Patent Publication Number: US-2022238015-A1

Title: Parking detection sensor and parking detection method

Description:
TECHNICAL FIELD 
     The present invention relates to a parking detection sensor and a parking detection method that detect that a vehicle has been parked at a predetermined parking position in a parking area, for example. 
     BACKGROUND ART 
     In the related art, there is a parking sensor as an apparatus that detects the presence of a vehicle entering and leaving a parking lot. For example, Patent Literature (hereinafter referred to as “PTL”) 1 describes an apparatus that detects whether each parking lot in which a magnetic sensor is embedded is in a vacant state or in a parking state based on a change in magnetism between during vacancy and during parking. Further, PTL 1 describes that detection less susceptible to the surrounding environment and with high accuracy is possible by employing a hybrid system in which an infrared distance sensor and a magnetic sensor are used. 
     CITATION LIST 
     Patent Literature 
     PTL 1 
     Japanese Patent Application Laid-Open No. 2018-146560 
     SUMMARY OF INVENTION 
     Technical Problem 
     Incidentally, in parking detection using a magnetic sensor, data of three axes (X, Y and Z axes) of the magnetic sensor is used. However, reactions will also appear in data of the X and Y axes when a vehicle enters a parking lot adjacent to a parking lot in which the magnetic sensor is installed so that the parking in the adjacent parking lot may be erroneously detected as parking in the parking lot in which the magnetic sensor is installed. 
     Further, although PTL 1 proposes employing the hybrid system in which the infrared distance sensor and the magnetic sensor are used, PTL 1 does not sufficiently examine how to use measurement data of the infrared distance sensor and the magnetic sensor for performing parking determination. In addition, the infrared distance sensor utilizes light, and is therefore susceptible to stains and is not suitable for long-term installation in a parking area. 
     The present invention has been made in view of the points described above and provides a parking detection sensor and a parking detection method that are capable of improving the reliability of parking detection. 
     Solution to Problem 
     One aspect of a parking detection sensor of the present invention includes: 
     a Doppler sensor; 
     a magnetic sensor that detects magnetism on a Z axis toward a vehicle; 
     a change point detection section that detects a change point in output of the Doppler sensor and output of the magnetic sensor; 
     a level difference detection section that detects a level difference over time in the output of the Doppler sensor and the output of the magnetic sensor; and 
     a state determination section that determines a parking state of the vehicle based on a detection result of the change point detection section and a detection result of the level difference detection section. 
     One aspect of a parking detection method of the present invention includes: 
     acquiring a Doppler sensor signal from a Doppler sensor; 
     acquiring a magnetic sensor signal from a magnetic sensor that detects magnetism on a Z axis toward a vehicle; and 
     determining whether the vehicle has been parked by using a fluctuation in the Doppler sensor signal and a fluctuation in a Z-axis signal of the magnetic sensor signal. 
     Advantageous Effects of Invention 
     According to the present invention, it is possible to improve the reliability of parking detection. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a block diagram illustrating a basic configuration of a parking detection sensor according to an embodiment; 
         FIG. 2  is a block diagram illustrating a configuration example of a temperature correction section; 
         FIG. 3  is a block diagram illustrating a configuration example of a change point detection section; 
         FIG. 4  is a block diagram illustrating a configuration example of a level difference detection section; 
         FIG. 5  illustrates a configuration example of a threshold value calculation section; 
         FIG. 6  illustrates a configuration example of a maximum value storage section; 
         FIG. 7  is a flowchart in which a vacant state is a start of processing; 
         FIG. 8  is a flowchart in which a parking state is a start of processing; 
         FIGS. 9A to 9C  illustrate examples of data when a vehicle enters and leaves a parking lot in which the parking detection sensor is installed, in which  FIG. 9A  illustrates output data of a magnetic sensor and output data of a Doppler sensor,  FIG. 9B  illustrates a sample sum of XYZ fluctuations, a sample sum of Z fluctuations, a sample sum of IQ fluctuations, and threshold values (dotted lines), and  FIG. 9C  illustrates an XYZ level difference during vacancy, an XYZ level difference during stop, an IQ level difference during vacancy, and threshold values (dotted lines); 
         FIGS. 10A to 10C  illustrate examples of data when a vehicle has been parked in a parking lot adjacent to a parking lot in which the parking detection sensor is installed, in which  FIG. 10A  illustrates output data of the magnetic sensor and output data of the Doppler sensor,  FIG. 10B  illustrates a sample sum of XYZ fluctuations, a sample sum of Z fluctuations, a sample sum of IQ fluctuations, and threshold values (dotted lines), and  FIG. 10C  illustrates an XYZ level difference during vacancy, an XYZ level difference during stop, an IQ level difference during vacancy, and threshold values (dotted lines); 
         FIGS. 11A to 11C  illustrate examples of data when a vehicle passes through a parking lot in which the parking detection sensor is installed, in which  FIG. 11A  illustrates output data of the magnetic sensor and output data of the Doppler sensor,  FIG. 11B  illustrates a sample sum of XYZ fluctuations, a sample sum of Z fluctuations, a sample sum of IQ fluctuations, and threshold values (dotted lines), and  FIG. 11C  illustrates an XYZ level difference during vacancy, an XYZ level difference during stop, an IQ level difference during vacancy, and threshold values (dotted lines); 
         FIGS. 12A to 12C  illustrate examples of data when there is no reaction from the Doppler sensor and there is a reaction from the magnetic sensor, in which  FIG. 12A  illustrates output data of the magnetic sensor and output data of the Doppler sensor,  FIG. 12B  illustrates a sample sum of XYZ fluctuations, a sample sum of Z fluctuations, a sample sum of IQ fluctuations, and threshold values (dotted lines), and  FIG. 12C  illustrates an XYZ level difference during vacancy, an XYZ level difference during stop, an IQ level difference during vacancy, and threshold values (dotted lines); 
         FIGS. 13A to 13C  illustrate examples of data when there is no reaction from the magnetic sensor and there is a reaction from the Doppler sensor, in which  FIG. 13A  illustrates output data of the magnetic sensor and output data of the Doppler sensor,  FIG. 13B  illustrates a sample sum of XYZ fluctuations, a sample sum of Z fluctuations, a sample sum of IQ fluctuations, and threshold values (dotted lines), and  FIG. 13C  illustrates an XYZ level difference during vacancy, an XYZ level difference during stop, an IQ level difference during vacancy, and threshold values (dotted lines); 
         FIG. 14  is a side view of the parking detection sensor; 
         FIG. 15  is a top view of the parking detection sensor; 
         FIG. 16  is a bottom view of the parking detection sensor; 
         FIG. 17  is a top view illustrating a state in which an upper case is removed; 
         FIG. 18  is a bottom view illustrating a state in which a lower case is removed; 
         FIG. 19  is a bottom view illustrating a state in which a board protective case is removed; 
         FIG. 20  is a top view of a circuit board; and 
         FIG. 21  is a bottom view of the circuit board. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     First, before describing the configuration of the embodiment, it will be described how the present inventor has achieved the present invention. 
