Patent Publication Number: US-2022230452-A1

Title: On-vehicle system, externality recognition sensor, electronic control device

Description:
TECHNICAL FIELD 
     The present invention relates to an on-vehicle system, an externality recognition sensor, and an electronic control device. 
     BACKGROUND ART 
     The arithmetic device mounted in a vehicle is required to detect various objects present around the vehicle and deal with them. However, because of cost reduction, the arithmetic device does not always incorporate a computing unit with a high processing capacity. Patent Literature 1 discloses an object sensing device that includes image capture units for capturing images of the external world outside a host vehicle, and a processing device for sensing the objects to be sensed from the images captured by the image capture units. The processing device includes: a scene analysis unit for analyzing a travel scene of the host vehicle; a processing priority change unit for changing the sensing process priority of the object to be sensed, on the basis of the travel scene analyzed by the scene analysis unit; and a sensing object sensing unit for sensing the object to be sensed, on the basis of the sensing process priority changed by the processing priority change unit. 
     CITATION LIST 
     Patent Literature 
     
         
         Patent Literature 1: WO 2014/132747 
       
    
     SUMMARY OF INVENTION 
     Technical Problem 
     The invention described in Patent Literature 1 has room for improvement in terms of dealing with an environment in which there is a lot of information on the external world (externality information). 
     Solution to Problem 
     An on-vehicle system according to a first aspect of the present invention is an on-vehicle system that is mounted in a vehicle and provided with an electronic control device and an externality recognition sensor. The externality recognition sensor comprises a sensing unit that acquires pre-processing externality information through sensing operation. The system comprises: a condition calculation unit that, on the basis of the position of the vehicle, traveling direction of the vehicle, and map information, calculates a processing condition in which information identifying an area on the map is associated with processing priority of the pre-processing externality information acquired by the externality recognition sensor; and a processing object determination unit that, on the basis of the pre-processing externality information and the processing condition, creates externality information having a smaller amount of information than the pre-processing externality information. 
     An externality recognition sensor according to a second aspect of the present invention is an externality recognition sensor that is mounted in a vehicle. The sensor comprises: a sensing unit that acquires pre-processing externality information through sensing operation; a reception unit that acquires a processing condition created on the basis of the position of the vehicle, traveling direction of the vehicle, and map information in which information identifying an area on the map is associated with processing priority of the pre-processing externality information acquired by the externality recognition sensor; and a processing object determination unit that, on the basis of the pre-processing externality information and the processing condition, creates externality information having a smaller amount of information than the pre-processing externality information. 
     An electronic control device according to a third aspect of the present invention is an electronic control device that is mounted in a vehicle and connected to an externality recognition sensor that acquires pre-processing externality information through sensing operation, in which the electronic control device comprises: a condition calculation unit that, on the basis of the position of the vehicle, traveling direction of the vehicle, and map information, calculates a processing condition in which information identifying an area on the map is associated with processing priority of the pre-processing externality information acquired by the externality recognition sensor; a pre-processing externality information acquisition unit that acquires the pre-processing externality information from the externality recognition sensor; and a processing object determination unit that, on the basis of the pre-processing externality information and the processing condition, creates externality information having a smaller amount of information than the pre-processing externality information. 
     Advantageous Effects of Invention 
     According to the present invention, it is possible to deal with an environment in which there is a lot of externality information. Other issues, elements and effects will become apparent from the description of embodiments given below. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a general configuration diagram of an on-vehicle system according to the first embodiment of the present invention. 
         FIG. 2  is a hardware configuration diagram of the sensor processing unit and device processing unit. 
         FIG. 3  is a diagram which shows an example of the condition creation source. 
         FIG. 4  is a diagram which shows an example of the processing condition. 
         FIG. 5  is a diagram which shows an example of the intersection. 
         FIG. 6  is a diagram which shows an example of the terrain. 
         FIG. 7  is a diagram which shows an example of the route. 
         FIG. 8  is a diagram which shows an example of externality information. 
         FIG. 9  is a diagram which shows an example of the range calculated by range derivation equation f 1 . 
         FIG. 10  is a diagram which shows an example of the range calculated by range derivation equation f 2 . 
         FIG. 11  is a flowchart which shows the calculation process of range derivation equation f 1 . 
         FIG. 12  is a flowchart which shows the calculation process of range derivation equation f 2 . 
         FIG. 13  is a flowchart which shows operation of the on-vehicle system according to the first embodiment. 
         FIG. 14  is a flowchart which shows operation of the on-vehicle system according to the second embodiment. 
         FIG. 15  is a flowchart which shows operation of the on-vehicle system according to the third embodiment. 
         FIG. 16  is a general configuration diagram of the on-vehicle system according to the fourth embodiment. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     First Embodiment 
       FIG. 1  is a general configuration diagram of an on-vehicle system S 1  according to the present invention. The on-vehicle system S 1  is mounted in a vehicle and provided with an externality recognition sensor  1 , a navigation unit  2 , an electronic control device  3 , an actuator  4 , an input device  5 , and an own vehicle DB  6 . These are connected by signal lines as shown in  FIG. 1 . Hereinafter, the vehicle in which the on-vehicle system S 1  is mounted is called as the “own vehicle” in order to distinguish it from other vehicles. 
