In-vehicle system, externality detection sensor, electronic control device

Abstract

In-vehicle system designed to be installed in a vehicle and equipped with an electronic control device (3) and an externality detection sensor (1), wherein the externality detection sensor (1) includes a detection unit for acquiring preprocessing externality information (123) by a detection operation and The system includes the following: a condition calculation unit (311) that calculates a processing condition (121, 322) based on the vehicle's position, the vehicle's direction of travel, and map information, wherein information identifying an area on the map is assigned a processing priority of the preprocessing externality information (123) acquired by the externality detection sensor (1); and a processing object determination unit (111) that, based on the preprocessing externality information (123) and the processing condition (121, 322), creates externality information (122, 325) that contains a smaller amount of information than the preprocessing externality information (123), wherein the externality information (122, 325) contains a probability that indicates a degree of correctness, and the condition calculation unit (311) corrects the processing condition (121, 322) according to the probability, and wherein then, if the probability of a first area in the captured externality information (122, 325) is a predefined value or more, the condition calculation unit (311) lowers the priority of the first area in the processing condition (121, 322).

Description

Technical field

[0001] The present invention relates to a vehicle-internal system, an externality detection sensor and an electronic control device. Technical background

[0002] The arithmetic device mounted in a vehicle must detect and process various objects present near the vehicle. However, to reduce costs, the arithmetic device does not always include a computing unit with high processing capacity. Patent literature 1 discloses an object detection device comprising image acquisition units for capturing images of the outside world beyond a carrier vehicle, and a processing device for identifying the objects to be detected from the images captured by the image acquisition units.The processing device includes the following: a scene analysis unit for analyzing a motion scene of the carrier vehicle; a processing priority change unit for changing the acquisition process priority of the object to be acquired based on the motion scene analyzed by the scene analysis unit; and an acquisition signal acquisition unit for acquiring the object to be acquired based on the acquisition process priority changed by the processing priority change unit.

[0003] DE 10 2014 117 751 A1 discloses methods and systems for the dynamic prioritization of target areas to be monitored in the vicinity of a vehicle. The system comprises a sensor, a GPS receiver, and a processor that communicates with the sensor and GPS receiver. The processor is configured to perform the following functions: determining the vehicle's location, direction, and position based on GPS receiver data; determining the predicted trajectory of the vehicle; prioritizing target areas based on the determined location, direction, and trajectory; and analyzing sensor data based on the prioritized target areas.

[0004] DE 10 2006 061390 A1 discloses an environment detection system for a motor vehicle in which sensor data are converted into an environment map with cells using a probability method, to which probability values ​​for the presence of objects are assigned. A selection unit determines a preferred spatial area for which information is specifically collected, and a control unit controls the sensors accordingly.

[0005] DE 10 2013 207 905 A1 discloses a method for providing occupancy information about sections of a vehicle's environment, comprising: determining the vehicle's driving situation; determining the position and geometric shape of sections of the environment for which occupancy information is to be determined, depending on the specific driving situation; determining occupancy information for each section based on the probability of an object or part of an object being present in the respective section; and storing the occupancy information determined for each section in a data structure. List of prior art patent literature

[0006] Patent literature 1: WO 2014 / 132 747 A1 Summary of the invention: Technical problem

[0007] The invention, which is described in patent literature 1, offers room for improvement with regard to dealing with an environment in which a lot of information about the outside world (externality information) is available. Solution to the problem

[0008] The aforementioned problem is solved by the invention according to the independent claims. Further preferred embodiments are described in the dependent claims. Advantageous effects of the invention

[0009] According to the present invention, it is possible to deal with an environment containing a large amount of externality information. Further problems, elements, and effects will become clear from the description of the embodiments given below. Brief description of the drawings Fig. Figure 1 is a general configuration diagram of a vehicle-internal system according to the first embodiment of the present invention. Fig. Figure 2 is a hardware configuration diagram of the sensor processing unit and the device processing unit. Fig. Figure 3 is a diagram showing an example of the condition generation source. Fig. Figure 4 is a diagram showing an example of the processing condition. Fig. Figure 5 is a diagram showing an example of the intersection. Fig. Figure 6 is a diagram showing an example of the terrain. Fig. Figure 7 is a diagram showing an example of the route. Fig. Figure 8 is a diagram showing an example of externality information. Fig. Figure 9 is a diagram showing an example of the range calculated using the range derivation equation f1. Fig. Figure 10 is a diagram showing an example of the range calculated by the range derivation equation f2. Fig. Figure 11 is a flowchart showing the calculation process of the domain derivation equation f1. Fig. Figure 12 is a flowchart showing the calculation process of the domain derivation equation f2. Fig. Figure 13 is a flowchart showing the operation of the vehicle's internal system according to the first embodiment. Fig. Figure 14 is a flowchart showing the operation of the vehicle's internal system according to the second embodiment. Fig. Figure 15 is a flowchart showing the operation of the vehicle's internal system according to the third embodiment. Fig. Figure 16 is a general configuration diagram of the vehicle's internal system according to the fourth embodiment. Description of the embodiments: First embodiment