     In a case where parking is detected using a magnetic sensor, output data of the magnetic sensor represents data of output of three axes (X, Y and Z axes). Among them, a reaction in the Z-axis output is large when a vehicle moves just above the sensor, and a reaction to a parking lot adjacent to a parking lot in which the magnetic sensor is installed is weak. Accordingly, looking at only a change in the Z-axis output of the magnetic sensor makes it possible to reduce the probability that the magnetic sensor will erroneously detect a vehicle parked in a parking lot adjacent to a parking lot in which the magnetic sensor is installed. 
     To determine whether a vehicle has stopped, it is necessary to detect whether the value of magnetism has changed from its value in a vacant state. However, the value of magnetism depends on a stop position, and there is also a stop position at which the value of magnetism is almost unchanged from that in a vacant state. Accordingly, only with the Z-axis output, the magnetic sensor highly likely makes erroneous determination of whether the vehicle has stopped in a parking lot or passed therethrough so that determination of whether the vehicle has stopped is more preferably performed by incorporating the X-axis output and the Y-axis output as well. 
     Further, the reliability of determination is improved by using a Doppler sensor in combination with a magnetic sensor. That is, it is possible to prevent a detection omission by using a Doppler sensor in combination with a magnetic sensor even under a situation in which detection is impossible only with the magnetic sensor. For example, when the bottom surface of a vehicle is made of metal, there are few detection omissions due to a magnetic sensor. In a case where the bottom surface of a vehicle is coated with resin or the like, however, the reaction from a magnetic sensor becomes weak and a detection omission may occur. Even in such a situation, a detection omission can be prevented when a Doppler sensor is used in combination with a magnetic sensor. 
     Further, when only a Doppler sensor is used, the Doppler sensor reacts to unevenness of the bottom surface of a vehicle or to a pitch of a vehicle in an up-down direction and erroneous detection may occur. Even in such a situation, it is possible to prevent erroneous detection by using a magnetic sensor in combination with the Doppler sensor. 
     That is, in the present embodiment, the reliability of parking detection is improved by using a Doppler sensor and a magnetic sensor in combination and constructing an algorithm in which even when a detection omission or erroneous detection occurs in one of the Doppler sensor and the magnetic sensor, another thereof compensates for the detection omission or the erroneous detection. 
     Note that, sensor signals utilized in the present embodiment are data of I and Q signals of a Doppler sensor, and X, Y and Z signals and temperature T of a magnetic sensor. The present embodiment makes it easy to capture fluctuations in signals by acquiring data of these six signals at the interval of one second, for example. Note that, although it is possible to further reduce the probability of erroneous detection by using the X, Y and Z signals of the magnetic sensor as described above, even use of only a signal of the Z axis of the magnetic sensor also makes it possible to reduce the probability of erroneous detection in comparison with the prior art. 
     Hereinafter, an embodiment of the present invention will be described with reference to the accompanying drawings. 
     &lt;1&gt; Basic Configuration 
       FIG. 1  is a block diagram illustrating a basic configuration of parking detection sensor  100  according to the embodiment. Parking detection sensor  100  is installed, for example, on the ground of each parking lot of a parking area or in the floor or ceiling of each parking lot of a parking area. 
     Parking detection sensor  100  includes Doppler sensor  110  and magnetic sensor  120 . In the example of the present embodiment, Doppler sensor  110  outputs I and Q signals at the interval of one second, and magnetic sensor  120  outputs X, Y and Z signals of three axes thereof and temperature signals T at the interval of one second. The configurations of Doppler sensor  110  and magnetic sensor  120  will be described later. 
     In addition, parking detection sensor  100  includes change point detection section  130 , level difference detection section  140 , and state determination section  150 . Further, parking detection sensor  100  includes temperature correction section  160  and temperature coefficient calculation section  170 . 
     I and Q signals which are sensing results of Doppler sensor  110  are inputted into change point detection section  130  and level difference detection section  140 . X, Y and Z signals and T (temperature) signal which are sensing results of magnetic sensor  120  are inputted into change point detection section  130  and level difference detection section  140  via temperature correction section  160 . Detection results of change point detection section  130  and level difference detection section  140  are inputted into state determination section  150 . State determination section  150  determines the state of a vehicle, such as whether the vehicle is parked in a parking lot, based on the detection results of change point detection section  130  and level difference detection section  140 . 