     The externality recognition sensor  1  detects the position of a landmark present around the own vehicle or the like as externality information. The externality recognition sensor  1  is, for example, a camera or laser radar or the like. Although  FIG. 1  shows that the on-vehicle system S 1  includes only one externality recognition sensor  1 , the on-vehicle system S 1  may include a plurality of externality recognition sensors  1 . The navigation unit  2  outputs information such as route, terrain, and the latitude and longitude of the own vehicle. The electronic control device  3  derives the position of the landmark and determines the method for controlling the own vehicle. 
     The actuator  4  is a steering wheel, brake, and accelerator which change the orientation and speed of the vehicle. Although  FIG. 1  shows that the on-vehicle system S 1  includes only one actuator  4 , the on-vehicle system S 1  may include a plurality of actuators  4 . The input device  5  reads, writes, and rewrites information which is stored in a sensor storage unit  12  of the externality recognition sensor  1  and information which is stored in a device storage unit  32  of the electronic control device  3 . The input device is, for example, a personal computer. The on-vehicle system S 1  may include a plurality of input devices  5 . The own vehicle DB  6  is a database which outputs the speed, yaw rate, and winker input condition of the own vehicle, and the steering angle of the steering wheel. The own vehicle DB  6  successively receives information on the speed, yaw rate and winker or steering wheel operation status of the own vehicle from a sensor (not shown) mounted in the own vehicle. 
     The externality recognition sensor  1  includes a sensor processing unit  11 , a sensor storage unit  12 , a sensing unit  13 , and a condition reception unit  14 . The hardware configuration of the sensor processing unit  11  will be described later. The sensor storage unit  12  is a nonvolatile memory area and for example, a flash memory or EEPROM (Electrically Erasable Programmable Read-Only Memory). The sensor processing unit  11  includes a processing object determination unit  111  and an externality information output unit  112 . The sensor storage unit  12  stores a processing condition  121 , externality information  122 , and pre-processing externality information  123 . 
     The sensing unit  13  is a combination of sensor components, for example, a light source and a light receiving element. The sensing unit  13  performs sensing in a given processing cycle and stores the pre-processing externality information  123  in the sensor storage unit  12 . The condition reception unit  14  receives a processing condition  322  from the electronic control device  3  and stores it as the processing condition  121  in the sensor storage unit  12 . The condition reception unit  14  is, for example, a communication module which conforms to CAN (registered trademark) or IEEE802.3. 
     The electronic control device  3  includes a device processing unit  31 , a device storage unit  32 , and a condition transmission unit  33 . The hardware configuration of the device processing unit  31  will be described later. The device storage unit  32  is a nonvolatile memory area and for example, a flash memory or EEPROM. The device processing unit  31  includes a condition calculation unit  311  and a vehicle control unit  312 . The device processing unit  31  stores the information received from the externality recognition sensor  1 , navigation unit  2  and own vehicle DB 6  in the device storage unit  32 . The device storage unit  32  stores a condition creation source  321 , processing condition  322 , terrain  323 , route  324 , and externality information  325 . The condition transmission unit  33  is, for example, a communication module which conforms to CAN or IEEE802.3. 
     As will be described in detail, the processing condition  121  stored in the sensor storage unit  12  and the processing condition  322  stored in the device storage unit  32  are the same. Also, the externality information  122  stored in the sensor storage unit  12  and the externality information  325  stored in the device storage unit  32  are the same. Specifically, the processing condition  322  is created by the condition calculation unit  311  and the processing condition  322  is transmitted from the electronic control device  3  to the externality recognition sensor  1  by the condition transmission unit  33  and stored in the sensor storage unit  12  as the processing condition  121 . Also, the externality information  122  is created by the externality information output unit  112  and the externality information  122  is transmitted from the externality recognition sensor  1  to the electronic control device  3  and stored in the device storage unit  32  as the external information  325 . This embodiment assumes that the processing condition  121  and processing condition  322  are the same in all aspects including the data storage method and the externality information  122  and externality information  325  are the same in all aspects including the data storage method, but instead they may be different in terms of the data storage method or data expression. 
     The configuration shown in  FIG. 1  merely shows a logical configuration and there is no limitation to the physical configuration. For example, an alternative physical configuration may be that the sensor processing unit  11  and sensor storage unit  12  are mounted in a device in which the electronic control device  3  is mounted. 
       FIG. 2  is a diagram which shows the hardware configurations of the sensor processing unit  11  and device processing unit  31 . The sensor processing unit  11  includes a CPU  10001  as a central processing unit, a ROM  10002  as a read-only memory, and a RAM  10003  as a readable and writable memory. The CPU  10002  expands the program stored in the ROM  10002  into the RAM  10003  and executes it to realize a processing object determination unit  111  and an externality information output unit  112 . 
     However, instead of the combination of the CPU  10001 , ROM  10002 , and RAM  10003 , the sensor processing unit  11  may be realized by an FPGA (Field Programmable Gate Array) as a rewritable logic circuit or an ASIC (Application Specific Integrated Circuit). Also, instead of the combination of the CPU  10001 , ROM  10002 , and RAM  10003 , the sensor processing unit  11  may be realized by a different combination, for example, a combination of the CPU  10001 , ROM  10002 , RAM  10003 , and an FPGA. 
