JP2005132291A - Vehicle control system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a vehicle control system capable of calculating an index universally indicating a probability of a present position and carrying out vehicle control utilizing the present position of a vehicle based on the index. <P>SOLUTION: The vehicle control system has a vehicle position specifying means 111 for specifying a final vehicle position on a road by calculating a vehicle position by hybrid navigation based on a measurement value by electronic navigation and a vehicle presumption position by self-supporting navigation and carrying out map-matching processing based on the vehicle position and road map data. A determination result indicating a probability of the vehicle position calculated by the hybrid navigation and a determination result indicating a probability of the vehicle position specified by map-matching processing are outputted and they are added while imparting predetermined weighting to the result. Thereby, accuracy A indicating a probability of a present position is determined (S900-S980). The vehicle control device 120 changes a content of the vehicle control using the vehicle position based on the accuracy A. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to a vehicle control system that calculates a current position of a vehicle and controls a desired control target in the vehicle based on the calculated current position.

  As this type of vehicle control system, for example, a vehicle control system described in Patent Document 1 is known. In this conventional vehicle control system, the degree of confidence is set for each evaluation item selected in advance in order to represent the reliability of the sensor for obtaining the current position and the reliability of each determination means for performing logic determination.

  For example, the reliability of GPS that measures the position of the vehicle, the reliability of the gyro sensor that detects the traveling direction of the vehicle, the reliability of the determination means that makes a logic determination as to whether the traveling locus of the vehicle matches the road data, etc. Is selected as an evaluation item. The reliability of the GPS is based on the evaluation criteria such as whether three-dimensional positioning is being performed or whether the vehicle has traveled a predetermined distance without receiving radio waves from an artificial satellite. In this case, if the GPS is performing three-dimensional positioning, the confidence level regarding the reliability of the GPS is set to “1”, while if the radio wave from the artificial satellite is not received while the vehicle travels a predetermined distance, Is set to “0”. Further, the reliability of the gyro sensor is evaluated based on whether or not the rotational angular velocity of the vehicle is zero, and if it is zero, the confidence level is set to “1”. In addition, regarding the logic determination as to whether or not the vehicle travel locus and the road data match, when the current position is corrected by performing a turn determination or the like based on the road data, the confidence level is set to “1”. When the vehicle position deviates from the road data, the confidence level is set to “0”.

In this way, the confidence level is set for each evaluation item. In principle, when the confidence level of all the evaluation items is set to “1”, the automatic transmission as a control target is controlled. Yes. That is, when there is a possibility that the current position cannot be calculated accurately, the automatic transmission is not controlled to prevent the driver from feeling uncomfortable.
JP 2001-182817 A

  As described above, in the conventional vehicle control system, the degree of confidence in the sensor or determination means as the evaluation item is represented by “1” or “0”. When the confidence level of all the evaluation items is “1”, the control of the automatic transmission is permitted. In other words, this conventional vehicle control system regards the calculated current position as correct when predetermined evaluation criteria are satisfied for each of a plurality of predetermined evaluation items, and otherwise the current position is incorrect. It is considered to be.

  When a predetermined control target is controlled based on the current position of the vehicle, the accuracy of the required current position may be different when the control target is different. However, in the above-described vehicle control system, accuracy conditions necessary for controlling a specific control target (automatic transmission) are set as evaluation items. Therefore, if the control targets are different, the accuracy required for the control is set. It is necessary to separately set evaluation items for satisfying the conditions.

  In other words, the conventional vehicle control system has a problem in terms of expandability and flexibility because it cannot obtain an index that universally indicates the certainty of the current position.

  The present invention has been made in view of the above points, and can calculate an index that universally indicates the certainty of the calculated current position, and uses the current position of the vehicle based on the index. It is an object of the present invention to provide a vehicle control system capable of performing vehicle control.

In order to achieve the above object, in the vehicle control system according to claim 1,
A radio navigation means for outputting a measured value of the vehicle position by radio navigation and a self-contained navigation means for estimating the position of the vehicle by self-contained navigation; and a measurement value by the radio navigation means and a vehicle estimated position by the self-contained navigation means. Based on the hybrid navigation means for calculating the vehicle position,
Road map data storage means for storing road map data;
Map matching means for performing a map matching process based on the vehicle position calculated by the hybrid navigation means and the road map data stored in the road map data storage means to identify the final vehicle position on the road; ,
When the hybrid navigation means calculates the vehicle position, a first determination means for determining the likelihood of the vehicle position and outputting the determination result;
A second determination means for determining the likelihood of the vehicle position when outputting the determination result when specifying the vehicle position on the road by the map matching process;
The determination result output by the first determination unit and the determination result output by the second determination unit while weighting the determination result of the first determination unit larger than the determination result of the second determination unit A calculating means for calculating an added value of
Vehicle control means for changing the content of vehicle control using the final vehicle position specified by the map matching means based on the magnitude of the addition value calculated by the calculation means.

  As described above, in the vehicle control system according to claim 1, the vehicle position is calculated by the hybrid navigation means, and the final vehicle position is determined by matching the calculated vehicle position with the road of the road map data. Identify. In consideration of such vehicle position calculation processing, the likelihood of the vehicle position calculated by the hybrid navigation means is determined, and the first determination means for outputting the determination result is specified on the road by the map matching processing. The second determination means for determining the likelihood of the vehicle position to be output and outputting the determination result is provided. That is, regarding the process for obtaining the vehicle position, it is possible to obtain a partial probability for each functional element by disassembling the process into functional elements. Then, by adding the respective determination results indicating the partial certainty while giving a predetermined weight, an index that universally indicates the certainty of the desired vehicle position can be obtained. That is, the total value of the determination results weighted for each functional element can be used as an index indicating the probability of the vehicle position to be obtained.

