the IR sensor's field of view are detected. The IR pulse can be focused and aimed to detect objects within a particular region, and thus would not be fooled by vehicles in adjacent spaces; and detection depends on the position of a vehicle only and not on the state of a vehicle (on or off) or it's size.
However, active IR detection poses its own set of difficulties: compared with the magnetic detection, IR LED emitters draw a relatively high current;
IR sensors are usually operated in pulse mode with a low duty-cycle to minimise power consumption. This results in a loss of temporal resolution, as only vehicle movements lasting longer than one duty cycle (typically 3 seconds minimum) can be detected. In parking applications, particularly, this can result in critical errors; changes in ambient light levels can affect sensitivity, and require continual re-calibration; ambient IR light can trigger a false detection; and
IR lenses require continual cleaning, as dirt, debris, and acts of vandalism can all cause the lens to become blocked.
Embodiments of the present invention combine a magneto-resistive sensor with an active IR sensor, and provide a set of algorithms that exploit the positive qualities of each, while minimising the effect of the negative qualities. This enables production of a small, self-contained, battery-powered sensor node with high detection accuracy and low latency, and enough battery life to last several years on a single charge. Fig. 1 shows a sensing element 100 for use in an Anisotropic Magneto- Resistive (AMR) sensor. The sensing element 100 comprises a thin layer or thin film of nickel iron (Ni Fe) permalloy 110 having metal contacts 130, 135 at each end and mounted on a silicon substrate 120. The NiFe permalloy thin
5 layer 110 undergoes a directional or anisotropic change in resistance according to the intensity of a magnetic field applied in the directions indicated by arrows 150, which causes current flow in the direction indicated by arrows 140. The sensing element 100 has excellent linearity with magnetic field, along with enough sensitivity to detect vehicles. Linearity is within 0.1 % of fullo scale in a measurement range of +/- 1 Gauss.
The sensing element 100 is capable of measuring the earth's magnetic field, which is a static ambient magnetic field of value upwards of 650 milli- Gauss, depending on geographical location. When a large ferrous object enters this static field, it distorts the field and generates a change in resistances in the sensing element 100. This change is in the order of 15 milli-Gauss at a range of about 5ft or about 1.5m. Fig. 2 shows magnetic flux distortions 230 caused by entry of a ferrous object 200 into a static magnetic field 210.
A number of difficulties or complications need to be taken into account in0 relation to the sensing element 100. Firstly, the earth's magnetic field is very large when compared to the change in magnetic field (or inductance) that a vehicle might produce. For example, the lowest value of the earth's static magnetic field is of the order of 650 milli-Gauss, yet a typical change in magnetic field generated by a vehicle at about 1.5m is only about 15 milli-5 Gauss. Secondly, the sensitivity of the sensing element 100 is nominally
1 mV/mA/Gauss. Translating a 15 milli-Gauss change into a signal produces
18uV. Thirdly, the sensitivity of the sensing element 100 to an induced magnetic field varies with temperature. For example, the Honeywell HMC1052
AMR datasheet specifies a -600 parts-per-million temperature coefficient ofo sensitivity. Fig. 3 shows a high-level diagram of a single channel AMR sensor 300. It should be noted that there are two axes of measurement, which are orthogonal to each other.
The sensor 300 comprises: an AMR bridge sensor element 310 (similar to or the same as the sensing element 100 of Fig. 1 ), a voltage reference 320, a current source 330, a strap driver 340, a digital potentiometer 350, and two amplifier stages 360 and 370.
The voltage reference 320 provides an accurate and low temperature coefficient reference point for the surrounding analog circuitry. The current source 330 provides immunity against sensitivity drift. As temperature increases, the resistance of the bridge sensor element 310 changes, which causes a change in current flow. The differential amplifier 360 minimises common-mode noise generated by the bridge configuration of the bridge sensor element 310 and is selected for low noise, low input offset voltage, and low input offset drift. The function of the differential amplifier stage 360 is to amplify the very small voltage changes generated by the bridge sensor element 310 into larger useable signals. The digital potentiometer 350 and related offset control algorithm enable the amplifier 370 (the final gain stage) to zoom in on the signal (essentially providing a form of automatic gain control), which dramatically increases the dynamic range of the output of the bridge sensor element 310.
In operation, the sensor element 310 is reset via a strap driver circuit 340 and then an analog-to-digital converter (not shown in Fig. 3) measures the low-gain signal 365 at the output of the differential amplifier 360. A microcontroller (not shown in Fig. 3) uses the measurement from the analog- to-digital converter to determine a value for outputting to the digital potentiometer 350, which offsets the first amplifier stage 360. The second amplifier stage 370 provides a high gain output 375 of a small selected window of the full range of possible signals. The use of high gain and 'zooming in' on the signal enables successful detection of vehicles based on measured changes in the magnetic field. The strap driver circuit 340 utilises an internal resistive strap that toggles the sensing polarity and flushes any remnant flux before/after sensing. By applying a short duration high-current pulse to the strap, accumulated flux can 5 be removed to provide an accurate reading.