     The device processing unit  31  includes a CPU  30001  as a central processing unit, a ROM  30002  as a read-only memory, and a RAM  30003  as a readable and writable memory. The CPU  30002  expands the program stored in the ROM  30002  into the RAM  30003  and executes it to realize a condition calculation unit  311  and a vehicle control unit  312 . However, instead of the combination of the CPU  30001 , ROM  30002 , and RAM  30003 , the device processing unit  31  may be realized by an FPGA or ASIC. Also, instead of the combination of the CPU  30001 , ROM  30002 , and RAM  30003 , the device processing unit  31  may be realized by a different combination, for example, a combination of the CPU  30001 , ROM  30002 , RAM  30003 , and an FPGA. 
     (Outline of Data) 
     Next, the data which is stored in the sensor storage unit  12  and device storage unit  32  will be outlined. The condition creation source  321  has previously been stored in the device storage unit  32  and the condition creation source  321  is not changed in the scope in which this embodiment is described. In this embodiment, the navigation unit  2  has created the route  324  in advance through user operation. The route  324  is information which indicates the travel route along which the own vehicle travels. The terrain  324  is information on nodes in an area including the route  324 . The processing condition  322  is created by the condition calculation unit  311  in reference to the position of the own vehicle, the condition creation source  321 , terrain  323 , and route  324 . Since the processing condition  322  is also influenced by the position of the own vehicle, the processing condition  322  is created with high frequency, for example, every 200 ms. 
     As mentioned above, the processing condition  322  and processing condition  121  are the same. The pre-processing externality information  123  is information on the area around the own vehicle which is collected by the externality recognition sensor  1 , and updated with high frequency, for example, every 200 ms. The externality information  122  is created by the externality information output unit  112  on the basis of the processing condition  121  and pre-processing externality information  123 . The externality information output unit  112  is transmitted to the electronic control device  3  and stored as the externality information  325  in the device storage unit  32 . The electronic control device  3  enters the externality information  325  into the vehicle control unit  312 . However, instead, the electronic control device  3  may not use the externality information  325  and may send the externality information  325  to another device connected to the electronic control device  3 . 
     (Condition Creation Source) 
       FIG. 3  is a diagram which shows an example of the condition creation source  321 . The condition creation source  321  has a plurality of records and each record has fields for condition  3211 , range derivation equation  3212 , priority  3212 , and processing granularity  3214 . The condition to which what is written in the record is applied is stored in the field for condition  3211 . For example, “IN ROUTE &amp; INTERSECTION” written in the first record in  FIG. 3  indicates a condition that the node is included in the route  324  and terrain  323  and the attribute of the node in the terrain  323  is “INTERSECTION”. 
     The derivation equation for deriving the range to which the priority and processing granularity written in the same record is applied is stored in the field for range derivation equation  3212 . The functions f 1  and f 2  shown in  FIG. 3  are range derivation equations which are separately defined and indicate the use of longitude, latitude, and rotation angle. A concrete example of a range derivation equation will be described later. “A derivation equation” is a concept and need not always be expressed by a numerical formula and for example, the process of derivation may be expressed, using a flowchart. 
     The order of priority in the process for the externality recognition sensor  1  to derive the landmark position is stored in the field for priority  3213 . In this embodiment, when the value in the field for priority is smaller, higher priority is given. The interval between landmark positions in landmark position output by the externality recognition sensor  1  is stored in the field for processing granularity  3214 . For example, processing granularity “1 point/1 m” denotes that a landmark position is output on the basis of one point per 1 m and “1 point/4 m” denotes that a landmark position is output on the basis of one point per 4 m. 
     (Processing Condition) 
       FIG. 4  is a diagram which shows an example of the processing condition  121  and processing condition  322 . Although the composition of the processing condition  322  is explained below, the composition of the processing condition  121  is the same. The processing condition  322  has a plurality of records and each record has fields for priority  3221 , processing granularity  3222 , area  3223 , and node  3224 . The fields for priority  3221  and processing granularity  3222  correspond to the fields for priority  3213  and processing granularity  3214  in the condition creation source  321  shown in  FIG. 3 . The field for area  3223  stores information on the object area to which the priority and processing granularity in the record are applied. 
     In the example shown in  FIG. 4 , the object area is a rectangle parallel to an axis set in the coordinate system with reference to the own vehicle and the minimum and maximum values of X coordinate and the minimum and maximum values of Y coordinate are stored in the area  3223 . However, the shape of the object area is not limited to a rectangle but instead it may be a parallelogram, trapezoid, rhomboid, or ellipse. Even when the object area is a rectangle, the information on the coordinates of the four corners of the rectangle may be stored in the field for area  3223 . The identifier of the node nearest to the area indicated in the field for area  3223  is stored in the field for node  3224 . However, the processing condition  121  and processing condition  322  may not have the field for node  3224 . 
     (Example of Intersection) 
       FIG. 5  is a diagram which shows an example of intersection C. Since terrain  323  and route  324  are explained using the example of intersection C shown in  FIG. 5 , intersection C is first explained. The intersection C shown in  FIG. 5  is an intersection where a road running south and north and a road running east and west intersect, in which the upward direction in the figure is north. In the example shown in  FIG. 5 , different nodes are set in each traveling direction on the roads. Specifically, node N 11  to node N  18  are set. For example, while node N 11  and node N 18  are both ends of the road shown on the lower side of the figure, they are set as different nodes because node N 11  is a node on the side for entering the intersection and node N 18  is a node on the side for leaving the intersection. Here, the ends of the road mean the ends nearest to the intersection. 