       FIG. 2  is a block diagram illustrating a configuration example of temperature correction section  160 . X, Y and Z signals from magnetic sensor  120  are inputted into adders  161 , respectively. Temperature T of magnetic sensor  120 , on the other hand, is multiplied by temperature coefficients αx, αy and αz of X, Y and Z calculated in advance by temperature coefficient calculation section  170  ( FIG. 1 ), respectively, and the products are inputted to adders  161 , respectively. As a result, X, Y and Z signals after temperature correction are outputted from adders  161 , respectively. 
       FIG. 3  is a block diagram illustrating a configuration example of change point detection section  130 . Change point detection section  130  performs the following processing to find a point where sensor output rapidly changes. 
     Five signals, which are I and Q signals of Doppler sensor  110  and X, Y and Z signals of magnetic sensor  120  after temperature correction, are subjected to differentiation processing using differentiation filters. In the case of the present embodiment, as the differentiation filters, FIR filters with filter coefficients of 0.5 and −0.5 are applied to I and Q signals of Doppler sensor  110 , and FIR filters with filter coefficients of 0.25, 0.25, −0.25 and −0.25 are applied to X, Y and Z signals of magnetic sensor  120 . 
     Since directions of changes are not utilized, absolute values of differentiation filter output are determined and information on only absolute values of changes is calculated. 
     With respect to output of magnetic sensor  120 , absolute values (X, Y and Z) of differentiation filter output are summed up. Further, with respect to Z alone, an absolute value of differentiation filter output is taken out. With respect to output of Doppler sensor  110 , absolute values (I and Q) of differentiation filter output are summed up. 
     Next, it is configured such that peaks of change points are easily found by taking sample sums. In the example of the present embodiment, each sample sum is generated by taking the sum of 10 samples. This processing can be performed, for example, by setting the coefficient of a FIR filter with a degree of 10 to be 1. 
     Next, sample sum output is compared with a predetermined threshold value. In a case where the sample sum output exceeds the threshold value, it is determined that there is a change, and this determination result is outputted to state determination section  150 . State determination section  150  is, for example, a state machine, and executes an algorithm to be described later. 
     Further, change point detection section  130  includes threshold value calculation section  131  and threshold value calculation section  132 . Threshold value calculation section  131  calculates, based on Z-axis output of magnetic sensor  120 , a threshold value for detecting a change in magnetism. Threshold value calculation section  132  calculates, based on I and Q output of Doppler sensor  110 , a threshold value for calculating a Doppler change. 
     Further, change point detection section  130  includes maximum value storage section  133 . Maximum value storage section  133  stores a maximum value of Z-axis output of magnetic sensor  120  and maximum values of I and Q output of Doppler sensor  110 . Values stored in maximum value storage section  133  are used as a measure for the reliability of a determination result. 
     Threshold value comparison section  134  compares a sum signal of X, Y and Z signals of magnetic sensor  120  with a threshold value, and outputs comparison result signal R 1 . Threshold value comparison section  135  compares a Z signal of magnetic sensor  120  with a threshold value, and outputs comparison result signal R 2 . Threshold value comparison section  136  compares I and Q signals of Doppler sensor  110  with a threshold value, and outputs comparison result signal R 3 . 
       FIG. 4  is a block diagram illustrating a configuration example of level difference detection section  140 . 
     Merely a change in sensor output of magnetic sensor  120  does not clarify whether a vehicle has actually stopped in a parking lot or has only passed therethrough. Accordingly, level difference detection section  140  compares an output level of magnetic sensor  120  before a change point and an output level of magnetic sensor  120  after the change point, and determines whether there is a difference therebetween. Further, level difference detection section  140  comparing an output level of Doppler sensor  110  during vacancy and an output level of Doppler sensor  110  at a current time, and determines whether there is a difference therebetween. 
     Level difference detection section  140  acquires magnetic levels for use in comparison as follows. 
     As magnetic levels to be compared, magnetic levels of the X, Y and Z axes for each of three levels of “vacant level (that is, a magnetic level in a vacant state)”, “previous vacant level”, and “stop level (that is, a magnetic level in a stop state)” are held. The held values thereof are updated with averaged values of inputted data (each data of X, Y and Z), respectively. In the example of the present embodiment, the averaging is performed by calculating a moving average with  10  filters having a filter coefficient of 0.1, which are arranged and have a length of 10 in total. Further, in order to cause delay by 4 samples for adaptation to the differentiation filters used for the change point detection in magnetic sensor  120 , FIR filters in which four zeros are added to the filter coefficient such that the FIR filters have a length of 14 in total are applied. 
     In a vacant state, state determination section (state machine)  150  updates the held values of the “vacant level” to output values of the average+delay filter described above. In a stop state, state determination section (state machine)  150  updates the held values of the “stop level” to output values of the average+delay filter described above. 
     On the other hand, the held values of the “previous vacant level” copy the held values of the “vacant level” when the state transitions from a state, which has changed from a vacant state and in which a change in X, Y and Z signals of magnetic sensor  120  is detected, to a vacant state, and when the state transitions from a state, which has changed from a stop state and in which a change in X, Y and Z signals of magnetic sensor  120  is detected, to a vacant state. Further, the held values of the “previous vacant level” copy and hold output values of the average+delay filter described above when the state transitions from a state, which has changed from a vacant state and in which a change in I and Q signals of Doppler sensor  110  or in a Z-axis signal of magnetic sensor  120  is detected, to a vacant state, and when the state transitions from a state, which has changed from a stop state and in which a change in I and Q signals of Doppler sensor  110  or in a Z-axis signal of magnetic sensor  120  is detected, to a vacant state. 
     Comparison between held values of a magnetic level and current values thereof is performed as follows. 
     Vacant Level Comparison: absolute values of differences between held values of X, Y and Z in a vacant state and current values of X, Y and Z are totaled. Threshold value comparison section  141  compares this totaled value with a threshold value calculated by threshold value calculation section  144 , and outputs, as comparison result signal R 11 , 1 in a case where the totaled value is larger than the threshold value, or 0 in a case where the totaled value is equal to or less than the threshold value. 