Fig. 4 is a circuit diagram showing the strap driver circuit 340 of Fig. 3 for applying a set/reset pulse to the bridge sensor element 310. Referring to Fig. 4, when the AMR_RSP signal 410 is asserted while the AMR_RSM signal 420o is in the reset state, a positive-going current pulse 430 will be generated and applied to the internal strap of the AMR sensor. This pulse typically has amplitude of ~600mA and decay of 2uS. When the AMR_RSP signal 410 and AMR_RSM signal 420 are reversed, the current 'spike' 435 flows in the opposite direction. 5
The magnetic domain orientations through set/reset of the bridge sensor element 310 are illustrated in Fig. 5.
Fig. 5a shows a permalloy (NiFe) magneto-resistive element 510 exhibiting random magnetic domain orientations 521 , 522, 523 ... o Fig. 5b shows the permalloy (NiFe) magneto-resistive element 510 of Fig
5a after a 'set' pulse has been applied by the strap driver circuit 340 of Fig. 3.
As may be seen from Fig. 5b, the magnetic domain orientations 530 are from left to right along the easy axis 540, which is orthogonal to the sensitive axis
550. 5 Fig. 5c shows the permalloy (NiFe) magneto-resistive element 510 of Fig
5a after a 'reset' pulse has been applied by the strap driver circuit 340 of Fig.
3. As may be seen from Fig. 5c, the magnetic domain orientations 560 are from right to left along the easy axis 540, which is orthogonal to the sensitive axis 550. 0 Use of the strap driver circuit 340 provides a relatively more accurate measurement of magnetic field that is generally independent of prior magnetic influence. Fig. 6 is a circuit diagram showing the voltage reference 320 of Fig. 3. Referring to Fig. 6, the output 610 of the voltage reference integrated circuit 620 is divided by the potential divider comprising resistors R101 and R103 to create a half-reference 630, which is buffered by the integrated circuit 640 to provide a buffered output 650. The calculations below show computation of the worst-case deviation of the voltage reference:
Vref = 2.5V (nominal) Temperature Coefficient: 20 PPM
Accuracy: 0.4%
Deviation from nominal (+/- 60 degrees)
= 2.5V * ((+/-) 0.004 (+/-) 60 * 20 * 10Λ-6) = (+/-) 13mV
Thus, the projected deviation of the half reference is: Vref / 2 = Y2 * (+/-) 13mV = 6.5mV
Adding in worst case temperature and tolerance effects of the voltage divider provides a good estimate of the maximum deviation of Vref / 2 with temperature and tolerance:
Resistance (nominal) = 499K Tolerance = 0.5%
Temperature Coefficient = 25PPM Resistance Deviation
= 499K * ((+/-) 0.005 (+/-) 60 * 25 * 10Λ-6)
= 3243.5 ohms
Mismatch of voltage divider
= (+/-) (499K + 3243.5) / (499K) - 1 = +/- 0.0065
Thus, Vref/ 2 = 1.25V +/- (0.0065V + 0.008125V)
Conclusion: Vref can be 2.5V (+/-) 13mV
Vref / 2 can be 1.25V (+/-) 14.625mV
Fig. 7 is a circuit diagram showing the current source 330 of Fig. 3, which provides a stable constant current through the bridge sensor element 310. It is instructive to analyse current drift, since sensitivity of the bridge sensor element 310 is proportional to current flow. The operational amplifier (op-amp) 710 uses negative feedback from the emitter of the transistor 720 to set the current flowing from the bridge sensor element 310. The op-amp 710 will attempt to force the voltage at its inverting input to match the voltage at the non-inverting input, thus effecting a constant voltage across resistor 730. A constant voltage across a constant resistance yields a constant current. The calculations below show computation of variation in the non-inverting input, input offset, drift, and the current setting resistor. This yields a current variation over tolerance and temperature, which ultimately yields a sensitivity variation that can be used in the detection algorithm:
V+ = Vref * ( R91 / R88 + R91 )
R88 = 499K * (1 (+/-) 0.005) * (1 (+/-) 60 * 25 * 10Λ-6) = 499K (+/-) 3247.24 ohms
R91 = 49.9K (+/-) 324.724 ohms
V+ = (2.5V (+/-) 0.013V) * [(49.9K (+/-) 324.72) / (499K (+/-) 3247.24 + 49.9K (+/-) 324.72]
= 0.22727V +/- 3.45mV Now, considering an input offset voltage of +/- 5mV:
VR92 = 0.22727V +/- 8.5mV
Current through the bridge sensor element is VR92 / 180 ohms.
Considering tolerance alone, the resistor can be about +/- 1 ohm. Accordingly:
lbridge = (0.22727(+/-) 8.5mV/180(+/-) 1 ) = 1 .2626mA +/- 55uA
The sensitivity of the bridge sensor element is nominally 1 mV / mA / Gauss. It should be noted that this sensitivity rating has its own +/- 20% tolerance, which is significantly higher than the current source variation. This means that there is no way to make sensitivity any more predictable upon start-up. Therefore, a worst-case sensitivity of 0.8mV/mA/Gauss must be assumed for calculating detection at the target range.