     Node N 11  covers lane L 111 , lane L 112 , and lane L 113 . Node N 12  covers lane L 121  and lane L 122 . The latitude of the end of lane L 111  is “La 1 ” and the longitude of the end of lane L 111  is “Lo 1 ”. Since lane L 111 , lane L 112 , and lane L 113  are arranged side by side horizontally, the latitude of the ends of lane L 112  and lane L 113  is also “La 1 ”. The longitude of the end of lane L 112  is “Lo 2 ” and the longitude of the end of lane L 113  is “Lo 3 ”. The longitudes of lane L 121  and lane L 122  covered by node N 12  are both “Lo 4 ”. The latitude of lane L 121  is “La 2 ” and the latitude of lane L 122  is “La 3 ”. 
     (Terrain) 
       FIG. 6  is a diagram which shows an example of terrain  323 . Terrain  323  is comprised of a plurality of records and each record has fields for node  3231 , attribute  3232 , lane  3233 , latitude  3234 , longitude  3235 , and azimuth  3236 . 
     The sign which denotes a representative point on the terrain is stored in the field for node  3231 . Representative points are set for each road connected to the intersection so that the traveling route of the own vehicle can be specified by specifying nodes in a sequential order. In addition, nodes are set for each vehicle traveling direction. For example, the intersection C shown in  FIG. 5  where four roads intersect has eight nodes (4×2). 
     The field for attribute  3232  indicates the attribute of the last road leading to the node in the record. For example, if the road just before the node in the record is linear, “linear” is stored in the attribute  3232  and if there is an intersection just before the node in the record, “intersection” is stored in the attribute. For example, in the intersection C shown in  FIG. 5 , for node N 11 , which is located in a position to enter the intersection C from the lower side in the figure, “linear” is stored in the attribute  3232 . For node  12 , which is located in a position to move leftward from the intersection C in the figure, “intersection” is stored in the attribute  3232 . 
     The information to identify the lanes covered by the node in the record is stored in the lane  3233 . For example, since node N 11  in the intersection C shown in  FIG. 5  covers three lanes, these lanes are written in the terrain  323  shown in  FIG. 6 . The latitudes of the ends of the lanes in the record are stored in the latitude  3234 . The longitudes of the ends of the lanes in the record are stored in the longitude  3235 . The direction of the lanes in the record is stored in the azimuth  3236 . The azimuth of a lane, for example, means the angle of the line obtained by linear approximation of the lane, with respect to true north. 
     (Route) 
       FIG. 7  is a diagram which shows an example of route  324 . Route  324  indicates the order in which the vehicle passes the nodes on the route along which the vehicle runs. For route  324 , the identifier of the node  3231  in the terrain  323  is used. In the example shown in  FIG. 7 , the nodes are listed in the order in which the vehicle runs, from top to bottom. 
     (Externality Information) 
       FIG. 8  is a diagram which shows an example of externality information  122  and externality information  325 . Although the composition of externality information  122  is explained below, the composition of externality information  325  is the same. Externality information  122  is comprised of a plurality of records and each record has fields for X coordinate  1221 , Y coordinate  1222 , and probability  1223 . The landmark position information with reference to the own vehicle is stored in the X coordinate  1221  and Y coordinate  1222 . Specifically, with the center of the own vehicle as the origin, the direction ahead of the own vehicle which passes through the center of the own vehicle is taken as the positive direction of X axis. 
     Furthermore, Y axis, which is perpendicular to the X axis, is defined and for example, the left of the own vehicle is taken as the positive direction of the Y axis. The index which indicates the correctness of the landmark position in the record is stored in the field for probability  1223 . In the example shown in  FIG. 8 , when the value stored in the probability  1223  is larger, correctness is higher. For example, when the externality recognition sensor  1  is a laser radar, the index stored in the probability  1223  is determined on the basis of the magnitude of reflection intensity difference between the road surface around the landmark position and the landmark position. 
     (Range Derivation Equation) 
     Next, the information which is stored in the range derivation equation  3212  in  FIG. 3  will be explained. As for the range derivation equation, there are a plurality of variations other than f 1  and f 2  shown in  FIG. 3  and each of them uses the terrain  323 , route  324 , and the position of the own vehicle. Next, two examples of range derivation equation will be explained referring to  FIG. 9  to  FIG. 12 . 
       FIG. 9  is a diagram which shows an example of the range calculated by range derivation equation f 1  and  FIG. 10  is a diagram which shows an example of the range calculated by range derivation equation f 2 .  FIG. 11  is a flowchart which shows the calculation process of range derivation equation f 1  and  FIG. 12  is a flowchart which shows the calculation process of range derivation equation f 2 .  FIG. 9  and  FIG. 10  show the intersection C shown above, and the terrain  323  is the one shown in  FIG. 6 . 
     As shown in  FIG. 9 , with the range derivation equation f 1 , when the vehicle travels from node N 11  to node N 12 , an area A 11  is calculated and when the vehicle travels from node N 11  to node N 14 , an area A 12  is calculated. As shown in  FIG. 10 , with the range derivation equation f 2 , when the vehicle travels from node N 11  to node N 12 , an area A 21  is calculated and when the vehicle travels from node N 11  to node N 14 , an area A 22  is calculated. The range derivation equation f 1  and range derivation equation f 22  calculate different areas even when the condition is the same. For example, the calculation of an area is performed as follows. 