     Previous Vacant Level Comparison: absolute values of differences between held values of X, Y and Z in a previous vacant state and current values of X, Y and Z are totaled. Threshold value comparison section  142  compares this totaled value with a threshold value calculated by threshold value calculation section  144 , and outputs, as comparison result signal R 12 , 1 in a case where the totaled value is larger than the threshold value, or 0 in a case where the totaled value is equal to or less than the threshold value. 
     Stop Level Comparison: absolute values of differences between held values of X, Y and Z in a stop state and current values of X, Y and Z are totaled. Comparison section  143  compares this totaled value with a totaled value of a vacant level, and outputs comparison result signal R 13 . Specifically, comparison section  143  outputs 1 in a case where the totaled value of the stop level is larger than the totaled value of the vacant level (in other words, in a case where the current value is closer to that of the vacant level than that of the stop level), and 0 in a case where the totaled value of the stop level is equal to or less than the totaled value of the vacant level (in other words, when the current value is closer to that of the stop level than that of the vacant level). 
     Level difference detection section  140  also performs the same processing to I and Q signals obtained by Doppler sensor  110 . That is, when a value obtained by totaling absolute values of differences between values of I and Q in a vacant state and current values of I and Q is inputted, threshold value comparison section  145  compares this totaled value with a predetermined threshold value, and outputs, as comparison result signal R 14 , 1 in a case where the totaled value is larger than the threshold value, or 0 in a case where the totaled value is equal to or less than the threshold value. 
     Next, threshold values used in the present embodiment will be described. As described above, change point detection section  130  includes threshold value calculation sections  131  and  132 , and level difference detection section  140  includes threshold value calculation section  144 . Threshold value calculation section  131  calculates threshold values for detecting a change point in the magnetic Z axis and change points in the magnetic X, Y and Z axes. Threshold value calculation section  132  calculates a threshold value for detecting a Doppler change point. Threshold value calculation section  144  calculates a threshold value for comparing vacant levels. 
     Threshold values calculated by threshold value calculation sections  131  and  132  are updated when a determination result of state determination section  150  does not change from a vacant state or a stop state. On the other hand, a threshold value calculated by threshold value calculation section  144  is updated when a determination result of state determination section  150  does not change from a vacant state. 
       FIG. 5  illustrates a configuration example of threshold value calculation section  131 ,  132  or  144 . In the configuration example of  FIG. 5 , a value to be compared with a threshold value is multiplied by coefficient α, offset β is added thereto, and then the value is clipped between an upper limit and a lower limit that are a current threshold value +C and the current threshold value −C, respectively. A value obtained by multiplying the above result by coefficient γ&lt;1.0 and a result obtained by multiplying the current threshold value by 1−γ are summed up to set a new threshold value. 
       FIG. 6  illustrates a configuration example of maximum value storage section  133  ( FIG. 3 ). Maximum value storage section  133  in the example of  FIG. 6  acquires maximum values of latest 16 samples. The reason why 16 samples are set is that since a calculation interval of the algorithm is one second and a packet transmission interval to a gateway (a parking management apparatus) (that is, a determination result transmission interval) is 16 seconds in the case of the present embodiment, it is configured such that maximum values between packet transmissions can be obtained at the gateway. 
     &lt;2&gt; Determination Processing by State Determination Section  150   
       FIGS. 7 and 8  are flowcharts illustrating determination procedures to be executed by state determination section  150 .  FIG. 7  is a flowchart in which a vacant state is a start of processing.  FIG. 8  is a flowchart in which a parking state is a start of processing. 
     For example, it is obviously a vacant state when parking detection sensor  100  is installed in a parking area and the power supply of parking detection sensor  100  is turned on. Accordingly, when the power supply of parking detection sensor  100  is on, the processing starts in step S 10  of  FIG. 7 . Further, in a case where parking detection sensor  100  performs vacancy determination, the next determination starts in step S 10  in  FIG. 7 . In a case where parking detection sensor  100  performs parking determination, the next determination starts in step S 50  in  FIG. 8 . 
     Further, in other words, the processing flow of  FIG. 7  is mainly executed when it is detected whether a vehicle enters a parking lot in which parking detection sensor  100  is installed, and the processing flow of  FIG. 8  is mainly executed when it is detected whether a vehicle leaves a parking lot in which parking detection sensor  100  is installed. 
     First, the processing flow of  FIG. 7  will be described. 
     When state determination section  150  starts the processing in a vacant state in step S 10 , state determination section  150  determines in step S 20  subsequent thereto whether a Z fluctuation has been detected based on comparison result R 2  of threshold value comparison section  135 . In a case where an affirmative result is obtained in step S 20 , state determination section  150  shifts the processing to step S 21 . In step S 21 , state determination section  150  determines whether an XYZ level difference during vacancy has been detected based on comparison result R 11  of threshold value comparison section  141 . In a case where an affirmative result is obtained in step S 21 , state determination section  150  shifts the processing to step S 22 , and performs parking determination. Here, the parking determination refers to a determination result indicating that a parked vehicle is present in a parking lot in which parking detection sensor  100  is installed. 
     In a case where a negative result is obtained in step S 21 , state determination section  150  shifts the processing to step S 23 . In step S 23 , state determination section  150  determines whether an IQ level difference during vacancy has been detected based on comparison result R 14  of threshold value comparison section  145 . In a case where an affirmative result is obtained in step S 23 , state determination section  150  shifts the processing to step S 24 , and performs parking determination. In a case where a negative result is obtained in step S 23 , state determination section  150  shifts the processing to step S 25 , and performs vacancy determination. Here, the vacancy determination refers to a determination result indicating that a parked vehicle is not present in a parking lot in which parking detection sensor  100  is installed. 