Fig. 8 is a circuit diagram of the analog front-end of the embodiment shown in Fig. 3. In order to increase low (typically milli-volt) signal levels, it is necessary to use a high gain differential amplifier 360 to read the bridge sensor element 310. It is important to offset the differential amplifier integrated circuit 810 via the digital potentiometer 350, in order to be able to acquire useable signals off of the high gain stage 370 formed by the integrated circuit 820. The bridge sensor element 310 has two types of offsets: electrical and magnetic. These offsets must not saturate the first gain stage 360, which requires calculation to select an appropriate gain. Firstly, the electrical offset is due to manufacturing tolerances and cannot be avoided; for the HMC1052, this offset is specified at 1.25mV with a temperature coefficient of 10 PPM. Therefore, within the desired temperature range, the offset can be (+/-) 1.85mV. Secondly, the magnetic offset induced by the earth's magnetic field must be accounted for. This value is known to be nominally around +/- 650 milli-Gauss. The maximum sensitivity over temperature is assumed (given - 600PPM from specifications) when calculating this offset, as shown:
Sensitivity (S) = 1.2mV/mA/Gauss * (1 + 600 * 60 * 10Λ-6) = 1.2432mV/mA/Gauss
Thus, the maximum static offset due to a magnetic field: = [(+/-) 0.650 * 1.2432mV*1.3176mA] = +/- 1.065 mV
Thus, the total possible offset from the bridge sensor element over temperature is +/- 2.92mV. There is an extremely small input offset of 5uV for the op-amp stage, along with 2nV/degree Celsius offset drift, and this can therefore be ignored. The +/-2.92mV figure can thus be rounded to 3mV for safety. Upon calibration, an offset of 1.25V is written to the high gain stage, which enables uni-polar operation of our circuitry. In order to offset the field, the offsets multiplied by the gain need to be less than the measurement range. Taking a single side, maximum gain can be calculated as 1.25V / 0.003V = 416. A gain of 200 is thus suitable, yielding a high safety margin. This minimises the risk of possible external magnetic sources saturating the sensor.
Filters in the feedback path are optimised for quick start-up, rather than noise immunity. Noise filtering is performed in the digital domain and averaged, since the primary noise source is white.
The second gain stage is designed to give a gain of 20, which was determined experimentally by computing the total expected vehicle change at the maximum sensitivity multiplied by a gain to fall within the required analog- to-digital (ADC) range. An algorithm for detecting vehicles using the magneto-resistive sensor 300 is as follows:
POWER UP FROM SLEEP • In shutdown mode, all AMR_CTRL, PWR_CTRL1 , PWR_CTRL2 signals must be kept high. During microcontroller reset, these pins are pulled high with resistors, since the general purpose input/output ports are floating during sleep.
Reset/Set (to flush out residual flux from the sensor) • Read temperature sensor and store the temperature as (for testing): t(degrees Celcius) = (((((2.5/1024)* ADC_Reading)/2) - 0.424) / 0.00625)
INITIAL CALIBRATION (Must be in Set mode)
Write initial 1.25V offset to digital potentiometer • Perform a Reset/Set
Sleep until settled (20OuS for calibration to ensure best possible signal) Read Low Gain AMR sensor outputs (sample at least 50 times and average value for noise immunity) Calculate the final written offset as [ 2.5V - (#4 value)] for each channel, then write offset into digital potentiometer's volatile and non-volatile memory. This calibration should not be changed unless the sensor is reinstalled at another location, or readings are constantly out of range on the ADC (rare error). Note that the value written can only be precise to 2.5V / 256 steps due to limited resolution of the digital potentiometer. • Read the high gain channels (at least 50 times), then calculate RMS value, store the RMS, axisi and axis2 values.
Optionally, as a sanity check, ensure that the actual low gain outputs are close to 1.25V (- +/- 1OmV)
RESET / SET
2OuS must have elapsed from the assertion of AMR wakeup in order to apply the reset signal. Bring RESET_P Signal High and RESET_N Signal Low Sleep ~20uS
Bring Reset_P Signal Low and RESET_N Signal High Sleep ~150uS (before any valid reading from high or low channels) Leave in this state
SUMMARY (AFTER CALIBRATION):
Wake up (AMR PFET low)
Wait 2OuS • Reset
Wait 2OuS
Set
Wait 15OuS
Sample high gains (At least 36 times, but would work better if higher (depends on power budget)
Compare sample (RMS | AXIS1 | AXIS2) to threshold
More advanced algorithms that take into account temperature drift are possible, for example, through time domain analysis of the signal. The fact that an incoming vehicle will appear as a transient and temperature change will appear as a slowly changing DC bias will make the algorithm work exceptionally well. A simple moving average filter, which is a type of FIR filter, is used to provide a slowly changing value to make comparisons with.
Fig. 9 shows the sensitivity change (Y-axis) as a function of temperature
(X-axis) for the sensor. A small environmental unit was constructed to sweep the temperature of the sensor printed circuit board (PCB) and a Peltier device (digitally controlled heat pump) was thermally coupled to the sensor PCB to produce this graph. As can be seen, sensitivity has a negative coefficient of change as specified. Interestingly, rather than the -600 PPM projected, a roughly -1000 PPM curve is seen; this is due to the effects of the support circuitry in combination with the inherent drift of the device.
Fig. 10 shows high level gain across a broad temperature sweep. The direction of the curve is not of much significance since the direction of the magnetic field is not known a priori.
A void around room temperature was introduced in the graphs of Fig. 9 and Fig. 10 on account of magnetic field influence of the Peltier device when powered.