  Here, in the map matching process, the final vehicle position on the road is specified using the vehicle position calculated by the hybrid navigation means. That is, if the vehicle position error calculated by the hybrid navigation means is large, it is inevitable that an error will occur in the finally obtained vehicle position even if the map matching process itself is performed correctly. Thus, in the vehicle position calculation process, the upstream process has a greater influence on the finally obtained vehicle position than the downstream process. For this reason, the calculation means calculates an addition value of each determination result while performing a greater weighting on the determination result output by the first determination means than the determination result output by the second determination means. Thereby, it is possible to obtain an index that more accurately indicates the likelihood of the finally obtained vehicle position.

  When the hybrid navigation means calculates the vehicle position, as described in claim 2, the first determination means depends on whether or not each sensor for the self-contained navigation means to obtain the estimated position of the vehicle is normal. It is preferable to output the first determination result. For example, if any sensor has a failure such as disconnection or short circuit, the vehicle position estimated based on the output signal from the sensor is completely different from the actual vehicle position.

  Further, as described in claim 3, the first determination means determines whether the radio navigation means receives the radio wave necessary for outputting the measurement value of the vehicle position. It is preferable to output the result. For example, in GPS, in order to obtain an accurate vehicle position, it is usually necessary to receive radio waves from four satellites. In other words, when only radio waves are received from three or less satellites, there is a possibility that an accurate vehicle position cannot be obtained from the measured value of the vehicle position by the radio navigation means. Therefore, whether or not the radio navigation means receives radio waves necessary for outputting an accurate measurement value of the vehicle position greatly affects the accuracy of the finally obtained vehicle position.

  Furthermore, as described in claim 4, the first determination means calculates a detection error of each sensor for the self-contained navigation means to obtain the estimated position of the vehicle with reference to the measured value of the vehicle position by radio wave navigation. The third determination result is preferably output depending on the magnitude of the detection error of each sensor. The self-contained navigation means uses the sensor output from each sensor that detects the distance and direction in order to obtain the estimated position of the vehicle. However, if there is an error in the sensor output, naturally, the estimated position of the vehicle by the self-contained navigation means is likely to be different from the correct vehicle position. Therefore, the detection error of each sensor is calculated on the basis of the measured value of the vehicle position by radio navigation indicating the absolute position of the vehicle, and the probability of the vehicle position is determined based on the magnitude of the detection error. It is preferable to output the result.

  Further, as described in claim 5, the first determination means calculates an error included in the vehicle position calculated by the hybrid navigation means, and determines the fourth determination result depending on the magnitude of the error. You may calculate. Based on the error included in the vehicle position calculated by the hybrid navigation means, the likelihood of the vehicle position can be determined. Note that the error included in the vehicle position calculated by hybrid navigation may be used for setting a search area for candidate roads to which the vehicle position is matched in the map matching process. If the error included in the vehicle position becomes large and the search area widens, the likelihood of the vehicle position obtained by the map matching process also decreases, and the likelihood of the vehicle position in the map matching process is also affected. . Therefore, it is preferable to obtain the accuracy in consideration of the magnitude of the error included in the vehicle position calculated by the hybrid navigation means.

  When the first determination unit outputs a plurality of determination results from the first determination result to the fourth determination result, the first determination unit adds the determination result to be output as described in claim 6. The weighting to be performed is preferably set so as to decrease in order from the first determination result to the fourth determination result. This is because the influence on the accuracy of the finally obtained vehicle position is considered to be reduced according to the order of the first determination result to the fourth determination result.

  When determining the likelihood of the vehicle position specified on the road by the map matching process, as described in claim 7, the second determination means specifies the current vehicle position direction and the vehicle position. The fifth determination result can be output depending on the magnitude of the difference. For example, when the difference between both positions is smaller than a predetermined value, it can be considered that the certainty of the final vehicle position obtained by fitting on the road is high.

  In addition, as described in claim 8, the second determination means obtains a difference between the direction at the time of calculating the vehicle position and the road direction in the road map data in a section from the current vehicle position to the rear of the predetermined distance. Depending on the magnitude of the difference, the sixth determination result may be output. Even in this case, it is possible to obtain a determination result indicating the probability that the road on which the vehicle position is matched by the map matching process is the road on which the vehicle is actually traveling.

  Further, as described in claim 9, the second determination means obtains the number of map matching process candidate roads belonging to the search range set with reference to the vehicle position, and depends on the number, The determination result of 7 may be output. This is because in the map matching process, as the number of candidate roads to which the vehicle position is matched increases, the possibility of matching the vehicle position on the wrong road increases.

  Further, as described in claim 10, the second determination means obtains the magnitude of the displacement of the previous and current vehicle positions with respect to the final vehicle position specified on the road by the map matching process, and The eighth determination result may be output depending on the magnitude of the displacement. When the displacement of the vehicle position is larger than the length according to the traveling speed of the vehicle, it means that the road position where the vehicle position is adjusted by the map matching process has changed between the previous time and the current time. In this case, the vehicle position specified on the road by the map matching process is considered unstable. On the other hand, when the displacement of the vehicle position is a length corresponding to the traveling speed of the vehicle, the vehicle position is continuously adjusted on the same road, and the vehicle position is considered to be stable. Thus, the determination result according to the probability of the vehicle position by the map matching process can be obtained also by the magnitude of the displacement of the vehicle position.