     Note that, when the processing flow has reached step S 25  through steps S 10 -S 20 -S 21 -S 23 , it means that a vehicle has passed through a parking lot in which itself is installed. Accordingly, it may also be configured such that when the processing reaches step S 25 , state determination section  150  performs vacancy determination and performs passing-through determination. 
     When a negative result is obtained in step S 20 , state determination section  150  shifts the processing to step S 30 . In step S 30 , state determination section  150  determines whether an IQ fluctuation has been detected based on comparison result R 3  of threshold value comparison section  136 . When an affirmative result is obtained in step S 30 , state determination section  150  shifts the processing to step S 31 . In step S 31 , state determination section  150  determines whether an XYZ level difference during vacancy has been detected based on comparison result R 11  of threshold value comparison section  141 . In a case where an affirmative result is obtained in step S 31 , state determination section  150  shifts the processing to step S 32 , and performs parking determination. 
     When a negative result is obtained in step S 30 , state determination section  150  shifts the processing to step S 40 . In step S 40 , state determination section  150  determines whether an XYZ fluctuation has been detected based on comparison result R 1  of threshold value comparison section  134 . In a case where an affirmative result is obtained in step S 40 , state determination section  150  shifts the processing to step S 41 . In step S 41 , state determination section  150  determines whether an XYZ level difference during vacancy has been detected based on comparison result R 11  of threshold value comparison section  141 . In a case where an affirmative result is obtained in step S 41 , state determination section  150  shifts the processing to step S 42 , and performs adjacent parking determination. Here, the adjacent parking determination refers to a determination result indicating that a parked vehicle is present in a parking lot adjacent to a parking lot in which parking detection sensor  100  is installed. When a negative result is obtained in step S 41 , state determination section  150  shifts the processing to step S 43 , and performs vacancy determination. 
     Further, when a negative result is obtained in step S 40 , state determination section  150  shifts the processing to step S 44 , and performs vacancy determination. 
     Here, the processing flow illustrated in  FIG. 7  has the following characteristics.
         Even in a case where a fluctuation in the Z axis of magnetic sensor  120  has been detected during vacancy (step S 20 ; YES), vacancy determination is performed when levels of I and Q of Doppler sensor  110  are close to levels of I and Q during vacancy (step S 23 ; NO). Thus, a case where a vehicle simply “passes through” a parking lot in which parking detection sensor  100  is installed is not erroneously determined as “parking”, but can be correctly determined as “vacancy”.   Even in a case where a fluctuation in the Z axis of magnetic sensor  120  has not been detected during vacancy (step S 20 ; NO), it is determined whether an IQ fluctuation in Doppler sensor  110  has been detected (step S 30 ). Thus, even in a case where the output level of magnetic sensor  120  is generally low for a certain reason, that is, even in a case where determination is erroneously performed only with the output of magnetic sensor  120 , it is possible to compensate for a determination error due to a low output level of magnetic sensor  120 , based on a detection result of an IQ fluctuation in Doppler sensor  110 .   Even in a case where neither a fluctuation in the Z axis of magnetic sensor  120  nor an IQ fluctuation in Doppler sensor  110  are detected during vacancy (step S 20 ; NO and step S 30 ; NO), it is determined whether an XYZ fluctuation in magnetic sensor  120  has been detected (step S 40 ), and whether an XYZ fluctuation level difference during vacancy in magnetic sensor  120  is detected (step S 41 ). Thus, it is possible to determine whether a vehicle is parked in a parking lot adjacent to a parking lot in which parking detection sensor  100  is installed.       

     Next, the processing flow of  FIG. 8  will be described. 
     When state determination section  150  starts the processing in a parking state in step S 50 , state determination section  150  determines in step S 60  subsequent thereto whether a Z fluctuation has been detected based on comparison result R 2  of threshold value comparison section  135 . In a case where an affirmative result is obtained in step S 60 , state determination section  150  shifts the processing to step S 61 . In step S 61 , state determination section  150  determines whether an XYZ level difference during stop has been detected based on comparison result R 13  of the comparator unit  143 . In a case where an affirmative result is obtained in step S 61 , state determination section  150  shifts the processing to step S 62 , and performs vacancy determination. In a case where a negative result is obtained in step S 61 , state determination section  150  shifts the processing to step S 63 , and performs parking determination. 
     In a case where a negative result is obtained in step S 60 , state determination section  150  shifts the processing to step S 70 . In step S 70 , state determination section  150  determines whether an IQ fluctuation has been detected based on comparison result R 3  of threshold value comparison section  136 . In a case where an affirmative result is obtained in step S 70 , state determination section  150  shifts the processing to step S 61 . In a case where a negative result is obtained in step S 70 , state determination section  150  shifts the processing to step S 71 , and performs parking determination. 
     Here, the processing flow illustrated in  FIG. 8  has the following characteristics.
         Even in a case where a fluctuation in the Z axis of magnetic sensor  120  has not been detected during vacancy (step S 60 ; NO), it is determined whether an IQ fluctuation in Doppler sensor  110  has been detected (step S 70 ). Thus, even in a case where the output level of magnetic sensor  120  is generally low for a certain reason, that is, even in a case where determination is erroneously performed only with the output of magnetic sensor  120 , it is possible to compensate for a determination error due to a low output level of magnetic sensor  120 , based on a detection result of an IQ fluctuation in Doppler sensor  110 .       

       FIGS. 9 to 13  illustrate examples of data in parking detection sensor  100 . The horizontal axis represents the time (seconds) and the vertical axis represents the signal level. 