[0010] Fig. Figure 1 is a general configuration diagram of an in-vehicle system S1 according to the present invention. The in-vehicle system S1 is mounted in a vehicle and is equipped with an externality detection sensor 1, a navigation unit 2, an electronic control device 3, an actuator 4, an input device 5, and a carrier vehicle DB 6. These are connected by signal lines, as shown in Figure 1. Fig. Figure 1 is shown. In the following, the vehicle in which the in-vehicle system S1 is installed will be referred to as the “carrier vehicle” to distinguish it from other vehicles.

[0011] The externality detection sensor 1 detects the position of an orientation point present around the carrier vehicle or the like as externality information. The externality detection sensor 1 is, for example, a camera or a laser radar or the like. Although Fig. Figure 1 shows that the vehicle's internal system S1 contains only one externality detection sensor 1; however, the vehicle's internal system S1 can contain multiple externality detection sensors 1. The navigation unit 2 outputs information such as a route, terrain, and the latitude and longitude of the carrier vehicle. The electronic control device 3 derives the position of the reference point and determines the procedure for controlling the carrier vehicle.

[0012] Actuator 4 is a steering wheel, a brake, and an accelerator pedal that change the vehicle's orientation and speed. Although Fig. Figure 1 shows that the vehicle-internal system S1 contains only one actuator 4; however, the vehicle-internal system S1 can contain multiple actuators 4. Information stored in a sensor memory unit 12 of the externality detection sensor 1 and information stored in a device memory unit 32 of the electronic control device 3 are read, written, and rewritten by the input device 5. The input device is, for example, a personal computer. The vehicle-internal system S1 can contain multiple input devices 5. The carrier vehicle database 6 is a database that outputs the speed, yaw rate, and turn signal input conditions of the carrier vehicle and the steering angle of the steering wheel.The carrier vehicle DB 6 sequentially receives information about the speed, yaw rate, and turn signal or steering wheel operation status of the carrier vehicle from a sensor (not shown) mounted in the carrier vehicle.

[0013] The externality detection sensor 1 comprises a sensor processing unit 11, a sensor storage unit 12, a detection unit 13, and a condition receiving unit 14. The hardware configuration of the sensor processing unit 11 is described later. The sensor storage unit 12 is a non-volatile memory area and, for example, a flash memory or an EEPROM (electrically erasable programmable read-only memory). The sensor processing unit 11 comprises 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 preprocessing externality information 123.

[0014] The sensing unit 13 is a combination of sensor components, e.g., a light source and a light-receiving element. The sensing unit 13 performs a sensing operation in a given processing cycle and stores the preprocessing externality information 123 in the sensor memory unit 12. The condition receiver unit 14 receives a processing condition 322 from the electronic control device 3 and stores it as the processing condition 121 in the sensor memory unit 12. The condition receiver unit 14 is, for example, a communication module that complies with CAN (registered trademark) or IEEE 802.3.

[0015] The electronic control device 3 comprises 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 is described later. The device storage unit 32 is a non-volatile memory area and is, for example, flash memory or an EEPROM. The device processing unit 31 comprises a condition calculation unit 311 and a vehicle control unit 312. The device processing unit 31 stores the information received from the externality detection sensor 1, the navigation unit 2, and the carrier vehicle DB 6 in the device storage unit 32. The device storage unit 32 stores a condition generation source 321, a processing condition 322, a terrain 323, a route 324, and externality information 325. The condition transmission unit 33 is, for example, aa communication module that complies with CAN or IEEE 802.3.

[0016] As 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 identical. Furthermore, the externality information 122, stored in the sensor storage unit 12, and the externality information 325, stored in the device storage unit 32, are identical. Specifically, the processing condition 322 is generated by the condition calculation unit 311 and is sent by the condition transmission unit 33 from the electronic control device 3 to the externality detection sensor 1 and stored in the sensor storage unit 12 as the processing condition 121.Furthermore, the externality information 122 is generated by the externality information output unit 112 and is sent by the externality detection 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 the processing condition 322 are identical in all aspects including the data storage procedure, and that the externality information 122 and the externality information 325 are identical in all aspects including the data storage procedure, but they may differ with respect to the data storage procedure or the data expression.

[0017] The configuration that is in Fig. Figure 1 shows only a logical configuration and does not represent a restriction of the physical configuration. For example, an alternative physical configuration could be that the sensor processing unit 11 and the sensor storage unit 12 are mounted in a fixture in which the electronic control device 3 is mounted.