  As described in claim 11, when the second determination unit outputs a plurality of determination results from the fifth determination result to the eighth determination result, the second determination unit gives the determination result to be output. The weight assigned to the fifth determination result is such that the weight assigned to the fifth determination result is at least smaller than the weight assigned to the first determination result, and decreases in the order of the fifth determination result to the eighth determination result. It is preferably set. As a result, the determination result output from the second determination means is weighted at least smaller than the weight for the first determination result output from the first determination means, and appropriate for each determination result. Weighting can be performed, and based on a plurality of determination results, an index that accurately indicates the likelihood of the finally obtained vehicle position can be obtained.

  According to a twelfth aspect of the present invention, the vehicle control means includes: an automatic transmission, a suspension device, a lighting device, a steering device, a braking device, a prime mover, an air conditioner, an energy management device, and a visibility support device. At least one of a display device, an operation device, a body control device, and a security device can be set as a control target.

  Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

  FIG. 1 is a block diagram showing a schematic configuration of a vehicle control system according to the present embodiment. The vehicle control system according to the present embodiment uses the current position of the vehicle calculated by the navigation apparatus 100 with the navigation apparatus 100 that performs processing such as calculation of the current position of the vehicle and the automatic transmission as a control target. And a vehicle control device 120 that performs shift control according to the road condition to which the vehicle belongs.

  For example, the vehicle control device 120 responds to road conditions such as the shape (curvature of a curve), slope (uphill or downhill), attribute (highway, etc.), branch (intersection, etc.), etc. to which the current position of the vehicle belongs. Thus, the shift control is executed so as to switch the automatic transmission to an appropriate shift position. In addition to the automatic transmission, the vehicle control device 120 includes a suspension device, a lighting device, a steering device, a braking device, a prime mover (engine, motor, etc.), an air conditioner, an energy management device (gasoline, methanol, hydrogen, chemical battery, Fuel cells, etc.), visibility support devices (electronic mirrors, night vision devices, etc.), HMIs (display devices such as meters, operation devices such as switches), body control devices (power doors, power windows, power seats, etc.), security A device or the like may be controlled.

  The navigation device 100 includes a position detection unit 101, a digital road map database 102, a display device 103, an operation switch group 104, an audio output unit 105, an audio input unit 106, an external storage device 107, a VICS reception device 108, and a control device 110. ing.

  The control device 110 is configured as a normal computer, and includes a well-known CPU, ROM, RAM, I / O, and a bus line for connecting these configurations. In the ROM, a program to be executed by the control device 110 is written, and a CPU or the like executes predetermined arithmetic processing according to this program.

  A position detector 101 is a GPS receiver 101A for GPS (Global Positioning System) that measures the position of a vehicle based on radio waves from a satellite, a wheel speed sensor 101B for detecting the travel distance of the vehicle, and the travel of the vehicle. A gyro sensor 101C for detecting the azimuth is provided. Furthermore, the position detector 101 includes an acceleration sensor 101D that detects the traveling acceleration of the vehicle.

  As described above, the position detector 101 includes the GPS receiver 101A for vehicle position measurement by radio navigation, and the wheel speed sensor 101B, gyroscope 101C, and acceleration sensor 101D for vehicle position estimation by self-contained navigation. doing. The acceleration sensor 101D can be used for detecting the gradient of the road on which the vehicle travels and for detecting the travel distance of the vehicle. Further, the radio navigation is not limited to the GPS, but, for example, a VICS optical beacon may be used. Further, in order to detect the direction in the self-contained navigation, a geomagnetic sensor or a steering sensor may be used instead of the gyro sensor 101C.

  The digital road map database 102 is a device for inputting digital map data including road data, background data, and character data to the control device 110. The digital road map database 102 has a storage medium 102A for storing digital map data. As the storage medium 102A, a CD-ROM or DVD-ROM is generally used depending on the amount of data, but a memory card is used. A hard disk or the like may be used.

  Here, the configuration of road data will be described. The road data is composed of data such as a link ID with a unique number for each road, link coordinate data, node coordinate data, road type data indicating a road type such as an expressway or a national road, and road width data. . The link in the road data is obtained by dividing each road on the map into a plurality of nodes by nodes indicating intersections, branching points, etc., and defining a link between the two nodes. The link coordinate data describes the start and end coordinates of this link. When a node is included in the middle of the link, the node coordinates are described in the node coordinate data. In addition to displaying a map, this road data is used to give the shape of a road when performing map matching processing, or used when searching for a guide route to a destination.

  The background data is data for displaying the facility shape, natural terrain, and the like to be displayed other than the road when the road map is displayed on the display device 103. The character data is for displaying place names, facility names, road names, and the like on the road map, and is configured as data in which coordinates on the map corresponding to the display positions are associated. As for the facility, data such as a telephone number and an address are also stored in association with the facility name. The data regarding this facility may be stored in the external storage device 107 described later.