     The process of calculation by the range derivation equation f 1  as shown in  FIG. 11  is explained below. Here, the node to which the own vehicle moves next is called “object node”. First, at Step S 411  the condition calculation unit  311  decides whether the route from the current position of the vehicle to the object node is straight or not. If it decides that the route is straight, it goes to Step S 412  and if it decides that the route is not straight, it goes to Step S 413 . At Step S 412 , the condition calculation unit  311  calculates an object area as an area from the current lane on which the own vehicle runs, to the object node, in which the area has the same width as the lane, for example, the area A 12  in  FIG. 9 . 
     At Step S 413 , the condition calculation unit  311  extracts a combination of lanes with the shortest distance. In the example shown in  FIG. 9 , among combinations of two lanes, each combination having one of the three lanes L 111 , L 112 , and L 113  covered by node N 11  and one of the two lanes L 121  and L 122  covered by node N 12 , the combination of lanes with the shortest distance is extracted. In this example, there are a total of six combinations and among them, the combination of lane L 113  and lane L 121  in which the distance is the shortest is extracted. 
     At the next step S 414 , the condition calculation unit  311  determines, as an object area, a rectangular area in which the ends of the lanes of the combination extracted at Step S 413  are opposite corners. In the example shown in  FIG. 9 , the rectangular area A 11  in which end E 113  of lane L 113  and end E 121  of lane L 121  are opposite corners is an object area. When Step S 412  or Step S 414  is completed, the process shown in  FIG. 11  is ended. 
     The process of calculation by the range derivation equation f 2  as shown in  FIG. 12  is explained below. However, explanations of the same steps as in the process of calculation by the range derivation equation f 1  are omitted. Since Step S 421  is the same as Step S 411 , its explanation is omitted. If a positive decision is made at Step S 421 , the condition calculation unit  311  goes to Step S 422  or if a negative decision is made at Step S 421 , it goes to Step S 423 . At Step S 422 , “the width of the lane on which the own vehicle is running” at Step S 412  is replaced by “the overall width of the node with which the own vehicle is running”. Therefore, the area A 22  shown in  FIG. 10  is an object area. 
     At Step S 423 , conversely to Step S 413 , a combination of lanes in which the distance is the longest is extracted. In the example shown in  FIG. 10 , lane L 111  and lane L 122  are extracted. The next step S 424  is the same as Step S 414 . However, since the combination of lanes extracted at the preceding step is different, in the example shown in  FIG. 10 , the rectangular area A 21  in which end Ell′ of lane L 111  and end E 122  of lane L 122  are opposite corners is an object area. 
     (Flowchart) 
       FIG. 13  is a flowchart which shows operation of the on-vehicle system S 1 . The on-vehicle system S 1  performs the process shown in  FIG. 13  in a given cycle, for example, 100 ms cycle. At Step S 101 , the condition calculation unit  311  acquires the terrain  323 , route  324 , the latitude, longitude, and azimuth of the own vehicle from the navigation unit  2  and acquires the speed, yaw rate, and steering angle of the own vehicle from the own vehicle DB. 
     At Step S 102 , the condition calculation unit  311  derives the range of latitude and longitude to be the processing object, on the basis of the latitude, longitude, and azimuth of the own vehicle as received at Step S 101  and a preset sensing range. The sensing range is preset in the device storage unit  32 , for example, as a rectangle which extends 100 m backward, 300 m forward, 200 m leftward and 200 m rightward from the own vehicle. At Step S 102 , for example, the latitudes and longitudes of the four points as the apexes of the rectangular area to be the processing object are calculated. 
     At Step S 103 , the condition calculation unit  311  detects the nodes included in the latitude/longitude range as the processing object as calculated at Step S 102 , among the nodes included in the terrain  323  received at Step S 101 . For example, if the terrain  323  is expressed as shown in  FIG. 6 , a node in which a representative point of a lane covered by each node, for example, the latitude and longitude of the first listed lane, is included in the latitude/longitude range derived at Step S 102  as the processing object is detected. 
     At Step S 104 , the condition calculation unit  311  calculates the processing condition  322  using the condition creation source  321 . For example, if the condition creation source  321 , terrain  323 , and route  324  are expressed as shown in  FIG. 3 ,  FIG. 6 , and  FIG. 7  respectively, the condition calculation unit  311  operates as follows. Namely, the condition calculation unit  311  search for a node which meets a condition among the conditions included in the condition creation source  321  in the order from top, calculates the range in accordance with the range derivation equation set in the same line, and records it as an area  3223  in the processing condition  322 . Furthermore, it records the priority  3213  and processing granularity  3214  set in the same line in the processing condition  322 , as priority  3221  and processing granularity  3222 . 