[0018] Fig. Figure 2 is a diagram showing the hardware configurations of the sensor processing unit 11 and the device processing unit 31. The sensor processing unit 11 contains a CPU 10001 as a central processing unit, a ROM 10002 as a read-only memory, and a RAM 10003 as a read / write memory. The CPU 10002 extends the program stored in the ROM 10002 into the RAM 10003 and executes it to implement a processing object determination unit 111 and an externality information output unit 112.

[0019] However, instead of the combination of CPU 10001, ROM 10002, and RAM 10003, the sensor processing unit 11 can be implemented as a rewritable logic circuit or an ASIC (application-specific integrated circuit). Furthermore, instead of the combination of CPU 10001, ROM 10002, and RAM 10003, the sensor processing unit 11 can be implemented as a different combination, e.g., a combination of CPU 10001, ROM 10002, RAM 10003, and an FPGA.

[0020] The device processing unit 31 contains a CPU 30001 as a central processing unit, a ROM 30002 as a read-only memory, and a RAM 30003 as a read / write memory. The CPU 30002 extends the program stored in the ROM 30002 into the RAM 30003 and executes it to implement a condition calculation unit 311 and a vehicle control unit 312. However, the device processing unit 31 can be implemented by an FPGA or an ASIC instead of the combination of CPU 30001, ROM 30002, and RAM 30003. Furthermore, the device processing unit 31 can be implemented by a different combination of components instead of CPU 30001, ROM 30002, and RAM 30003. B. a combination of the CPU 30001, the ROM 30002, the RAM 30003 and an FPGA can be implemented. (Overview of the data)

[0021] The data stored in the sensor storage unit 12 and the device storage unit 32 are then displayed. The condition generation source 321 was previously stored in the device storage unit 32, and the condition generation source 321 is not modified to the extent described in this embodiment. In this embodiment, the navigation unit 2 has pre-generated the route 324 by a user action. The route 324 is information specifying the route along which the carrier vehicle is moving. The terrain 324 is information about nodes in an area containing the route 324. The processing condition 322 is generated by the condition calculation unit 311 with reference to the position of the carrier vehicle, the condition generation source 321, the terrain 323, and the route 324.Since the processing condition 322 is also influenced by the position of the carrier vehicle, the processing condition 322 is created at a high frequency, e.g. every 200 ms.

[0022] As mentioned above, processing condition 322 and processing condition 121 are identical. The preprocessing externality information 123 is information about the area around the carrier vehicle, collected by the externality detection sensor 1 and updated at a high frequency, e.g., every 200 ms. The externality information 122 is generated by the externality information output unit 112 based on processing condition 121 and the preprocessing externality information 123. The externality information 122 is sent to the electronic control unit 3 and stored as externality information 325 in the device storage unit 32. The electronic control unit 3 inputs the externality information 325 into the vehicle control unit 312.However, the electronic control device 3 does not have to use the externality information 325 and can send the externality information 325 to another device connected to the electronic control device 3. (Condition generation source)

[0023] Fig. Figure 3 is a diagram showing an example of the condition generation source 321. The condition generation source 321 has multiple records, and each record has fields for a condition 3211, a range derivation equation 3212, a priority 3212, and a processing granularity 3214. The condition to which what is written in the record is applied is stored in the field for the condition 3211. For example, "ON ROUTE & INTERSECTION", which is in Fig. 3 written into the first data set specifies a condition that the node is contained in route 324 and in terrain 323 and that the property of the node in terrain 323 is “INTERSECTION”.

[0024] The derivation equation for deriving the range to which the priority and processing granularity, written in the same dataset, are applied is stored in the range derivation equation field 3212. The functions f1 and f2, which are in Fig. Figure 3 shows range derivation equations that are defined separately and specify the use of longitude, latitude, and rotation angle. A concrete example of a range derivation equation is described later. "A derivation equation" is a concept and does not always have to be expressed by a numerical formula; the derivation process can be expressed, for example, using a flowchart.

[0025] The priority order in the process, enabling the externality detection sensor 1 to derive the landmark position, is stored in the priority field 3213. In this embodiment, a higher priority is assigned if the value in the priority field is lower. The interval between landmark positions within the landmark position output by the externality detection sensor 1 is stored in the processing granularity field 3214. For example, a processing granularity of "1 point / 1 m" means that a landmark position is output based on one point per 1 m, and "1 point / 4 m" means that a landmark position is output based on one point per 4 m. (Processing conditions)

[0026] Fig. Figure 4 is a diagram showing an example of processing condition 121 and processing condition 322. Although the composition of processing condition 322 is explained below, the composition of processing condition 121 is the same. Processing condition 322 has multiple records, and each record has fields for a priority 3221, a processing granularity 3222, an area 3223, and a node 3224. The fields for priority 3221 and processing granularity 3222 correspond to the fields for priority 3213 and processing granularity 3214 in condition generation source 321, which is described in Fig. Figure 3 shows that the field for area 3223 stores information about the object area to which the priority and processing granularity are applied in the dataset.