In contrast to the magneto-resistive sensor, the IR technology provides a simpler and cheaper way to minimise both missed detections and false alarm errors. There are, however, some limitations for outdoor applications using IR technology.
The composition of sunlight includes visible light, waves in the UVA, UVB and UVC ranges, and waves in IR range. Therefore, sunlight may falsely trigger an IR receiver. Embodiments of the present invention use a special IR transmitter with pulse-width modulation (PWM) at a centre frequency of 455 KHz. The received IR signal is then filtered to that the IR receiver is triggered only by light at 850 nm wavelength and modulated IR at 455 KHz through the use of a tuned band-pass filter, automatic gain control, and a demodulator. Other protection mechanisms are also included, such as only triggering the IR receiver for a specified period of time (70 us after IR LED is driven). These measures prevent or reduce false triggering of the IR receiver due to ambient IR light.
Most IR applications are indoors and are in relatively dimly lit environments. To be effective in well-lit outdoor environments, a high power IR LED with very narrow emission angle (±3 °) and very high radiant intensity is required. Furthermore, the duty cycle of the pulse width modulation is adjusted to balance between the life of the battery and the power of the IR LED. Table 1 , below, shows specifications for one particular IR LED emitter and receiver pair:
Figure imgf000020_0001
TABLE l
Fig. 11 is a schematic circuit diagram of an Infra-Red (IR) sensor or detection circuit.
Referring to Fig. 11 , the IR receiver comprises a PIN photo diode D9, with an initial trans-impedance stage followed by a third-order bandpass filter tuned to 455 KHz. This significantly minimises false triggers due to external sources. Therefore, the frequency of pulse-width modulation (PWM) for driving the IR LED transmitter D10, D12 has to be close to 455 KHz, and the time period for driving the IR LED transmitter D10, D12 is about 25us (>22us and <500us).
As the IR LED transmitter D10, D12 (SFH4550) requires a high current which the battery cannot provide, a bank of capacitors C26, C19, C20 and C22 act as short-term storage devices for supplying the required current. The capacitors C26, C19, C20 and C22 store energy from the battery and provide power for driving the IR LED at high current. Thus, before driving the IR LED transmitter D10, D12, current has to be pulse-width modulated into transistor Q2 to charge the capacitors C26, C19, C20 and C22. Then transistor Q2 is switched off, and the IR LED transmitter D12, D12 is driven for 25us at 455 KHz.
The sequence of operation for operating the IR sensor/detector is as follows:
Switch on Q2, charge capacitors for providing power to drive IR LED Once capacitors are fully charged, switch Q3 for powering IR receiver Drive the IR LED 70us at 455 KHz
Check the output of the IR receiver. If it is low, then a vehicle is detected, otherwise, no vehicle is detected. • After 25us, the whole operation is complete
Performance of the individual magneto-resistive (AMR) and infra-red (IR) sensors has been optimised for vehicle detection by careful design, as described hereinbefore. However, even with the optimisations described, the performance of each type of sensor operating alone is considered insufficient for effective commercial deployment of battery powered vehicle detection sensors or nodes. In particular, the AMR sensor suffers from high sensitivity and is prone either to a relatively high false alarm rate (i.e., a high rate of false positives) or a high miss rate. The IR sensor on the other hand, while providing a highly accurate detection rate, suffers from high current consumption resulting in reduced battery life of the sensor. To exploit the strengths of both sensors, while minimising their shortcomings, the present inventors have combined the two sensors to provide a method and apparatus for detecting vehicles with high accuracy and low average current consumption.
Fig. 12 shows a block diagram of a vehicle sensor or vehicle sensor node 1200 in accordance with an embodiment of the present invention. The vehicle sensor 1200 is a completely self-contained, battery-operated apparatus capable of communicating to an external access point via a secure wireless network. Vehicle detection is performed using two main sensors (AMR and IR), as described hereinbefore, with optional auxiliary sensors used to calibrate and refine the detection routines.
Referring to Fig. 12, the vehicle sensor 1200 comprises a circuit board and the following main components:
An RF or wireless transceiver 1210. The Semtech XE1203F RF transceiver was selected for this particular embodiment and is operated at 868 / 915 MHz (Frequency Hopping Spread Spectrum). A separate RF or wireless transmitter and receiver may be practiced in alternative embodiments.
A RF antenna 1220. A circuit board-mounted Splatch quarter-wave monopole antenna was selected for this embodiment.
A microcontroller 1220 with on-board memory. The 8-bit Renesas
H8/38076 microcontroller with 52K Flash and 2K RAM was selected for this embodiment.
An AMR sensor 1240, such as the AMR sensor described hereinbefore with reference to Fig. 3. The two-axis Honeywell HMC1022 sensor was selected as the bridge sensor in this embodiment.
A temperature sensor 1250.
Batteries 1260. Two "C"-type Saft LS26500 Lithium-Thionyl-Chloride batteries were selected for this embodiment. • An IR sensor 1270, such as the IR sensor described hereinbefore with reference to Fig. 11.
A light sensor 1280.
The vehicle sensor 1200 is preferably housed in a durable, weather- proof, impact-resistant enclosure. Since the sensor must be capable of withstanding occasional direct impact from a vehicle, the enclosure must comprise an extremely strong material. In addition, the material must be non- ferrous, so as not to compromise the communication effectiveness, or mask the magnetic fields measured by the AMR sensor. Two materials are used in construction of the sensor enclosure: a Lexan polycarbonate, and a Xenoy glass-filled nylon, both of which have extremely high strength to weight ratios.