     For example, if the condition set in the first line of the condition creation source in  FIG. 3  is “in route &amp; intersection”, a node with “intersection” as the attribute in the terrain  323  in  FIG. 6  is searched from among the nodes included in the route  324  in  FIG. 7  and “N 12 ” is extracted. Then, in the same manner, the range is derived in accordance with the range derivation equation “f 1  (La, Lo, θ) to derive the latitude range la 1  to La 2  and longitude range Lo 3  to Lo 4 . Then, in the same manner, “1” as priority and “1 point/1 m” as processing granularity which are set in the first line of the condition creation source  321  in  FIG. 3  are written in the processing condition  322 . At this time, processing granularity may be converted so as to be expressed by a relative magnification ratio (2) with respect to prescribed processing granularity (½ m). By carrying out the same process for each of the second and subsequent lines of the condition creation source  321  in  FIG. 3 , priority  3221  and processing granularity  3222  can be determined as shown in  FIG. 4  for all the lines of the condition creation source  321  in  FIG. 3 . 
     At Step S 105 , the condition calculation unit  311  estimates the position and azimuth of the own vehicle in the next cycle on the basis of the information received from the own vehicle DB  6  at Step S 101  and shifts and rotates the range calculated at Step S 104  for correction. For example, if it receives the latitude/longitude, azimuth, speed and yaw rate of the own vehicle and the corresponding time from the own vehicle DB  6 , it calculates the amount of change in the position and azimuth of the own vehicle at the time of the next cycle in the case that the own vehicle runs at the same speed and the same yaw rate until the time of the next cycle. Then, it determines the following rectangle as a range corrected by shift/rotation: a rectangle including the range obtained by converting the range calculated at Step S 104 , for example, the latitude range La 1  to La 2  and longitude range Lo 3  to Lo 4 , into an own vehicle-centered coordinate system with the own vehicle position and azimuth in the next cycle, for example, the coordinate range X 11  to Xul in the traveling direction and the coordinate range Yll to Yul in the left-right direction. 
     At Step S 106 , the condition calculation unit  311  creates the processing condition  322  by combining the priority  3221  and processing granularity  3222  calculated at Step S 104  and the range corrected by shift/rotation at Step S 105 , and sends it to the processing object determination unit  111 . 
     At Step S 107 , the processing object determination unit  111  of the externality recognition sensor  1  derives the externality information  122  according to the processing condition  322  sent at Step S 106 . For example, if the processing condition is expressed as shown in  FIG. 4 , it searches the first line in which the highest priority “1” is set. As a result of searching, if a plurality of lines with the same priority are found, processing is performed in accordance with the rule preset in the sensor storage unit  12 , for example, a rule that processing should be performed in the ascending order from the lowest line number. Then, according to the range and processing granularity set in the line extracted as a result of searching, the externality information  122  (X, Y) detected in the range is identified by the specified processing granularity. At this time, if the externality recognition sensor  1  has the function to set probability for each landmark position, probability may be set for each landmark position as shown in  FIG. 8 . 
     The function to set probability is, for example, the function to set probability according to the landmark edge position error which depends on the degree of landmark blurring or the surrounding illuminance. Processing as mentioned above may be also performed in accordance with the rule preset in the sensor storage unit  12 . The rule is, for example, that processing should be repeated until the number of landmark positions reaches the upper limit number  64  or that if the upper limit number is exceeded during processing for a certain range, processing should be performed in order from the landmark position near the own vehicle until the upper limit number is reached. 
     At Step S 108 , the externality information output unit  112  sends the externality information  122  derived at Step S 107  to the vehicle control unit  312 . The received landmark position information is stored as externality information  325 , for example, in the device storage unit  32 . The externality information  325  may be discarded after vehicle control processing by the vehicle control unit  312 . 
     According to the above first embodiment, the following effects are produced. 
     (1) The on-vehicle system S 1  is mounted in a vehicle and provided with an electronic control device  3  and an externality recognition sensor  1 . The externality recognition sensor  1  includes a sensing unit  13  for acquiring pre-processing externality information  123  through sensing operation. The on-vehicle system S 1  includes: a condition calculation unit  311  that, on the basis of the vehicle position, vehicle traveling direction, and map information, calculates a processing condition  322  in which information identifying an area on the map is associated with the processing priority of the pre-processing externality information  123  acquired by the externality recognition sensor; and a processing object determination unit  111  that, on the basis of the pre-processing externality information  123  and the processing condition  121 , creates externality information  122  having a smaller amount of information than the pre-processing externality information  123 . Therefore, even in an environment with a lot of externality information such as an intersection, information on feature points of an area with high priority, namely externality information  122  smaller in the amount of information than the pre-processing externality information  123  is created and thus even when the electronic control device  3  does not have a high computing capacity, it can perform required processing. 
     (2) The processing condition  121  is the priority  3221  and processing granularity  3222  as spatial density of output which are associated with the area  3223  on the map. Therefore, information is obtained not only according to area selection by priority, but also according to processing granularity set for each area. 
     (3) The externality information  122  is information concerning landmarks, and processing of pre-processing externality information  123  is the process to derive the feature points of a landmark. Therefore, landmark information which depends on the processing condition  322  can be obtained as externality information  122 . 
     (4) A landmark is a lane mark present on a road and the processing granularity  3222  is point density in derivation of feature points of the lane mark. Therefore, when the processing granularity  3222  is higher, a larger number of feature points can be derived from one detected lane mark per unit length. 
     (5) The condition calculation unit  311  identifies the vehicle traveling direction on the basis of the position of the vehicle and the route  324  which is a previously calculated traveling route of the vehicle. Therefore, it is possible to acquire adequate area information with high density according to the traveling route of the vehicle. In addition, if an area in which the vehicle will not travel is previously known, for example, if the vehicle is going to take a left turn at the intersection, it is possible that the externality information  122  does not include information on the area on the right-turn side and the area for the vehicle to run straight. 