  The display device 103 is configured by, for example, a liquid crystal display, and the vehicle generated by the vehicle position mark corresponding to the current position of the vehicle on the screen of the display device 103 and the map data input from the digital road map database 102. The surrounding road map can be displayed. When a destination is set, a guidance route from the current position to the destination is displayed on the road map in an overlapping manner.

  The operation switch group 104 includes, for example, a touch panel switch integrated with the display device 103 or a mechanical switch provided around the display device 103, and is used for various inputs.

  The voice output unit 105 includes a speaker or the like, and outputs a guidance voice when route guidance is being performed, or outputs a guidance regarding input voice at the time of voice recognition. The voice input unit 106 includes a microphone or the like, and takes in a voice uttered by the user and inputs it to the control device 110. The control device 110 performs input speech recognition processing and executes various controls based on the recognition result.

  The external storage device 107 includes a storage medium such as a memory card or a hard disk. The external storage device 9 stores various data such as text data, image data, and audio data stored by the user.

  The VICS receiver 108 receives information such as road traffic information distributed from the VICS center via beacons laid on the road and FM broadcast stations in various places, and sends information from the vehicle side to the outside as necessary. It is a device that transmits. The received information is processed by the control device 110. For example, traffic jam information, regulation information, and the like are displayed on the road map displayed on the display device 103.

  In addition, when the destination position is input by the operation switch group 7 or voice recognition, the navigation device 100 according to the present embodiment automatically selects the optimum route from the current position to the destination and selects the guidance route. It also has a so-called route guidance function that is formed and displayed. As a method for automatically setting an optimum route, a known method such as the Dijkstra method is known. In addition, for example, a search function for searching for the position of a facility or the like from an address, a facility name, a telephone number or the like input by the user is also provided.

  These functions are executed mainly when various control processes are performed by the control device 110. That is, when the destination is input, the control device 110 calculates a route using the map data of the digital road map database 102, displays the route, and enlarges the road map at a branch point or an intersection to be turned right or left. Provide voice guidance. In addition, the control device 110 displays the vehicle position mark indicating the position of the vehicle and the road map around it on the display device 103 or changes the scale of the road map.

  In addition to executing the general navigation function as described above, the navigation device 100 according to the present embodiment provides the vehicle control device 120 with the calculated current position and the accuracy as an index indicating the certainty as current position related information. Send. The vehicle control device 120 changes the content of vehicle control using the current position of the vehicle based on the received current position related information.

  FIG. 2 is a flowchart showing a process for the navigation device 100 to generate current position related information and transmit it to the vehicle control device 120. First, in step (hereinafter abbreviated as S) 200, the current position is calculated by hybrid navigation, the current position calculated by the map matching process is adjusted on the road, and the final current position is calculated. The calculation method of the current position and the map matching process by these hybrid navigation will be described in detail later. The functional block displayed as the vehicle position specifying means 111 in the block diagram of FIG. 1 corresponds to the process of S200.

  Next, in S210, the accuracy as an index indicating the likelihood of the current position obtained by the hybrid navigation and the map matching process is calculated. A method for calculating the accuracy indicating the certainty of the current position will be described in detail later. In S220, the road shape ahead of the traveling direction of the vehicle is calculated from the current position based on the road map data. The functional block displayed as the road shape detecting means 112 in the block diagram of FIG. 1 corresponds to the processing of S220.

  Then, the current position, the accuracy of the current position, and the front road shape calculated in S200 to S220 are transmitted to the vehicle control device 120 as current position related information in S230.

  FIG. 3 is a flowchart illustrating a process in which the vehicle control device 120 receives current position related information and changes the contents of vehicle control using the current position of the vehicle based on the received current position related information. First, in S300, the current position related information transmitted from the navigation device 100 is received. In S310, it is determined whether or not the accuracy of the current position included in the current position related information satisfies the required accuracy as the vehicle control execution condition.

  If it is determined that the current position accuracy of the received current position related information satisfies the required accuracy, a control target value is set in S320 using the current position related information, that is, the current position and the road shape ahead. On the other hand, if it is determined that the current position accuracy of the current position related information does not satisfy the required accuracy, the control target value is set in S330 without using the current position related information. That is, whether or not to execute vehicle control using the current position is switched according to the probability of the current position by the processing of S310 to S330. In S340, vehicle control is executed based on the control target value set in S320 or S330. Note that the control target value may be changed stepwise between the control target value using the current position related information and the control target value not used according to the accuracy of the current position.

  Next, the hybrid navigation in the process of S200 described above will be described.

  In a navigation apparatus, there are a radio navigation method and a self-contained navigation method for measuring the current position of a vehicle. As represented by the global positioning system (GPS), the radio navigation receives radio waves from a satellite or the like, and calculates the current position (latitude, longitude) of the vehicle from the received information. The advantage of radio navigation is that the current position of the vehicle can be obtained as an absolute position while receiving radio waves. On the other hand, the disadvantage of radio navigation is that the vehicle position cannot be measured in tunnels or under elevated roads.

  In the self-contained navigation, for example, the current position of the own vehicle is estimated by integrating the movement distance calculated from the output signal of the vehicle speed sensor according to the direction calculated from the direction sensor such as a gyro sensor. The advantage of self-contained navigation is that it can always calculate the vehicle position without being affected by the surrounding environment. On the other hand, the disadvantage of the self-contained navigation is that the error of the sensor is accumulated because the movement distance is integrated according to the direction to obtain the own position, and the error increases as the movement distance becomes longer.