       FIGS. 9A to 9C  illustrate examples of data when a vehicle enters and leaves a parking lot in which parking detection sensor  100  is installed.  FIG. 9A  illustrates output data (X, Y, Z) of magnetic sensor  120  and output data (I, Q) of Doppler sensor  110 .  FIG. 9B  illustrates a sample sum of XYZ fluctuations (sum XYZ), a sample sum of Z fluctuations (sum Z), a sample sum of IQ fluctuations (sum IQ), and threshold values (dotted lines). The sample sums and the threshold values are inputted into threshold value comparison sections  134 ,  135  and  136  of change point detection section  130 , respectively.  FIG. 9C  illustrates an XYZ level difference during vacancy (vacant_diff), an XYZ level difference during stop (occ_diff), an IQ level difference during vacancy (dop IQ), and threshold values (dotted lines). The sample sums and the threshold values are inputted into threshold value comparison sections  141 ,  143  and  145  of level difference detection section  140 , respectively. 
     With respect to the data as illustrated in  FIGS. 9A to 9C , parking detection sensor  100  performs the processing in steps S 10 -S 20 -S 21 -S 22  to obtain a determination result that a vehicle enters a parking lot in which parking detection sensor  100  itself is installed. Further, with respect to the data as illustrated in  FIGS. 9A to 9C , parking detection sensor  100  performs the determinations in steps S 50 -S 60 -S 61 -S 62  to obtain a determination result that a vehicle leaves a parking lot in which parking detection sensor  100  itself is installed. 
       FIGS. 10A to 10C  illustrate examples of data when a vehicle has been parked in a parking lot adjacent to a parking lot in which parking detection sensor  100  is installed.  FIG. 10A  illustrates output data (X, Y, Z) of magnetic sensor  120  and output data (I, Q) of Doppler sensor  110 .  FIG. 10B  illustrates a sample sum of XYZ fluctuations (sum XYZ), a sample sum of Z fluctuations (sum Z), a sample sum of IQ fluctuations (sum IQ), and threshold values (dotted lines). The sample sums and the threshold values are inputted into threshold value comparison sections  134 ,  135  and  136  of change point detection section  130 , respectively.  FIG. 10C  illustrates an XYZ level difference during vacancy (vacant_diff), an XYZ level difference during stop (occ_diff), an IQ level difference during vacancy (dop IQ), and threshold values (dotted lines). The sample sums and the threshold values are inputted into threshold value comparison sections  141 ,  143  and  145  of level difference detection section  140 , respectively. 
     With respect to the data as illustrated in  FIG. 10A to 10C , parking detection sensor  100  performs the determinations in steps S 10  S 20  S 30  S 40  S 41  S 42  to obtain a determination result that a vehicle has been parked in a parking lot adjacent to a parking lot in which parking detection sensor  100  itself is installed. 
       FIGS. 11A to 11C  illustrate examples of data when a vehicle passes through a parking lot in which parking detection sensor  100  is installed.  FIG. 11A  illustrates output data (X, Y, Z) of magnetic sensor  120  and output data (I, Q) of Doppler sensor  110 .  FIG. 11B  illustrates a sample sum of XYZ fluctuations (sum XYZ), a sample sum of Z fluctuations (sum Z), a sample sum of IQ fluctuations (sum IQ), and threshold values (dotted lines). The sample sums and the threshold values are inputted into threshold value comparison sections  134 ,  135  and  136  of change point detection section  130 , respectively.  FIG. 11C  illustrates an XYZ level difference during vacancy (vacant_diff), an XYZ level difference during stop (occ_diff), an IQ level difference during vacancy (dop IQ), and threshold values (dotted lines). The sample sums and the threshold values are inputted into threshold value comparison sections  141 ,  143  and  145  of level difference detection section  140 , respectively. 
     With respect to the data as illustrated in  FIGS. 11A to 11C , parking detection sensor  100  performs the determinations in steps S 10 -S 20 -S 21 -S 23 -S 25  to obtain a determination result that a vehicle passes through a parking lot in which parking detection sensor  100  itself is installed. 
       FIGS. 12A to 12C  illustrate examples of data when there is no reaction from Doppler sensor  110  (that is, there is no IQ fluctuation) and there is a reaction from magnetic sensor  120  (specifically, there is a fluctuation in the Z axis).  FIG. 12A  illustrates output data (X, Y, Z) of magnetic sensor  120  and output data (I, Q) of Doppler sensor  110 .  FIG. 12B  illustrates a sample sum of XYZ fluctuations (sum XYZ), a sample sum of Z fluctuations (sum Z), a sample sum of IQ fluctuations (sum IQ), and threshold values (dotted lines). The sample sums and the threshold values are inputted into threshold value comparison sections  134 ,  135  and  136  of change point detection section  130 , respectively.  FIG. 12C  illustrates an XYZ level difference during vacancy (vacant_diff), an XYZ level difference during stop (occ_diff), an IQ level difference during vacancy (dop IQ), and threshold values (dotted lines). The sample sums and the threshold values are inputted into threshold value comparison sections  141 ,  143  and  145  of level difference detection section  140 , respectively. 
     With respect to the data as illustrated in  FIGS. 12A to 12C , parking detection sensor  100  performs the determinations in steps S 10 -S 20 -S 21 -S 22  to obtain a determination result that a vehicle enters a parking lot in which parking detection sensor  100  itself is installed. 
       FIGS. 13A to 13C  illustrate examples of data when there is no reaction from magnetic sensor  120  (specifically there is no XYZ difference during vacancy) and there is a reaction from Doppler sensor  110  (that is, there is an IQ fluctuation).  FIG. 13A  illustrates output data (X, Y, Z) of magnetic sensor  120  and output data (I, Q) of Doppler sensor  110 .  FIG. 13B  illustrates a sample sum of XYZ fluctuations (sum XYZ), a sample sum of Z fluctuations (sum Z), a sample sum of IQ fluctuations (sum IQ), and threshold values (dotted lines). The sample sums and the threshold values are inputted into threshold value comparison sections  134 ,  135  and  136  of change point detection section  130 , respectively.  FIG. 13C  illustrates an XYZ level difference during vacancy (vacant_diff), an XYZ level difference during stop (occ_diff), an IQ level difference during vacancy (dop IQ), and threshold values (dotted lines). The sample sums and the threshold values are inputted into threshold value comparison sections  141 ,  143  and  145  of level difference detection section  140 , respectively. 