     (6) The electronic control device  3  includes a condition calculation unit  311  and a condition transmission unit  33  for transmitting the processing condition  322  to the externality recognition sensor  1 . The externality recognition sensor  1  includes a sensing unit  13  and a processing object determination unit  111 . 
     (7) The externality recognition sensor  1  is mounted in a vehicle and provided with: a sensing unit  13  that acquires pre-processing externality information through sensing operation; a condition reception unit  14  that acquires the processing condition  121  which is created on the basis of the vehicle position, vehicle traveling direction, and map information, and in which information identifying an area on the map is associated with the processing priority of the pre-processing externality information acquired by the externality recognition sensor; and a processing object determination unit  111  that creates externality information  122  having a smaller amount of information than the pre-processing externality information  123 , on the basis of the pre-processing externality information  123  and processing condition  121 . Therefore, even in an environment with a lot of externality information such as an intersection, the externality recognition sensor  1  creates information on feature points of an area with high priority, namely externality information  122  smaller in the amount of information than the pre-processing externality information  123 , on the basis of the calculated processing condition  322 . Consequently, even when the electronic control device  3  does not have a high computing capacity, it can deal with an intersection with a lot of information. 
     (Variation 1) 
     The device storage unit  32  of the electronic control device  3  may store a plurality of condition creation sources  321  so that the condition calculation unit  311  decides which condition creation source  321  to be used, on the basis of the information indicating the country/region where the own vehicle is travelling, which is acquired from the navigation unit  2 . For example, the condition calculation unit  311  may calculate the processing condition  322 , using the condition creation source  321  which differs according to whether the country or region has a traffic rule that a vehicle should run on the right side in the traveling direction or a traffic rule that a vehicle should run on the left side in the traveling direction. 
     (Variation 2) 
     In the above first embodiment, the externality recognition sensor  1  outputs information on the feature points of a landmark which is a stationary object, as externality information  122 . However, instead the externality recognition sensor  1  may detect a moving object, such as another vehicle, a pedestrian or bicycle and output the information. 
     (Variation 3) 
     In the above first embodiment, the processing condition  322  includes processing granularity  3222 . However, the processing condition  322  need not include processing granularity  3222 . Even if that is the case, the externality information  122  includes not the landmark information on all the areas around the own vehicle but the landmark information only on the object area, so the same effects as in the first embodiment can be produced. 
     Second Embodiment 
     Next, the on-vehicle system according to the second embodiment will be described referring to  FIG. 14 . In the explanation below, the same elements as in the first embodiment are designated by the same reference signs and different points are mainly described. Points that are not described below are the same as in the first embodiment. This embodiment is mainly different from the first embodiment in that the processing condition  322  is changed according to the externality information  325  in the past. This makes it possible to collect more information that is important for control of the vehicle, without an increase in the total volume of processing, so higher safety can be ensured with the same volume of processing. 
     The hardware configuration and functional configuration of the on-vehicle system are the same as in the first embodiment. In the second embodiment, processing by the on-vehicle system is increased as follows. Specifically, Step S 511 , which is explained below, is added between Step S 504  and Step S 505 . 
       FIG. 14  is a flowchart which shows processing in the on-vehicle system according to the second embodiment. Explanations of the same steps as in the first embodiment are omitted. At Step S 511  to be carried out next to Step S 504 , the condition calculation unit  311  rewrites at least one of the priority and processing granularity calculated at Step S 104  according to the probability in the externality information  325  received from the externality information output unit  112 . 
     For example, the condition calculation unit  311  may lower the processing granularity for an area on which information with high probability has already been acquired, to decrease the number of output points for the area or lower its priority to make the output more difficult. Specifically, for example, the pieces of externality information  325  acquired just before are rearranged in the ascending order of X coordinate values and a range which has higher probability than a prescribed threshold, for example, 80 and is continuous is identified and the priority of the range is changed to “3” and the processing granularity is changed to “1 point/5 m”. 
     According to the above second embodiment, the following effects are produced. 
     (8) The externality information  122  includes probability  1223  that indicates the degree of correctness. The condition calculation unit  311  corrects the processing condition according to probability  1223 . Therefore, the condition calculation unit  311  can correct the processing condition  322  according to the information on the surroundings which has been acquired in the past. 
     (9) If the probability for an area in the acquired externality information  325  is a prescribed value or more, the condition calculation unit  311  lowers the priority for the area in the processing condition  322 . Therefore, more information which is important for control of the vehicle can be collected without an increase in the total volume of processing, so higher safety can be ensured with the same volume of processing. 
     Third Embodiment 
     Next, the on-vehicle system according to the third embodiment will be described referring to  FIG. 15 . In the explanation below, the same elements as in the first embodiment are designated by the same reference signs and different points are mainly described. Points that are not described below are the same as in the first embodiment. This embodiment is mainly different from the first embodiment in that the processing condition  322  is adjusted according to vehicle steering action. This makes it possible to collect more information which is important for control of the vehicle, without an increase in the total volume of processing, even if the user moves the vehicle in a direction different from the prescribed route, so an effect that higher safety can be ensured with the same volume of processing is expected. 