One embodiment of the sensor enclosure is shown in Figs. 13a and 13b.
The enclosure was designed with a particular focus on easing installation effort and reducing labour costs. The sensor comprises a two-part assembly: a base 1310, which is installed in a pre-drilled hole in the pavement and adhered to the pavement using hot asphalt / bitumen or other adhesives; and a dome 1320, which fits to the base 1310 and is secured with a tamper-proof screw down the centre 1330. In practice, an entire car park could be installed with sensor bases 1310 in advance, and the more expensive sensor domes containing all the electronics could be installed at a later date. In addition, the two part assembly advantageously assists maintenance when compared to existing sensors, which must be removed from the pavement by digging the sensor out the asphalt itself. The two-part assembly enables a faulty sensor to be replaced simply by unscrewing and removing the faulty dome portion 1320 with a proprietary torque wrench, and replacing with a new dome portion.
Another embodiment of the sensor enclosure avoids the use of a centre screw entirely, by shaping the dome and base in such a way that the dome screws or locks into the base directly by simply twisting the dome. For example, the dome shaft may be shaped with corkscrew grooves around the perimeter, with the base having complementary protrusions or shapes. Furthermore, the dome can be designed to be removed only by means of a proprietary tool to generally restrict removal of the dome. However, the shape would still need to provide a high degree of strength and impact resistance. A pattern of holes on the top of the dome could be used as a receptacle for a proprietary torque-wrench tool.
There are certain instances in which drilling even a shallow hole in the pavement is not possible. For example, concrete coring is prohibitively expensive and coring in a steel surface is not feasible. For those situations, a different "surface-mounted" base 1340 has been developed that accommodates the same dome 1320, as shown in the embodiment of Figs. 13c and 13d. The surface mounted base 1340 is mounted on the pavement surface, and is secured using concrete bolts and/or adhesive. The dome assembly 1320 is identical to that for the in-ground base 1310.
Fig. 14 is a flowchart of a method for detecting vehicles using an AMR sensor and an IR sensor. The method of Fig. 14 is described assuming an initially vacant parking bay. However, operation beginning with a parking bay in the occupied state is substantially similar.
The output of the AMR sensor is sampled at step 1410 to detect occupancy or presence of a vehicle based on variations in a magnetic field, in this instance, the earth's magnetic field.
At step 1420, a determination is made whether the sampled value has changed by more than a predetermined threshold compared to the previous sampled value or a combination of previously sampled values (e.g., a moving average). If not (NO), processing returns to step 1410 after a predetermined time delay (sleep interval) at step 1425. On the other hand, if the sampled value has changed by more than the predetermined threshold (YES), thus indicating presence of a vehicle, the IR sensor is activated at step 1430.
At step 1440, a determination is made whether a reflected IR message is successfully detected. If not (NO), the IR sensor is deactivated at step 1445 and processing returns to step 1410 after a predetermined time delay (sleep interval) at step 1425. If a reflected IR message is successfully detected (YES), the IR sensor is deactivated at step 1450 and vehicle detection or occupancy is confirmed and/or output at step 1460.
Activation of the IR sensor at step 1430 is preferably performed immediately prior to checking occupancy or presence of the vehicle using infra-red detection to conserve power. Similarly, deactivation of the IR sensor at step 1445 is preferably performed immediately after checking occupancy or presence of the vehicle using infra-red detection to conserve power.
By altering parameters such as the AMR threshold, the "sleep" interval length, and the emitted power of the IR LED transmitter, a continuum of operating set points can be achieved that trade off between detection accuracy, latency, and battery life. For example, with a low AMR threshold, detection accuracy can be improved by operating the IR detector more frequently (i.e., a shorter time delay or sleep interval). However, the trade-off for this increased level of detection accuracy is a reduction in battery life. Similarly, reducing the sleep interval can improve latency, but also at the expense of battery life. However, providing a long sleep interval with low AMR threshold can result in high accuracy and long battery life, at the expense of latency. Which operating point to use depends on the specific application. For example, a local parking guidance application might require extremely low latency with medium battery life and accuracy, whereas a parking enforcement application would require extremely high accuracy, with only moderate latency.
Fig. 15 is a flowchart of another method for detecting vehicles using an
AMR sensor and an IR sensor. The method of Fig. 15 is described assuming an initially occupied parking bay. However, operation beginning with a parking bay in the vacant state is substantially similar. Furthermore, in the method of Fig. 15, a discrepancy between the AMR and IR sensors is identified as an "error" state. This could be useful in cases where there is a high risk of vandalism or interference, wherein one of the two sensors is unable to function accurately. For example, the IR lens could become covered, causing a vehicle exit to go undetected. With the method of Fig. 15, the error would be detected, and an enforcement officer or other person could be dispatched to clean the lens.
Referring to Fig. 15, the output of the AMR sensor is sampled at step 1510.
At step 1520, a determination is made whether the sampled value has changed by more than a predetermined threshold compared to the previous sampled value or a combination of previously sampled values (e.g., a moving average). If not (NO), processing returns to step 1510 after a predetermined time delay (sleep interval) at step 1525. On the other hand, if the sampled value has changed by more than the predetermined threshold (YES), thus indicating absence of a vehicle, operation of the IR sensor is activated at step 1530 to confirm absence of the vehicle (vacancy).