     With respect to the data as illustrated in  FIGS. 13A to 13C , parking detection sensor  100  performs the determinations in steps S 10 -S 20 -S 21 -S 23 -S 24  to obtain a determination that a vehicle enters a parking lot in which parking detection sensor  100  itself is installed. 
     &lt;3&gt; Structure of Parking Detection Sensor 
     Next, the structure of parking detection sensor  100  of the present embodiment will be described. 
       FIG. 14  is a side view of parking detection sensor  100 .  FIG. 15  is a top view of parking detection sensor  100 .  FIG. 16  is a bottom view of parking detection sensor  100 . Parking detection sensor  100  includes an outer shell formed of upper case  210  having a dome shape and lower case  220  having a plate shape. 
       FIG. 17  is a top view illustrating a state in which upper case  210  is removed.  FIG. 18  is a bottom view illustrating a state in which lower case  220  is removed. Further,  FIG. 19  is a bottom view illustrating a state in which board protective case  230  of  FIG. 18  is removed. As can be seen from  FIGS. 18 and 19 , the lower-surface side of circuit board  300  is covered and protected by board protective case  230 . Further, as can be seen in  FIG. 19 , batteries  240  are attached to the lower-surface side of circuit board  300 . 
       FIG. 20  is a top view of circuit board  300 .  FIG. 21  is a bottom view of circuit board  300 . As can be seen from these drawings, circuit board  300  is divided into two regions, which are a Doppler sensor forming region and a magnetic sensor forming region, at a boundary indicated by a dash-dotted line. 
     As illustrated in  FIG. 20 , antennas  310  of the 24 GHz band that transmit microwaves for performing Doppler detection are formed in the Doppler sensor forming region on an upper-surface side of circuit board  300 . 
     As illustrated in  FIG. 21 , IC chip  311  of Doppler sensor  110  is mounted in the Doppler sensor forming region on the lower-surface side of circuit board  300 . Further, power supply IC chip  312  is mounted in the Doppler sensor forming region. 
     On the other hand, IC chip  321  of magnetic sensor  120  is mounted in the magnetic sensor forming region on the lower-surface side of circuit board  300 . Further, microcomputer chip  322  that implements the functions of change point detection section  130 , level difference detection section  140 , temperature coefficient calculation section  170 , temperature correction section  160 , and state determination section  150  is mounted in the magnetic sensor forming region. Further, radio communication IC chip  323  that wirelessly transmits a determination result obtained by state determination section  150  to the parking management apparatus is mounted in the magnetic sensor forming region. Further, ON/OFF switch  324  of a magnet type is mounted in the magnetic sensor forming region. Parking detection sensor  100  is configured such that a user causes a magnet to approach ON/OFF switch  324  from the outside of the case to turn on/off ON/OFF switch  324 , thereby turning on/off the power supply. 
     Thus, in parking detection sensor  100 , all circuit components except antenna  310  are mounted on the lower surface of circuit board  300 , and all these circuit components are covered and packaged by board protective case  230  ( FIG. 18 ). 
     &lt;4&gt; Summary 
     As described above, parking detection sensor  100  of the present embodiment includes: Doppler sensor  110 ; magnetic sensor  120  that detects magnetism on the X, Y and Z axes; change point detection section  130  that detects a change point in output of Doppler sensor  110  and output of magnetic sensor  120 ; level difference detection section  140  that detects a magnetic level difference over time in the output of Doppler sensor  110  and the output of magnetic sensor  120 ; and state determination section  150  that determines a parking state of a vehicle based on a detection result of change point detection section  130  and a detection result of level difference detection section  140 , thereby improving the reliability of parking detection. 
     Further, according to parking detection sensor  100 , state determination section  150  determines that a vehicle has been parked (step S 24 ) in a case where a detection result indicating that a fluctuation in the Z axis of magnetic sensor  120  is larger than a predetermined threshold value is obtained in change point detection section  130  (step S 20 ; YES) and a difference between an output level of Doppler sensor  110  during vacancy and a current output level of Doppler sensor  110  is larger than a predetermined threshold value in level difference detection section  140  (step S 23 ; YES). Thus, it is possible to further improve the reliability of parking detection. 
     Further, according to parking detection sensor  100 , even when a detection result indicating that a fluctuation in the Z axis of magnetic sensor  120  is equal to or less than a predetermined threshold value is obtained in change point detection section  130  (step S 20 ; NO), state determination section  150  determines that a vehicle has been parked (step S 32 ) in a case where a detection result indicating that a fluctuation in output of Doppler sensor  110  is larger than a predetermined threshold value is obtained in change point detection section  130  (step S 30 ; YES) and a difference in an XYZ output level of magnetic sensor  120  during vacancy and a current XYZ output level of magnetic sensor  120  is larger than a predetermined threshold value in level difference detection section  140  (step S 31 ; YES). Thus, it is possible to further improve the reliability of parking detection. 
     Further, according to parking detection sensor  100 , state determination section  150  determines that a vehicle is determined to be parked in an adjacent or nearby parking lot in a case where detection results indicating that a fluctuation in the Z axis of magnetic sensor  120  is equal to or less than a predetermined threshold value in change point detection section  130  (step S 20 ; NO) and a fluctuation in output of Doppler sensor  110  is equal to or less than a predetermined threshold value (step S 30 ; NO) are obtained and a difference between an XYZ output level of magnetic sensor  120  during vacancy and a current XYZ output level of magnetic sensor  120  is larger than a predetermined threshold value in level difference detection section  140  (step S 41 ; YES). Thus, it is possible to correctly detect that a vehicle has been parked in an adjacent or nearby parking lot. 