       FIG. 15  is a flowchart which shows processing in the on-vehicle system according to the third embodiment. The steps up to Step S 503  are the same as in the first embodiment and their explanations are omitted. Next to Step S 503 , the condition calculation unit  311  decides whether the steering angle is consistent with the route or not. For example, if the steering angle is consistent with the route, it decides whether at the time to take a left turn, the steering angle is consistent with the angle to turn left or not. If the condition calculation unit  311  decides that the steering angle is consistent with the route, it goes to Step S 504  or if it decides that the steering angle is not consistent with the route, it goes to Step S 522 . 
     At Step S 504 , as in the first embodiment, it calculates the range, priority, and processing granularity using the route information and goes to Step S 505 . At Step S 522 , the condition calculation unit  311  estimates a node ahead of the own vehicle. At the next step S 523 , the condition calculation unit  311  calculates the range, priority, and processing granularity using the node estimated at Step S 522  and goes to Step S 505 . Step S 505  and subsequent steps are the same as in the first embodiment and their explanations are omitted. 
     According to the third embodiment, the following effect is produced. 
     (10) The condition calculation unit  311  identifies the traveling direction of the vehicle on the basis of the position of the vehicle, the previously calculated traveling route of the vehicle or the steering angle of the vehicle. Therefore, it can deal with a case that the vehicle runs out of the route  324 . 
     Fourth Embodiment 
     Next, the on-vehicle system according to the fourth embodiment will be described referring to  FIG. 16 . In the explanation below, the same elements as in the first embodiment are designated by the same reference signs and different points are mainly described. Points that are not described below are the same as in the first embodiment. This embodiment is mainly different from the first embodiment in that the electronic control device includes a processing object determination unit. 
       FIG. 16  is a general configuration diagram of the on-vehicle system S 4  according to the fourth embodiment. All the elements of the on-vehicle system S 4  are included in the on-vehicle system S 1  according to the first embodiment. However, the locations of specific functions are different. Specifically, whereas in the first embodiment the processing object determination unit  111  is located in the externality recognition sensor  1 , in this embodiment it is located as a processing object determination unit  313  in the electronic control device  3 . The processing object determination unit  313  operates in the same way as the processing object determination unit  111  in the first embodiment. 
     In this embodiment, the electronic control device  3  need not send the calculated processing condition  322  to the externality recognition sensor  1 , so it need not include the condition transmission unit  33 . The externality recognition sensor  1  does not include the processing object determination unit  111 , externality information output unit  112 , and condition reception unit  14 . However, the externality recognition sensor  1  includes a pre-processing externality information output unit  113  that sends the acquired pre-processing externality information  123  to the electronic control device  3 . 
     According to the above fourth embodiment, the following effects are produced. 
     (11) The electronic control device  3  includes a condition calculation unit  311  and a processing object determination unit  313 . The externality recognition sensor  1  includes a pre-processing externality information output unit  113  that sends the pre-processing externality information  123  to the electronic control device  3 . Therefore, the vehicle control unit  312  of the electronic control device  3  takes only the externality information  325  calculated by the processing object determination unit  313  using the processing condition  322 , as the processing object, so that it can deal with an intersection with a lot of information. 
     (12) The electronic control device  3  is mounted in a vehicle and connected to the externality recognition sensor  1  that acquires the pre-processing externality information  123  through sensing operation. The electronic control device  3  includes: a condition calculation unit  311  that, on the basis of the vehicle position, vehicle traveling direction, and map information, calculates a processing condition  322  in which information identifying an area on the map is associated with the processing priority of the pre-processing externality information  123  acquired by the externality recognition sensor  1 ; a pre-processing externality information acquisition unit  34  that acquires the pre-processing externality information  123  from the externality recognition sensor  1 ; and a processing object determination unit  313  that, on the basis of the pre-processing externality information  123  and the processing condition  322 , creates externality information  325  having a smaller amount of information than the pre-processing externality information  123 . 
     In the abovementioned embodiments and variations, the functional block configurations are just examples. Some of the functional blocks separately shown in the figures may be integrated or one functional block shown in the figures may be divided into two or more functional blocks. Furthermore, some of the functions in a functional block may be transferred to another functional block. 
     The abovementioned embodiments and variations may be combined. Various embodiments and variations have been described above but the present is not limited thereto. Other embodiments that are within the scope of the technical idea of the present invention are also included in the scope of the present invention. 
     The disclosure of the following priority basic application is incorporated herein as a citation. 
     Japanese Patent Application 2019-90541 (filed on May 13, 2019). 
     LIST OF REFERENCE SIGNS 
     
         
         
           
               1  . . . externality recognition sensor, 
               3  . . . electronic control device, 
               13  . . . sensing unit, 
               14  . . . condition reception unit, 
               33  . . . condition transmission unit, 
               34  . . . pre-processing externality information acquisition unit, 
               111  . . . processing object determination unit, 
               112  . . . externality information output unit, 
               113  . . . pre-processing externality information output unit, 
               121 ,  322  . . . processing condition, 
               122 ,  325  . . . externality information, 
               123  . . . pre-processing externality information, 
               311  . . . condition calculation unit, 
               313  . . . processing object determination unit, 
               321  . . . condition creation source, 
               323  . . . terrain, 
               324  . . . route