At step 1540, a determination is made whether a reflected IR message is successfully detected. If so (YES), the IR sensor is deactivated and an error condition is output at step 1645 to indicate that the AMR and IR sensors have output a differing detection result. Thereafter, processing returns to step 1510 after a predetermined time delay (sleep interval) at step 1525.
If a reflected IR message is not detected (NO), the IR sensor is deactivated at step 1550 and vehicle vacancy status is confirmed and/or output at step 1560.
Further to the methods described hereinbefore with reference to Figs. 14 and 15, a broad embodiment of the present invention provides a method for detecting vehicles that comprises the steps of: detecting presence of a vehicle based on variations in a magnetic field; checking presence of the vehicle using infra-red detection if presence of the vehicle was detected based on magnetic field variations; and outputting an indication of presence of the vehicle if the infra-red detection confirms presence of the vehicle. The magnetic field may be the earth's magnetic field. Presence of the vehicle may be detected if a variation in the magnetic field exceeds a predetermined threshold. The method may comprise the further steps of: activating the infrared detection immediately prior to checking presence of the vehicle; and deactivating the infra-red detection immediately after checking presence of the vehicle to conserve power. The step of outputting an indication of presence of the vehicle may comprise the steps of: activating a wireless transmitter; transmitting, via the wireless transmitter, data representative of presence of the vehicle; waiting a predetermined time period for a signal acknowledging receipt of the data; and de-activating the wireless transmitter after receipt of the acknowledgement signal. The method may comprise the further step of resending the data if the acknowledgement signal is not received within the predetermined time period. The method may be performed by a battery- powered apparatus.
The magneto-optical vehicle sensors and methods described herein are useful for many applications where vehicle detection is required. Such applications include, but are not limited to: Parking guidance: Real-time parking information can be displayed on electronic maps such as Google Maps or on satellite navigation devices, directing motorists to nearby available spaces, whether on-street or in an off-street parking area. Once in a parking structure or area, variable message signs and LED indicator lights can be used to direct motorists to unoccupied parking bays quickly and efficiently. Policy enforcement: Real-time information can be used to identify vehicles that are in violation of parking policies. This includes: vehicles that overstay a set time limit; vehicles that fail to pay a parking fee; and vehicles that do not have a required permit. In addition, strict access control can be implemented by the additional use of electronic ID tags. Traffic management: The magneto-optical vehicle sensors and methods described herein can be used to monitor the speed, volume and direction of traffic in laneways, streets, and highways. Data from the sensors can be used to support traffic analysis, and variable message signs and other displays can be used to manage traffic flows and provide real-time feedback to drivers. Electronic ID tags can be used to allow drivers to pay tolls according to driving distance, which can be measured on a very precise scale. Yield management: Analysis of historical trends can help owners of a parking asset maximise the return on the cost of the asset by optimising its ongoing revenue and cost streams. Analysis can include evaluation of and extrapolation from historical trends, as well as more advanced prediction modelling that takes into account complex relationships between multiple variables.
Labour force management: Analysis of historical trends can aid in the efficient deployment of labour to reduce costs while maximising revenues. Labour and other resources can be allocated efficiently by extrapolating and predicting needs from historical trends; in addition, predicted needs can be compared to actual deployments to determine labour force efficiency. Operational management: Real-time information can help parking managers and traffic analysts make quick, well-informed operational decisions. Models based on historical trends can enhance these decisions by providing recommendations based on optimal desired outcomes. Managers can also remotely monitor operations from offsite locations (through the web service), and set up real-time alerts through email, SMS, and other communication devices. Finally, managers can also control some operations remotely, such as updating variable message signs and reassigning enforcement policies.
Applications such as those described above require a distributed system architecture. Such systems generally comprise: apparatus and a method to communicate data to and from multiple vehicle sensors to a common location; • apparatus and a method to process the data at the common location, and generate control signals and/or provide other required interfaces for the vehicle sensor data; and peripheral devices and apparatus and a method for communicating between the peripheral devices, the vehicle sensors, and the common location.
A particular embodiment of such a system is described hereinafter. However, those skilled in the art will appreciate that numerous alternative embodiments are possible.
Fig. 16 shows a schematic block diagram of a parking management system 1600 that includes vehicle sensors according to an embodiment of the present invention.
The parking management system comprises a Local Facilities Management Computer 1610, LEDs 1622, 1624..., message signs 1632,
1634... and vehicle sensors 1642, 1644.... The LEDs 1622 and 1624, message signs 1632 and 1634 and vehicle sensors 1642 and 1644 are electrically and communicatively coupled to the Local Facilities Management Computer 1610 by way of an LED bridge 1620, a message sign bridge 1630 and a vehicle sensor bridge 1640, respectively. The various bridges provide an intermediate level of sub-system device management and may comprise programmable logic controllers.
The Local Facilities Management Computer 1610 is adapted to control the LEDs 1622, 1624... in accordance with data received from the vehicle sensors 1642, 1644... to indicate occupancy status of individual parking bays (i.e., occupied or vacant). Those skilled in the art will appreciate that other indicator lights (e.g., incandescent, fluorescent or halogen lights) may be alternatively used in place of LEDs.