     Further, since parking detection sensor  100  includes state determination section  150 , data to be sent from parking detection sensor  100  to an external management apparatus can be only a determination result obtained by state determination section  150 . As a result, it is possible to significantly reduce the amount of data to be transmitted or the number of transmission in comparison with a case where measurement data obtained by Doppler sensor  110  and magnetic sensor  120  is sent as it is to the management apparatus. Accordingly, in a case where data is wirelessly transmitted, battery consumption can be reduced and the time when parking detection sensor  100  can be operated by the batteries can be lengthened. 
     One characteristic of parking detection sensor  100  of the present embodiment lies in determining whether a vehicle is above the sensor by using the magnitudes of a fluctuation in signals of Doppler sensor  110  and a fluctuation in a Z-axis signal of magnetic sensor  120 . In other words, only the signals of Doppler sensor  110  and Z-axis data of magnetic sensor  120  (excluding X- and Y-axis data thereof) are taken and used. Thus, it is possible to reduce erroneous detection due to parking in a parking lot adjacent to a parking lot in which parking detection sensor  100  is installed. That is, when a vehicle has been parked in a parking lot adjacent to a parking lot in which parking detection sensor  100  is installed, it is possible to prevent occurrence of erroneous detection as if the vehicle had been parked in the parking lot in which parking detection sensor  100  is installed. 
     One characteristic of parking detection sensor  100  of the present embodiment lies in that values of the X, Y and Z axes of magnetic sensor  120  during vacancy are held, and that after it is determined that a vehicle is above the sensor, a detection result is obtained by using a difference between current values of magnetic sensor  120  and the held values of the sensor during vacancy. Thus, it is possible to know whether the vehicle has stopped above the sensor or has only passed through the sensor. 
     One characteristic of parking detection sensor  100  of the present embodiment lies in that in a case where no fluctuation is found in a Z-axis signal of magnetic sensor  120 , but a fluctuation is found in a signal obtained by totaling X-, Y- and Z-axis signals of magnetic sensor  120 , it is determined that a vehicle stops not above the sensor but in a place adjacent thereto, and at this time the update of values of the magnetic sensor during vacancy is stopped. Thus, it is possible to achieve an effect of preventing values of the magnetic sensor during vacancy from becoming erroneous. 
     One characteristic of parking detection sensor  100  of the present embodiment lies in that use of a fluctuation amount of a sensor signal makes it less susceptible to a component that slowly changes such as temperature drift. 
     Further, according to the present embodiment, Doppler sensor  110 , magnetic sensor  120 , change point detection section  130 , level difference detection section  140 , and state determination section  150  are mounted on one circuit board  300 , which makes it possible to realize measurement through determination in a compact configuration, and to realize parking detection sensor  100  that is also easily installed in a parking area. 
     Further, a radio section (radio communication IC chip  323 ) that wirelessly transmits a determination result of state determination section  150  is mounted on circuit board  300  so that wiring connecting parking detection sensor  100  and the management apparatus (not illustrated) is not required. 
     The embodiment described above is only illustration of an exemplary embodiment for implementing the present invention, and the technical scope of the present invention shall not be construed limitedly thereby. That is, the present invention can be carried out in various forms without departing from the gist thereof or the main characteristics thereof. 
     In the embodiment described above, a case of performing parking detection by executing the determination processing flows of  FIGS. 7 and 8  has been described, but the determination processing flows of  FIGS. 7 and 8  are not necessarily required to be executed as they are. For example, some processing in the determination processing flows of  FIGS. 7 and 8  may be omitted or changed. Alternatively, additional processing may be added thereto. Further, in order to increase resistance to noise, the determination of sensor signals may be performed a plurality of times. Further, in order to increase resistance to noise, magnetic sensor signals acquired a plurality of times may be averaged for use. 
     Further, it may also be configured such that a plurality of parking detection sensors  100  is installed and final determination is obtained by combining results of the plurality of parking detection sensors  100 . That is, it may also be configured such that parking detection sensors  100  adjacent to each other are linked to each other to obtain a determination result. 
     Further, in the embodiment described above, a case in which magnetic sensor  120  that detects magnetism on the three axes (X, Y and Z axes) is used and parking is detected by using detection results of X, Y and Z signals has been described, but parking determination may be performed using, among each output of magnetic sensor  120  that is a triaxial magnetic sensor, only the Z-axis signal toward a vehicle or by using a uniaxial magnetic sensor (not illustrated) that detects a Z-axis signal toward a vehicle or a biaxial magnetic sensor (not illustrated) with two axes including a Z axis. The point is that it may be configured such that parking determination is performed using, among each output of the magnetic sensor, the Z-axis signal toward a vehicle. In this case, the processing on X and Y signals may be omitted from the embodiment described above. For example, in  FIG. 7 , it may be configured such that a Z level difference during vacancy is detected in step S 21 , a Z level difference during vacancy is detected in step S 31 , and a Z level difference during vacancy is detected in step S 41 . Further, a Z level difference during stop may be detected in step S 61  of  FIG. 8 . 
     The disclosure of Japanese Patent Application No. 2019-109561, filed on Jun. 12, 2019, including the specification, drawings and abstract, is incorporated herein by reference in its entirety. 
     INDUSTRIAL APPLICABILITY 
     The present invention is widely applicable as a parking detection sensor. 
     REFERENCE SIGNS LIST 
     
         
           100  Parking detection sensor 
           110  Doppler sensor 
           120  Magnetic sensor 
           130  Change point detection section 
           140  Level difference detection section 
           150  State determination section 
           210  Upper case 
           220  Lower case 
           230  Board protective case 
           240  Battery 
           300  Circuit board 
           310  Antenna