[0027] In the example that is in Fig. As shown in Figure 4, the object surface is a rectangle parallel to a set of axes in the coordinate system with reference to the carrier vehicle, and the minimum and maximum values ​​of the X-coordinate and the minimum and maximum values ​​of the Y-coordinate are stored in field 3223. However, the shape of the object surface is not limited to a rectangle; it can instead be a parallelogram, a trapezoid, a rhomboid, or an ellipse. Even if the object surface is a rectangle, information about the coordinates of the four vertices of the rectangle can be stored in the field for surface 3223. The identifier of the node closest to the surface specified in the field for surface 3223 is stored in the field for node 3224. However, processing condition 121 and processing condition 322 do not necessarily require the field for node 3224. (Example of the intersection)

[0028] Fig. 5 is a diagram showing an example of intersection C. Since terrain 323 and route 324 use the example of intersection C, which is in Fig. As shown in section 5, intersection C will be explained first. Intersection C, which is shown in Fig. Figure 5 shows an intersection where a south-northbound lane and an east-westbound lane intersect, with north being the upward direction in the figure. In the example shown in Fig. As shown in Figure 5, various nodes are placed on the roadways in each direction of travel. Specifically, nodes N11 to N18 are defined. For example, while nodes N11 and N18 are both ends of the roadway shown at the bottom of the figure, they are defined as distinct nodes because node N11 is on the side entering the intersection, and node N18 is on the side exiting the intersection. Here, the ends of the roadway refer to the ends closest to the intersection.

[0029] Interchange N11 covers lanes L111, L112, and L113. Interchange N12 covers lanes L121 and L122. The latitude of the end of lane L111 is "La1" and the longitude of the end of lane L111 is "Lo1". Since lanes L111, L112, and L113 are horizontally adjacent, the latitude of the ends of lanes L112 and L113 is also "La1". The longitude of the end of lane L112 is "Lo2" and the longitude of the end of lane L113 is "Lo3". The longitudes of lanes L121 and L122, which are covered by intersection N12, are both "Lo4". The latitude of lane L121 is “La2” and the latitude of lane L122 is “La3”. (site)

[0030] Fig. Figure 6 is a diagram showing an example of terrain 323. Terrain 323 consists of several data records, and each data record has fields for a node 3231, a property 3232, a lane 3233, a latitude 3234, a longitude 3235, and an azimuth 3236.

[0031] The symbol designating a representative point in the terrain is stored in the field for node 3231. Representative points are set for each roadway connected to the intersection, such that the route of the carrier vehicle can be determined by setting nodes in a sequential order. Additional nodes are set for each direction of vehicle movement. For example, intersection C, which is located in Fig. Figure 5 shows where four lanes intersect, forming eight junctions (4 x 2).

[0032] The field for property 3232 specifies the property of the last roadway leading to the node in the dataset. For example, if the roadway is straight just before the node in the dataset, "straight" is stored in property 3232, and if there is an intersection just before the node in the dataset, "intersection" is stored in the property. For example, at intersection C, which is in Fig. As shown in Figure 5, for node N11, which is in a position to enter intersection C from the bottom of the figure, the property 3232 is set to "straight ahead". For node 12, which is in a position to move left from intersection C in the figure, the property 3232 is set to "intersection".

[0033] The information for identifying the lanes covered by the junction is stored in the data set for lane 3233. For example, since junction N11 is located at intersection C, which is in Fig. Figure 5 shows three lanes, these lanes leading into area 323, which is in Fig. As shown in Figure 6, the latitudes of the lane ends in the dataset are stored in latitude 3234. The longitudes of the lane ends in the dataset are stored in longitude 3235. The direction of the lanes in the dataset is stored in azimuth 3236. The azimuth of a lane represents, for example, the angle of the line obtained by linearly approaching the lane relative to true north. (Route)

[0034] Fig. Figure 7 is a diagram showing an example of route 324. Route 324 indicates the order in which the vehicle passes the nodes on the route it is traveling along. Route 324 uses the identifier of node 3231 in terrain 323. In the example shown in Fig. Figure 7 shows that the nodes are listed from top to bottom in the order in which the vehicle travels. (Externality information)

[0035] Fig. Figure 8 is a diagram showing 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 consists of several data records, and each data record has fields for an X-coordinate 1221, a Y-coordinate 1222, and a probability 1223. The landmark position information, with reference to the carrier vehicle, is stored in the X-coordinate 1221 and the Y-coordinate 1222. Specifically, with the center of the carrier vehicle as the origin, the direction in front of the carrier vehicle, passing through the center of the carrier vehicle, is taken as the positive direction of the X-axis.