The Local Facilities Management Computer 1610 may further be adapted to control the message signs 1632, 1634... in accordance with data received from the vehicle sensors 1642, 1644.... Such message signs may, for example, comprise LED or incandescent bulb panels, LCD displays, back- lit projection boxes, organic LED displays, cathode ray tube screens, digital light projected displays, or any other programmable electronic variable message display.
The Local Facilities Management Computer 1610 may be communicatively coupled to other systems 1650. Such other systems may include, but are not limited to: billing and reporting systems, GPS navigation systems, mapping information systems such as Google Maps®, mobile information systems such as XM satellite radio, portable digital information systems such as mobile telephones and personal digital assistants (PDAs), desktop computers, remote displays such as off-site message signs, on- and off-site payment systems such as parking meters, pay and display terminals, telephone billing systems, online payment systems and online space reservation systems. Such coupling may, for example, be via a dedicated connection or a network such as a local area network (LAN), a Wide Area Network (WAN) or the Internet. ID tags 1660, such as Radio Frequency Identification Tags, may be detected and read by the vehicle sensors 1642, 1644 to uniquely identify vehicles or occupants of vehicles. The vehicle sensors 1642 and 1644 communicate with the sensor bridge 1640 via a wireless communication link in a star topology. In other words, each of the sensors 1642 and 1644 communicate directly with the sensor bridge 1640, but the sensors 1642 and 1644 never communicate directly with each other. Since the sensors 1642 and 1644 are battery operated and are required to last for more than 5 years on a single charge, the communication is necessarily performed using extremely low power. To save power, the radio sub-system is turned off when not in use. To avoid the overhead and latency of network co-ordination (for example, using a round-robin or token passing protocol), the sensors use a contention-based "push only" protocol, in which each sensor transmits data packets whenever it has new information to communicate. Thus, in this embodiment, only a sensor can initiate a communication - the sensor bridge cannot communicate with a sensor at will, rather only in response to a message from the sensor.
Those skilled in the art will appreciate that embodiments of the parking management system may be implemented without the LEDs 1622, 1624... and/or the message signs 1632, 1634... Furthermore, embodiments of the parking management system may be implemented without one or more of the message sign bridge 1630, the LED bridge 1620, and/or the vehicle sensor bridge 1640.
Fig. 17 is a flowchart of a method for a sensor to communicate via a wireless network. For example, referring to Fig. 16, the vehicle sensors 1642 and 1644 may wirelessly communicate with the Local Facilities Management
Computer 1610 via the vehicle sensor bridge 1640 using the method of Fig.
17.
Referring to Fig. 17, a sensor activates its internal radio transceiver when wanting to communicate at step 1710. The sensor transmits a data packet at step 1720 and then waits a predetermined time at step 1730 for receipt of an acknowledge (ACK) signal. If an acknowledge (ACK) signal is not received (NO) at step 1740, the sensor waits for a random time delay period at step 1745 before returning to step 1720 to re-transmit the current data packet.
If an acknowledge (ACK) signal is received (YES) at step 1740, the sensor de-activates the radio transceiver at step 17850 until another data packet needs to be sent.
Those skilled in the art will appreciate that alternative communication schemes are possible, including mesh-type schemes wherein sensors relay data from other sensors towards the access point, and routes are computed dynamically as needed, as well as co-ordinated schemes such as round-robin schemes or slotted schemes that co-ordinate transmission windows among nodes.
There are numerous ways to implement the sensor bridges in the parking management system 1600, including:
A designated sensor node acts as a coordinator node, and communicates with all other nodes.
A specially designed "access point" communicates with all sensors in its vicinity, and possesses extra computing power and memory to perform advanced coordination functions. This node could be battery powered or line powered and could be situated in the pavement, or mounted on a light pole or on the side of a building, or inside a building.
A computer system (e.g. a PC) inside a building or other structure, with a radio device capable of communicating with sensors in its vicinity
A mesh or star or other network of such devices (1-3)
The local facilities management computer coordinates peripheral devices and other data interfaces. This device could be a personal computer (PC) running application-specific software, and could have a multitude of devices connected to it. Furthermore, those skilled in the art will appreciate that the Local Facilities Management Computer 1610 could be coupled directly to the vehicle sensor bridge 1640 as a single device.
There are a vast number of devices that could be incorporated into a vehicle sensor system. In particular, indicator lights in each bay could be used to convey the occupancy of the bay from a distance (e.g., red for occupied, green for vacant). LED lights could be powered by batteries and communicate with the local facilities management computer through a wireless network, or the LED lights could receive line power and communicate through a wireline network via some kind of bus or daisy chain. Furthermore, the vehicle sensors could communicate directly with the LEDs through a wireless or wireline link.
Similarly, electronic displays can be used to provide real-time updates about space occupancy and/or other information, and can communicate wirelessly or through a wireline network. Other peripherals, such as handheld devices, satellite navigation devices, mobile phones, and numerous others could be similarly implemented. Such devices could utilise existing networks, for example the mobile phone cellular network, or WiFi for WiFi enabled devices.