  Therefore, in the navigation device 100 of the present embodiment, the current position of the vehicle is calculated by hybrid navigation utilizing the advantages of both navigations by combining radio navigation and self-contained navigation. The calculation processing of the current position by this hybrid navigation is shown in the flowcharts of FIGS. 4 is a flowchart showing the entire hybrid navigation process, FIG. 5 is a flowchart showing the Kalman filter update process, and FIGS. 6 and 7 are flowcharts showing the update process based on time and the update process based on observation, respectively. . The hybrid navigation process shown in FIG. 4 and the Kalman filter update process shown in FIGS. 5 to 7 are performed in parallel.

  The use of the Kalman filter in positioning is a known technique. As shown in FIG. 5, the system state quantity that minimizes the square error is obtained by repeating the update based on time (S500) and the update based on observation (S510). presume. In this embodiment, the system state quantity to be estimated is, for example, a gyro offset error, a gyro gain correction coefficient error, a distance coefficient error, an absolute heading error, and a (latitude, longitude) absolute position error in self-contained navigation. The gyro offset, the gyro gain correction coefficient, the distance coefficient, the absolute azimuth, and the (latitude, longitude) absolute position in the result are used as reference observation values.

In the update process based on the time in FIG. 6, a prior estimated value x ⁻ _k of the system state vector is _obtained from Equation 1 below in S600.
(Formula 1) x ^- _k = Axk _-1
A is a process matrix.

Subsequently, in S610, a prior estimated value P ^- _k of the system state quantity covariance matrix is _obtained from the following Equation 2.
(Equation _{^{2) P - k = AP k}} -1 A T + Q
Note that ^AT represents a transposed matrix of the process matrix, and Q represents process noise. Further, in Expression 1 and Expression 2, the subscript k represents the number of steps.

In the update process based on the observation in FIG. 7, first, the Kalman filter gain K _k is calculated from the following Equation 3 in S700.
(Equation ^{_{3) K k = P - k}} H T (HP - k H T + R) -1
H represents an observation matrix, and R represents an observation error covariance matrix.

Further, in S710, a posteriori estimated value xk of the system state vector is _obtained from the following Equation 4.
(Equation ^{_{4) x k = x - k}} + K k (z k -Hx - k)
Z _k represents an observation vector.

Finally, in S720, a posteriori estimated value P _k of the system state quantity covariance matrix is _obtained from Equation 5 below.
(Formula 5) P _k = (I−K _k H) P ⁻ _k
I is a unit matrix. The diagonal components of P _k are covariances of gyro offset correction coefficient error, gyro gain correction error, distance coefficient error, absolute azimuth error, and (latitude, longitude) absolute position error, respectively.

  By repeating the update process based on the above time and the update process based on the observation, the estimation error of the system state quantity is rapidly reduced. In S430 of the hybrid navigation process shown in FIG. A gyro gain correction coefficient, a distance coefficient, an absolute direction, and an absolute position (latitude and longitude) are calculated.

  In S400 of FIG. 4, sensor output data from each sensor is acquired. In S410, the absolute direction is updated based on the direction data in the sensor output data. In S420, the absolute position (latitude, longitude) indicating the current position is updated based on the distance data in the sensor output data and the absolute direction updated in S410.

  Next, the map matching process in the process of S200 described above will be described.

  In the map matching process, the road on which the vehicle is traveling is estimated by comparing the vehicle travel locus obtained from the current position of the vehicle calculated by hybrid navigation with the road data stored in the road map database 102. This is a technique for obtaining a more accurate current position of the vehicle. The flow of this map matching process will be described based on the flowchart of FIG.

  First, in S800, a travel locus is calculated based on the vehicle position (absolute position and absolute direction) calculated by hybrid navigation. That is, the trajectory is obtained by connecting past vehicle positions in a section from the current vehicle position to a predetermined distance behind.

  Next, after the smoothing process is performed on the calculated travel locus in S810, a road that is a candidate for the map matching process is searched in S820. Specifically, a road belonging to a predetermined area centered on the current vehicle position (absolute position) is selected and set as a candidate road. Note that the candidate road search area may be variable according to the magnitude of the absolute position error calculated in the hybrid navigation.

  In S830, similarity determination between each of the selected candidate roads and the calculated travel locus is performed. Specifically, the road shape of the selected candidate road is compared with the shape of the traveling locus of the vehicle, and the height of similarity (correlation) is digitized. In S840, in the similarity determination in S830, the candidate road with the highest similarity is determined as the road on which the vehicle is traveling.

  In S850 and S860, when the azimuth and position calculated by the hybrid navigation are shifted by matching the current position and travel locus of the vehicle with the determined candidate road, the azimuth and position are corrected. In S870, the corrected azimuth and position are output as data indicating the current position of the vehicle.

  Next, the process of calculating the accuracy indicating the certainty of the current position in S210 of FIG. 2 will be described in detail based on the flowchart of FIG.

  First, in S900, as an initialization process, the accuracy A indicating the likelihood of the current position is reset to zero. In continuing S910, a sensor state determination process is performed. The details of the sensor state determination process are shown in the flowchart of FIG. That is, in the sensor state determination process, in S1000 to S1020, the vehicle speed sensor 101B, the gyro sensor 101B, and the acceleration sensor 101D are operating normally without any failure such as disconnection or short circuit, and each sensor is used. Determine if it is possible. This determination can be made, for example, by observing a change in output from each sensor.