[0036] Furthermore, the Y-axis, which is perpendicular to the X-axis, is defined, and, for example, the left of the carrier vehicle is taken as the positive direction of the Y-axis. The index indicating the correctness of the reference point position in the dataset is stored in the probability field 1223. In the example shown in Fig. As shown in Figure 8, the greater the value stored in probability 1223, the higher the accuracy. For example, if the externality detection sensor 1 is a laser radar, the index stored in probability 1223 is determined based on the magnitude of the reflection intensity difference between the road surface around the reference point position and the reference point position. (Derivation equation for the domain)

[0037] Then the information contained in the domain derivation equation 3212 in Fig. 3 are stored, explained. With regard to the domain derivation equation, there are several variants besides f1 and f2, which are in Fig. Three are shown, each using terrain 323, route 324, and the position of the carrier vehicle. Then, two examples of range derivation equations are given with reference to Fig. 9 to Fig. 12 explained.

[0038] Fig. Figure 9 is a diagram showing an example of the range calculated by the range derivation equation f1, and Fig. Figure 10 is a diagram showing an example of the range calculated by the range derivation equation f2. Fig. Figure 11 is a flowchart showing the calculation process of the domain derivation equation f1, and Fig. Figure 12 is a flowchart showing the calculation process of the domain derivation equation f2. Fig. 9 and Fig. Figure 10 shows intersection C, which is shown above, and site 323 is the one that is in Fig. 6 is shown.

[0039] As in Fig. As shown in Figure 9, the area derivation equation f1 calculates an area A11 when the vehicle moves from node N11 to node N12, and an area A12 when the vehicle moves from node N11 to node N14. As shown in Fig. As shown in Figure 10, the area derivation equation f2 calculates an area A21 when the vehicle moves from node N11 to node N12, and an area A22 when the vehicle moves from node N11 to node N14. The area derivation equations f1 and f22 calculate different areas even if the condition is the same. For example, the calculation of an area is performed as follows.

[0040] The process of calculation using the domain derivation equation f1, as in Fig. Figure 11 is explained below. Here, the node to which the carrier vehicle will next move is referred to as the "object node." First, in step S411, the condition calculation unit 311 decides whether the route from the vehicle's current position to the object node is straight or not. If it decides the route is straight, it proceeds to step S412, and if it decides the route is not straight, it proceeds to step S413. In step S412, the condition calculation unit 311 calculates an object area as an area extending from the current lane in which the carrier vehicle is traveling to the object node, where the area has the same width as the lane, e.g., area A12 in Figure 11. Fig. 9 owns.

[0041] In step S413, the condition calculation unit 311 extracts a combination of lanes with the shortest distance. In the example shown in Fig. As shown in Figure 9, among combinations of two lanes, each combination that includes one of the three lanes L111, L112, and L113 covered by junction N11 and one of the two lanes L121 and L122 covered by junction N12 is used to extract the combination of lanes with the shortest distance. In this example, there are a total of six combinations, and among these, the combination of lane L113 and lane L121 with the shortest distance is extracted.

[0042] In the next step, S414, the condition calculation unit 311 defines an object area as a rectangular area in which the ends of the lanes of the combination extracted in step S413 are opposite corners. In the example shown in Fig. As shown in Figure 9, the rectangular area A11, in which the end E113 of lane L113 and the end E121 of lane L121 are opposite corners, is an object surface. When step S412 or step S414 is completed, the process described in Fig. 11 is shown, it is finished.

[0043] The process of calculation using the domain derivation equation f2, as in Fig. Figure 12 is explained below. However, explanations of the same steps as in the process of calculating the area derivation equation f1 are omitted. Since step S421 is the same as step S411, its explanation is omitted. The condition calculation unit 311 proceeds to step S422 if a positive decision is made in step S421, or to step S423 if a negative decision is made in step S421. In step S422, "the width of the lane in which the carrier vehicle travels" is replaced in step S412 by "the total width of the junction with which the carrier vehicle travels." Therefore, the area A22, which is in Fig. As shown in 10, an object surface is shown.

[0044] In step S423, unlike step S413, a combination of lanes is extracted where the distance is longest. In the example shown in Fig. As shown in Figure 10, lanes L111 and L122 are extracted. The next step, S424, is the same as step S414. However, since the combination of lanes extracted in the previous step is different, in the example shown in Figure 10, the ... Fig. Figure 10 shows the rectangular area A21, in which the end E111 of lane L111 and the end E122 of lane L122 are opposite corners, an object area. (Schedule)

[0045] Fig. Figure 13 is a flowchart showing the operation of the vehicle's in-vehicle system S1. The vehicle's in-vehicle system S1 executes the process that is described in Fig. Figure 13 shows the process in a given cycle, e.g., a cycle of 100 ms. In step S501, the condition calculation unit 311 acquires the terrain 323, the route 324, the latitude, longitude, and azimuth of the carrier vehicle from the navigation unit 2 and acquires the speed, yaw rate, and steering angle of the carrier vehicle from the carrier vehicle DB.