The additional incorporation of ID tags and/or readers provides identification of specific vehicles or users in a parking bay, and may be useful for a variety of applications, including those already described hereinbefore. ID tags could be implemented in a variety of ways, including the use of off-the- shelf available RFID tags and readers, or the use of ID tags as devices that can communicate and pair directly with a wireless sensor. In one such implementation, the ID tags comprise a wireless transceiver of the same type as used in the wireless sensor nodes (i.e., to simplify implementation). Upon detecting a vehicle, the sensor node transmits an ID tag request message. The ID tags "listen" at regular intervals, and upon receiving a request, an ID tag transmits its unique ID message to the wireless sensor node. In another implementation, the ID tags comprise a wake-up detection circuit that, when excited with RF energy in a particular band, causes the transceiver in the ID tag to power on and transmit its ID message to the sensor node. In this implementation, the wireless sensor node transmits the requisite excitation RF energy upon detecting a vehicle. In the above implementations, the wireless sensor node forwards the ID message to the local facilities management computer.
The foregoing description provides exemplary embodiments only, and is not intended to limit the scope, applicability or configurations of the present invention. Rather, the description of the exemplary embodiments provides those skilled in the art with enabling descriptions for implementing an embodiment of the invention. Various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the invention as set forth in the claims hereinafter.
Where specific features, elements and steps referred to herein have known equivalents in the art to which the invention relates, such known equivalents are deemed to be incorporated herein as if individually set forth. Furthermore, features, elements and steps referred to in respect of particular embodiments may optionally form part of any of the other embodiments unless stated to the contrary.

Claims

Claims:
1. A method for detecting vehicles, said method comprising the steps of: detecting presence of a vehicle based on variations in a magnetic field; checking presence of said vehicle using infra-red detection if presence of said vehicle was detected based on magnetic field variations; and outputting an indication of presence of said vehicle if said infra-red detection confirms presence of said vehicle.
2. The method of claim 1 , wherein said magnetic field is the earth's magnetic field.
3. The method of claim 1 , wherein presence of said vehicle is detected if a variation in said magnetic field exceeds a predetermined threshold.
4. The method of claim 1 , comprising the further steps of: activating said infra-red detection immediately prior to checking presence of said vehicle; and de-activating said infra-red detection immediately after checking presence of said vehicle to conserve power.
5. The method of claim 1 , wherein the step of outputting an indication of presence of said vehicle comprises the steps of: activating a wireless transmitter; transmitting, via said wireless transmitter, data representative of presence of said vehicle; waiting a predetermined time period for a signal acknowledging receipt of said data; and de-activating said wireless transmitter after receipt of said acknowledgement signal.
6. The method of claim 5, comprising the further step of resending said data if said acknowledgement signal is not received within said predetermined time period.
7. The method of claim 1 , wherein said method is performed by a battery- powered apparatus.
8. An apparatus for detecting vehicles, said apparatus comprising: a magneto-resistive sensor for detecting presence of a vehicle; an infra-red sensor for checking presence of said vehicle; and a controller coupled to said magneto-resistive sensor and said infra-red sensor; wherein said controller is adapted to: detect presence of a vehicle based on variations in a magnetic field; check presence of said vehicle using infra-red detection if presence of said vehicle was detected based on magnetic field variations; and output an indication of presence of said vehicle if said infra-red detection confirms presence of said vehicle.
9. The apparatus of claim 8, wherein said controller comprises a microcontroller with on-board memory.
10. The apparatus of claim 8, wherein said magneto-resistive sensor is adapted to measure variations in the earth's magnetic field.
11. The apparatus of claim 8, wherein said controller is adapted to detect presence of said vehicle if said magnetic field variation exceeds a predetermined threshold.
12. The apparatus of claim 8, wherein said controller is further adapted to: activate said infra-red detector immediately prior to checking presence of said vehicle; and de-activate said infra-red detector immediately after checking presence of said vehicle to conserve power.
13. The apparatus of claim 8, further comprising a wireless transmitter and a wireless receiver, and wherein said controller is further adapted to: transmit, via said wireless transmitter, data representative of presence of said vehicle; and wait a predetermined time period for receipt, via said wireless receiver, of a signal acknowledging receipt of said data.
14. The apparatus of claim 13, wherein said controller is further adapted to resend said data if said acknowledgement signal is not received within said predetermined time period.
15. The apparatus of claim 8, wherein said apparatus is battery-powered.
16. An apparatus comprising a first part for permanent installation to a pavement or road surface and a second part housing an apparatus according to claim 15, wherein said second part is adapted to be removably attachable to said first part.
17. A parking management system comprising: a plurality of vehicle sensors installed in respective parking bays, said vehicle sensors comprising apparatuses according to claim 8; and a computer system coupled to said plurality of vehicle sensors; wherein said computer system is adapted to determine vehicle occupancy status of said parking bays in accordance with data received from respective ones of said plurality of vehicle sensors.
18. A parking management system according to claim 17, further comprising a plurality of indicator lights, each indicator light adapted to indicate vehicle occupancy status of a respective parking bay; and wherein said computer system is further adapted to control said plurality of indicator lights in
5 accordance with data received from respective ones of said plurality of vehicle sensors.
19. A parking management system according to claim 17 or claim 18, further comprising at least one message sign coupled to said computer system, and io wherein said computer system is adapted to control said message sign in accordance with data received from one or more of said plurality of vehicle sensors.
I 5
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