If it is determined that all the sensors can be used, the process proceeds to S1030, where the determination result is “1”, and a value obtained by assigning a weight of “2 ⁷ ” to the determination result is added to the accuracy A. On the other hand, if any one of the sensors is determined to be unusable, the process proceeds to S1040 and the determination result is set to “0”. For this reason, the value obtained by assigning a weight to the determination result is also zero, and the value of the accuracy A remains zero.

Next, in S920 of the flowchart of FIG. 9, a positioning status determination process is performed. Details of the positioning status determination processing are shown in the flowchart of FIG. That is, in the positioning status determination process, in S1100, it is determined from the number of satellites receiving radio waves and the arrangement of satellites whether 3D positioning is possible with GPS. If it is determined in this step that 3D positioning is possible, the process proceeds to S1110, the determination result is set to “1”, and a value obtained by assigning a weight of “2 ⁶ ” to the determination result is added to the accuracy A. On the other hand, if the number of radio waves necessary for 3D positioning (usually 4 or more) cannot be received or if the reception is extremely unstable due to the arrangement of the satellites, the process proceeds to S1120, and the determination result is set to “0”. To do. For this reason, the value to which the weighting is added to the determination result is also zero, and the value of the accuracy A is not increased in the positioning situation determination process.

Furthermore, in S930 of the flowchart of FIG. 9, a sensor accuracy determination process is performed. Details of this sensor accuracy determination processing are shown in the flowchart of FIG. In the sensor accuracy determination process, the sensor accuracy of the wheel speed sensor 101B and the gyro sensor 101C is determined. That is, in S1200 to S1220, Po, Pg, and Pd are standard deviations of gyro offset error, gyro gain correction coefficient error, and distance coefficient error, respectively, and threshold values Po _Th , Pg _Th , Pd obtained experimentally, respectively. Compared with _Th . In these comparison processes, when it is determined that the standard deviations Po, Pg, and Pd of each error are equal to or less than the threshold values Po _Th , Pg _Th , and Pd _Th , the sensor accuracy is considered good. Accordingly, the process proceeds to S1230, where the determination result is “1”, and a value obtained by assigning a weight of “2 ⁵ ” to the determination result is added to the accuracy A.

On the other hand, if the standard deviations Po, Pg, Pd of any error exceed the threshold values Po _Th , Pg _Th , Pd _Th , the sensor accuracy is considered to have deteriorated. 0 ”. Thereby, in the sensor accuracy determination process, the value of the accuracy A is not increased.

Note that the standard deviations Po, Pg, and Pd of the gyro offset error, the gyro gain correction coefficient error, and the distance coefficient error are the square roots of the corresponding diagonal components of the Kalman filter system state quantity covariance matrix (post-estimated value) P _k described above. This is a value obtained as (standard deviation).

Next, in S940 of the flowchart of FIG. 9, an orientation deviation determination process is performed. Details of this azimuth deviation determination processing are shown in the flowchart of FIG. In the azimuth deviation determination process, as shown in FIG. 14, in S1300, as shown in FIG. 14, the absolute value of the relative azimuth θ between the road link corresponding to the current position obtained in the map matching process and the vehicle azimuth and the threshold obtained experimentally. The value θ _Th is compared. When the absolute value of the relative azimuth θ is equal to or less than the threshold value θ _Th , the traveling azimuth of the vehicle approximates the road azimuth, and the vehicle is considered to be traveling on the road. Therefore, the process proceeds to S1310, where the determination result is “1”, and a value obtained by assigning a weight of “2 ⁴ ” to the determination result is added to the accuracy A.

On the other hand, when the absolute value of the relative azimuth θ exceeds the threshold value θ _Th , it is considered that the vehicle is not traveling on the road. Therefore, the process proceeds to S1320, and the determination result is set to “0”. Therefore, in this case, the accuracy A is not increased in the azimuth deviation determination process.

Next, in S950 of the flowchart of FIG. 9, an error range determination process is performed. Details of the error range determination processing are shown in the flowchart of FIG. In the error range determination process, in S1400, the standard deviation L of the absolute position error in the vehicle azimuth direction is compared with the threshold value _LTh obtained experimentally. Note that the standard deviation L of the absolute position error in the vehicle azimuth direction is obtained as follows. First, the covariance σ ² _{xx of} the absolute position (longitude direction) error and the covariance σ ² _{yy of the} absolute position (latitude direction) error, which are elements of the system state quantity covariance matrix (posterior estimation value) P _k of the Kalman filter described above. The distribution regarding the absolute position error is determined from the covariance σ ² _{xy of} the absolute position (longitude direction) error and the absolute position (latitude direction) error. The standard deviation L of the absolute position error in the vehicle azimuth direction can be obtained from the distribution related to the absolute position error.

When the standard deviation L is less than or equal to the threshold value L _Th , the absolute position error is small, so the process proceeds to S1410, where the determination result is “1” and the determination result is given a weight of “2 ³ ”. Is added to the accuracy A. On the other hand, if the standard deviation L is greater than the threshold value L _Th is the absolute position error is large, the process proceeds to S1420, the determination result is "0". Therefore, in this case, the accuracy A is not increased in the error range determination process.