[0046] In step S502, the condition calculation unit 311 derives the latitude and longitude range of the processing object based on the latitude, longitude, and azimuth of the carrier vehicle, as received in step S501, and a preset detection range. The detection range is preset in the device memory unit 32, for example, as a rectangle extending 100 m backward, 300 m forward, 200 m to the left, and 200 m to the right from the carrier vehicle. In step S502, the latitudes and longitudes of the four points are calculated as the vertices of the rectangular area that will be the processing object.

[0047] In step S503, the condition calculation unit 311 detects the nodes contained in the latitude / longitude range as the processing object, as calculated in step S502, among the nodes contained in the terrain 323 received in step S501. For example, if the terrain 323 is expressed as in Fig. Figure 6 shows a node in which a representative point of a lane covered by each node, e.g. the latitude and longitude of the first listed lane, is contained in the latitude / longitude range derived in step S502 as the processing object, is detected.

[0048] In step S504, the condition calculation unit 311 calculates the processing condition 322 using the condition generation source 321. For example, if the condition generation source 321, the terrain 323, and the route 324 are expressed as in Fig. 3, Fig. 6 or Fig. As shown in Figure 7, the condition calculation unit 311 functions as follows. Specifically, the condition calculation unit 311 searches for a node that satisfies a condition among the conditions contained in the condition generation source 321, in the order listed above, calculates the area in accordance with the area 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 the processing granularity 3214, which are set in the same line in the processing condition 322, as priority 3221 and processing granularity 3222, respectively.

[0049] For example, if the conditional sentence in the first line of the conditional generation source in Fig. 3 “On the route & intersection” is a node with “intersection” as the property in terrain 323 in Fig. 6 of the junctions that are in Route 324 in Fig. The 7 contained in the range are searched for and "N12" is extracted. Then, in the same way, the range is derived in accordance with the range derivation equation "f1 (La, Lo, θ)" to derive the latitude range la1 to La2 and the longitude range Lo3 to Lo4. Then, in the same way, "1" is used as the priority and "1 point / 1 m" as the processing granularity, which is found in the first line of the condition generation source 321 in Fig. 3 are set, written into the processing condition 322. At this point, the processing granularity can be converted to be expressed by a relative magnification ratio (2) with respect to a given processing granularity (1 / 2 m). By performing the same process for each of the second and subsequent lines of the condition generation source 321 in Fig. 3. The priority 3221 and the processing granularity 3222 can be set for all lines of the condition generation source 321 in Fig. 3 are determined as in Fig. 4 is shown.

[0050] In step S505, the condition calculation unit 311 estimates the carrier vehicle's position and azimuth in the next cycle based on the information received from the carrier vehicle DB 6 in step S501, and shifts and rotates the area calculated in step S504 to correct it. For example, if it receives the carrier vehicle's latitude / longitude, azimuth, speed, and yaw rate, and the corresponding time from the carrier vehicle DB 6, it calculates the amount of change in the carrier vehicle's position and azimuth during the next cycle, assuming the carrier vehicle maintains the same speed and yaw rate until the time of the next cycle. It then determines the following rectangle as an area corrected by shifting / rotating: a rectangle containing the area corrected by repositioning the area calculated in step S504, for example.The latitude range La1 to La2 and the longitude range Lo3 to Lo4 are converted into a carrier vehicle-centered coordinate system with the position and azimuth of the carrier vehicle in the next cycle, e.g. the coordinate range XI1 to Xu1 in the direction of travel and the coordinate range Y11 to Yu1 in the left / right direction.

[0051] In step S506, the condition calculation unit 311 creates the processing condition 322 by combining the priority 3221 and the processing granularity 3222 calculated in step S504, and the area corrected by a shift / rotation in step S505, and sends it to the processing object determination unit 111.

[0052] In step S507, the processing object determination unit 111 of the externality detection sensor 1 derives the externality information 122 according to the processing condition 322 sent in step S506. For example, if the processing condition is expressed as in Fig. Figure 4 shows the first row, in which the highest priority "1" is set. As a result of the search, if multiple rows with the same priority are found, processing is carried out according to the rule preset in the sensor memory unit 12, e.g., a rule that processing should be performed in ascending order starting with the lowest row number. Then, according to the range and processing granularity set in the row extracted as a result of the search, the externality information 122 (X, Y) detected in the range is identified by the set processing granularity. At this point, if the externality detection sensor 1 has the function to set the probability for each landmark position, the probability for each landmark position can be set as shown in Fig. 8 is shown.

[0053] The function to set a probability is, for example, the function to set a probability according to the reference point edge position error, which depends on the degree of reference point blurring or the ambient illuminance. The processing described above can also be performed according to the rule preset in the sensor memory unit 12. The rule is, for example, that the processing should be repeated until the number of reference point positions reaches the upper limit of 64, or that if the upper limit is exceeded during processing for a particular area, processing should be performed sequentially starting from the reference point position closest to the carrier vehicle until the upper limit is reached.

[0054] In step S508, the externality information output unit 112 sends the externality information 122, derived in step S507, to the vehicle control unit 312. The received orientation point position information is stored as externality information 325, for example, in the device storage unit 32. The externality information 325 can be discarded by the vehicle control unit 312 after vehicle control processing.

[0055] According to the first embodiment described above, the following effects are produced.

[0056] (1) The vehicle-integrated system S1 is mounted in a vehicle and is equipped with an electronic control device 3 and an externality detection sensor 1. The externality detection sensor 1 includes a sensing unit 13 for acquiring preprocessing externality information 123 by means of a sensing operation.The vehicle's internal system S1 contains the following: a condition calculation unit 311, which calculates a processing condition 322 based on the vehicle's position, direction of movement, and map information, whereby information identifying an area on the map is assigned to the processing priority of the preprocessing externality information 123, which is acquired by the externality detection sensor; and a processing object determination unit 111, which creates externality information 122 based on the preprocessing externality information 123 and the processing condition 121. This externality information contains a smaller amount of information than the preprocessing externality information 123. Therefore, even in an environment with a large amount of externality information, such as...at an intersection information about feature points of an area with high priority, namely externality information 122, the amount of information of which is smaller than that of the preprocessing externality information 123, is created and thus the electronic control device 3 can perform the required processing even if it does not have high computing capacity.

[0057] (2) The processing condition 121 is the priority 3221 and the processing granularity 3222 as the spatial density of the output assigned to the area 3223 on the map. Therefore, information is obtained not only according to an area selection by priority, but also according to a processing granularity set for each area.

[0058] (3) The externality information 122 is information regarding landmarks, and the processing of preprocessing externality information 123 is the process of deriving the feature points of a landmark. Therefore, landmark information that depends on the processing condition 322 can be obtained as externality information 122.

[0059] (4) A reference point is a lane marking present on a roadway, and the processing granularity 3222 is a point density in the derivation of feature points of the lane marking. Therefore, if the processing granularity 3222 is higher, a greater number of feature points can be derived from a detected lane marking per unit length.

[0060] (5) The condition calculation unit 311 identifies the vehicle's direction of movement based on the vehicle's position and the route 324, which is a previously calculated route for the vehicle. Therefore, it is possible to capture appropriate high-density area information according to the vehicle's route. Additionally, if an area in which the vehicle will not move is known in advance, e.g., if the vehicle will turn left at the intersection, the externality information 122 may not contain information about the area on the right-turn side and the area for the vehicle to proceed straight ahead.

[0061] (6) The electronic control device 3 includes a condition calculation unit 311 and a condition transmission unit 33 for sending the processing condition 322 to the externality detection sensor 1. The externality detection sensor 1 includes a detection unit 13 and a processing object determination unit 111.

[0062] (7) The externality detection sensor 1 is mounted in a vehicle and is equipped with: a detection unit 13, which acquires preprocessing externality information through a detection operation; a condition receiving unit 14, which acquires the processing condition 121, which is created on the basis of the vehicle position, the vehicle direction of movement and the map information, and wherein information identifying an area in the map is assigned to the processing priority of the preprocessing externality information acquired by the externality detection sensor; and a processing object determination unit 111, which creates externality information 122, which has a smaller amount of information than the preprocessing externality information 123, on the basis of the preprocessing externality information 123 and the processing condition 121.Therefore, even in an environment with a lot of externality information, such as an intersection, the externality detection sensor 1 generates information about feature points of an area with high priority, namely externality information 122, the amount of which is smaller than that of the preprocessing externality information 123, based on the calculated processing condition 322. Consequently, the electronic control device 3 can handle an intersection with a lot of information, even if it does not have high computing power. (Variant 1)

[0063] The device storage unit 32 of the electronic control device 3 can store multiple condition generation sources 321 such that the condition calculation unit 311, based on information indicating the country / territory in which the carrier vehicle is traveling and acquired by the navigation unit 2, decides which condition generation source 321 to use. For example, the condition calculation unit 311 can calculate the processing condition 322 using the condition generation source 321, which differs depending on whether the country or territory has a traffic rule requiring vehicles to drive on the right-hand side of the road or a traffic rule requiring vehicles to drive on the left-hand side of the road. (Variant 2)

[0064] In the first embodiment described above, the externality detection sensor 1 outputs information about the feature points of an orientation point, which is a stationary object, as externality information 122. However, the externality detection sensor 1 can instead detect a moving object, such as another vehicle, a pedestrian, or a bicycle, and output the information. (Variant 3)

[0065] In the first embodiment described above, the processing condition 322 includes a processing granularity 3222. However, the processing condition 322 need not contain a processing granularity 3222. Even if it does, the externality information 122 does not contain the orientation point information about all surfaces around the carrier vehicle, but only the orientation point information within the object surface, which is why the same effects can be produced as in the first embodiment. Second embodiment

[0066] Then the vehicle's internal system is configured according to the second embodiment with reference to Fig. 14. In the explanation below, the same elements as in the first embodiment are designated by the same reference numerals, and mainly different points are described. Points not described below are the same as in the first embodiment. This embodiment differs from the first embodiment mainly in that the processing condition 322 is modified in the past according to the externality information 325. This makes it possible to collect more information important for controlling the vehicle without increasing the overall processing volume, thus ensuring greater safety with the same processing volume.