  Next, in S960 of the flowchart of FIG. 9, shape correlation determination processing is performed. Details of this shape correlation determination processing are shown in the flowchart of FIG. In the shape correlation determination process, the shape correlation coefficient C is obtained in S1500. As shown in FIG. 17, the shape correlation coefficient C is calculated as an average value of the difference between the vehicle orientation based on the positioning result and the corresponding road orientation on the map data in the section from the current position to the rear of the predetermined distance. The

This shape correlation coefficient C is compared with a threshold value C _Th obtained experimentally in S1510. When the shape correlation coefficient C is equal to or less than the threshold value _CTh , there is a high possibility that the vehicle is traveling on the road selected in the map matching process. Therefore, the process proceeds to S1520, where the determination result is “1”, and a value obtained by assigning a weight of “2 ² ” to the determination result is added to the accuracy A. On the other hand, the waveform correlation coefficient C when exceeding the threshold _{C Th,} the process proceeds to S1530, the determination result is "0". Therefore, in this case, the accuracy A is not increased in the shape correlation determination process.

Next, in S970 of the flowchart of FIG. 9, candidate number determination processing is performed. Details of this candidate number determination processing are shown in the flowchart of FIG. In the candidate number determination process, in S1600, as shown in FIG. 19, the number N of candidate roads belonging to a predetermined search area centered on the current position of the vehicle is obtained and compared with a predetermined threshold number N _Th . . In this determination, if the number N of candidate roads is equal to or less than the threshold number N _Th , the possibility of selecting an incorrect road in the map matching process is small, and the process proceeds to S1610. In S1610, the determination result is set to “1”, and a value obtained by assigning a weight of “2 ¹ ” to the determination result is added to the accuracy A. On the other hand, when the number N of candidate roads exceeds the threshold number N _Th , there is a high possibility that an incorrect road will be selected, so the process proceeds to S1620 and the determination result is set to “0”. Therefore, in this case, the accuracy A is not increased in the candidate number determination process.

  Next, in S980 of the flowchart of FIG. 9, continuity determination processing is performed. The details of this continuity determination process are shown in the flowchart of FIG. In the continuity determination process, the magnitude D of the displacement of the vehicle position is obtained in S1700. In S1710, the magnitude D of the displacement of the vehicle position is compared with a value obtained by multiplying the vehicle speed v at that time by the time dt required for the displacement D. That is, as shown in FIG. 21, as a result of the fitting to the road by the map matching process, the vehicle position may jump greatly. When the magnitude D of the displacement of the vehicle position exceeds a value obtained by multiplying the vehicle speed D and the time dt, it can be considered that such a jump has occurred. In this case, since the road position where the vehicle position is adjusted by the map matching process has changed, the vehicle position specified on the road by the map matching process is considered unstable. On the other hand, when the magnitude D of the displacement of the vehicle position is equal to or less than the value obtained by multiplying the vehicle speed v and the time dt, the vehicle position is continuously adjusted on the same road, and the vehicle position is stable. It is thought that.

Accordingly, in S1710, when the magnitude D of the displacement is equal to or less than the value obtained by multiplying the vehicle speed v and the time dt, the process proceeds to S1720, where the determination result is “1”, and the determination result is weighted by “2 ⁰ ”. The given value is added to the accuracy A. On the other hand, when the magnitude D of the displacement exceeds the value obtained by multiplying the vehicle speed v and the time dt, the process proceeds to S1630 and the determination result is set to “0”. Therefore, in this case, the accuracy A is not increased in the continuity determination process.

  Through the above-described processing, the accuracy A becomes a value corresponding to the certainty of the vehicle position calculated by the hybrid navigation and the certainty of the vehicle position adjusted on the road by the hybrid processing. Therefore, the accuracy A can be used as an index that universally indicates the accuracy of the obtained vehicle position.

  That is, with respect to various determination results for determining the likelihood of the vehicle position calculated by hybrid navigation and various determination results for determining the likelihood of the vehicle position fitted on the road by the hybrid process, Since weighting in consideration of the influence on the obtained vehicle position accuracy is given, an index (accuracy A) showing the accuracy of the finally obtained vehicle position with high accuracy can be obtained.

Further, when calculating the accuracy A by the processing of S910 to S980, the determination result of each step is set to “1” or “0”, and the weight given to the determination result is “2 ⁷ ” to “2 ⁰ ”, respectively. It was. Therefore, the determination result of each determination process and its weight can be expressed by 1-byte data, and the amount of data for indicating the accuracy A can be suppressed.

  The preferred embodiments of the present invention have been described above, but the present invention is not limited to the above-described embodiments and can be implemented with various modifications.

  For example, in the above-described embodiment, the determination result in each determination process is set to “1” or “0”, but the determination result of three or more stages is obtained depending on the value to be determined in each determination process. You may make it output.

  Further, in the above-described embodiment, eight determination results are obtained by the processing of S910 to S980, but at least the determination result for determining the probability of the vehicle position calculated by hybrid navigation and the map matching processing are used. As long as the determination result for determining the likelihood of the vehicle position is included, the number of determination results used for calculating the accuracy A is arbitrary.

It is a block diagram showing a schematic structure of a vehicle control system concerning an embodiment. 7 is a flowchart showing a process for the navigation device 100 to generate current position related information and transmit it to the vehicle control device 120. It is a flowchart which shows the process which the vehicle control apparatus 120 receives the present position relevant information, and changes the content of the vehicle control using the present position of a vehicle based on the received present position relevant information. It is a flowchart which shows the process of the whole hybrid navigation. It is a flowchart which shows the process which updates a Kalman filter. It is a flowchart which shows the update process based on time in the update of a Kalman filter. It is a flowchart which shows the update process based on observation in the update of a Kalman filter. It is a flowchart which shows the flow of a map matching process. It is a flowchart which shows the process which calculates the accuracy which shows the probability of the present position. It is a flowchart which shows the detail of the sensor state determination process in the flowchart of FIG. FIG. 10 is a flowchart showing details of positioning status determination processing in the flowchart of FIG. 9. FIG. It is a flowchart which shows the detail of the sensor precision determination process in the flowchart of FIG. FIG. 10 is a flowchart showing details of an orientation deviation determination process in the flowchart of FIG. 9. FIG. It is explanatory drawing for demonstrating a direction misalignment determination process. 10 is a flowchart showing details of error range determination processing in the flowchart of FIG. 9. 10 is a flowchart showing details of shape correlation determination processing in the flowchart of FIG. 9. It is explanatory drawing for demonstrating a shape correlation determination process. 10 is a flowchart showing details of candidate number determination processing in the flowchart of FIG. 9. It is explanatory drawing for demonstrating a candidate number determination process. It is a flowchart which shows the detail of the continuity determination process in the flowchart of FIG. It is explanatory drawing for demonstrating a continuity determination process.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Navigation apparatus 101 Position detection part 102 Digital road map database 102
103 Display Device 104 Operation Switch Group 105 Audio Output Unit 106 Audio Input Unit 107 External Storage Device 108 VICS Receiver 110 Control Device 111 Vehicle Position Identification Unit 112 Road Shape Detection Unit 120 Vehicle Control Device

Claims (12)

A radio navigation means for outputting a measured value of the vehicle position by radio navigation and a self-contained navigation means for estimating the position of the vehicle by self-contained navigation; and a measurement value by the radio navigation means and a vehicle estimated position by the self-contained navigation means. Based on the hybrid navigation means for calculating the vehicle position,
Road map data storage means for storing road map data;
Map matching for identifying the final vehicle position on the road by performing map matching processing based on the vehicle position calculated by the hybrid navigation means and the road map data stored in the road map data storage means Means,
When the hybrid navigation means calculates the vehicle position, a first determination means for determining the likelihood of the vehicle position and outputting the determination result;
When specifying the vehicle position on the road by the map matching process, a second determination unit that determines the likelihood of the vehicle position and outputs the determination result;
The determination result of the first determination unit and the determination result of the second determination unit are weighted more heavily than the determination result of the second determination unit with respect to the determination result of the first determination unit. A calculating means for calculating an added value of
Vehicle control means comprising: vehicle control means for changing the content of vehicle control using the final vehicle position specified by the map matching means based on the magnitude of the addition value calculated by the calculation means. system.   2. The first determination unit according to claim 1, wherein the first determination unit outputs the first determination result depending on whether or not each sensor for obtaining the estimated position of the vehicle by the self-contained navigation unit is normal. Vehicle control system.   The first determination means outputs a second determination result depending on whether or not the radio navigation means receives a radio wave necessary for outputting a measurement value of a vehicle position. The vehicle control system according to claim 1 or 2.   The first determination means calculates a detection error of each sensor for the self-contained navigation means to obtain an estimated position of the vehicle based on a measured value of the vehicle position by the radio navigation, and the detection error of each sensor is calculated. The vehicle control system according to any one of claims 1 to 3, wherein the third determination result is output depending on the size.   The first determination means calculates an error included in the vehicle position calculated by the hybrid navigation means, and outputs a fourth determination result depending on the magnitude of the error. The vehicle control system according to any one of claims 1 to 4.   When the first determination means outputs a plurality of determination results from the first determination result to the fourth determination result, the weight given to the output determination result is the first The vehicle control system according to claim 5, wherein the vehicle control system is set so as to decrease in order from the determination result to the fourth determination result.   The second determination means obtains a difference between the current vehicle position direction and the road direction in which the vehicle position is specified, and outputs a fifth determination result depending on the magnitude of the difference. A vehicle control system according to any one of claims 1 to 6.   The second determination means obtains a difference between a direction at the time of vehicle position calculation and a road direction in the road map data in a section from the current vehicle position to a predetermined distance behind, and depends on the magnitude of the difference The vehicle control system according to any one of claims 1 to 7, wherein a sixth determination result is output.   The second determination means obtains the number of candidate roads for the map matching process belonging to the search range set with the vehicle position as a reference, and outputs a seventh determination result depending on the number. The vehicle control system according to claim 1, wherein:   The second determination means obtains the magnitude of displacement of the previous and current vehicle positions with respect to the final vehicle position specified on the road by the map matching process, and depends on the magnitude of the displacement. 10. The vehicle control system according to claim 1, wherein the determination result of 8 is output.   When the second determination means outputs a plurality of determination results in the eighth determination result from the fifth determination result, the weight given to the output determination result is the fifth The weight given to the determination result is set to be smaller than at least the weight given to the first determination result, and becomes smaller in the order of the fifth determination result to the eighth determination result. The vehicle control system according to claim 10.   The vehicle control means includes at least one of an automatic transmission, a suspension device, a lighting device, a steering device, a braking device, a prime mover, an air conditioner, an energy management device, a visibility support device, a display device, an operation device, a body control device, and a security device. The vehicle control system according to any one of claims 1 to 11, wherein one is a control target.

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