[0067] The hardware and functional configuration of the in-vehicle system are the same as in the first embodiment. In the second embodiment, processing by the in-vehicle system is enhanced as follows. Specifically, step S511, which is explained below, is added between step S504 and step S505.

[0068] Fig. Figure 14 is a flowchart showing processing in the vehicle's internal system according to the second embodiment. Explanations of the same steps as in the first embodiment are omitted. In step S511, which is to be executed alongside step S504, the condition calculation unit 311 rewrites the priority and / or processing granularity calculated in step S504, according to probability, in the externality information 325 received from the externality information output unit 112.

[0069] For example, the condition calculation unit 311 can reduce the processing granularity for an area where information has already been captured with a high probability, either to decrease the number of output points for the area or to lower its priority, thus making the output more difficult. Specifically, for example, pieces of externality information 325 that were captured recently are rearranged in ascending order of X-coordinate values, and an area with a higher probability than a predefined threshold, e.g., 80, and which is continuous, is identified, and the priority of the area is changed to "3", and the processing granularity is changed to "1 point / 5 m".

[0070] According to the second embodiment described above, the following effects are produced.

[0071] (8) The externality information 122 contains a probability 1223, which indicates the degree of correctness. The condition calculation unit 311 corrects the processing condition according to the probability 1223. Therefore, the condition calculation unit 311 can correct the processing condition 322 according to the information about the environment that was collected in the past.

[0072] (9) If the probability for an area in the captured externality information 325 is a predefined value or higher, the condition calculation unit 311 lowers the priority for the area in the processing condition 322. Therefore, more information important for controlling the vehicle can be collected without increasing the overall processing volume, thus ensuring greater safety with the same processing volume. Third embodiment

[0073] Then the vehicle's internal system is configured according to the third embodiment with reference to Fig. 15. In the explanation below, the same elements as in the first embodiment are designated by the same reference numerals, and mainly different points are described. Points not described below are the same as in the first embodiment. This embodiment differs from the first embodiment mainly in that the processing condition 322 is adapted according to a vehicle steering action. This makes it possible to collect more information important for controlling the vehicle without increasing the overall processing volume, even if the user moves the vehicle in a direction different from the predetermined route. Therefore, a higher level of safety is expected to be ensured with the same processing volume.

[0074] Fig. Figure 15 is a flowchart showing processing in the vehicle's in-vehicle system according to the third embodiment. The steps up to step S503 are the same as in the first embodiment, and their explanations have been omitted. In addition to step S503, the condition calculation unit 311 decides whether the steering angle is consistent with the route. For example, if the steering angle is consistent with the route, it then decides whether, at the time a left turn is to be made, the steering angle is consistent with the angle required to turn left. If the condition calculation unit 311 decides that the steering angle is consistent with the route, it proceeds to step S504, and if it decides that the steering angle is not consistent with the route, it proceeds to step S522.

[0075] In step S504, as in the first embodiment, it calculates the area, priority, and processing granularity using the route information and proceeds to step S505. In step S522, the condition calculation unit 311 estimates a node ahead of the carrier vehicle. In the next step, S523, the condition calculation unit 311 calculates the area, priority, and processing granularity using the node estimated in step S522 and proceeds to step S505. Step S505 and subsequent steps are the same as in the first embodiment, and their explanations are omitted.

[0076] According to the third embodiment, the following effect is produced.

[0077] (10) The condition calculation unit 311 identifies the direction of travel of the vehicle based on the position of the vehicle, the previously calculated route of the vehicle, or the steering angle of the vehicle. Therefore, it can handle a case where the vehicle leaves route 324. Fourth embodiment

[0078] Then the vehicle's internal system is configured according to the fourth embodiment with reference to Fig. 16. In the explanation below, the same elements as in the first embodiment are designated by the same reference numerals, and mainly different points are described. Points not described below are the same as in the first embodiment. This embodiment differs from the first embodiment mainly in that the electronic control device includes a processing object determination unit.

[0079] Fig.Figure 16 is a general configuration diagram of the vehicle-internal system S4 according to the fourth embodiment. All elements of the vehicle-internal system S4 are contained within the vehicle-internal system S1 according to the first embodiment. However, the locations of specific functions differ. Specifically, while the processing object determination unit 111 is located in the externality detection sensor 1 in the first embodiment, 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 manner as the processing object determination unit 111 in the first embodiment.

[0080] In this embodiment, the electronic control device 3 does not need to send the calculated processing condition 322 to the externality detection sensor 1, and therefore does not need to include the condition transmission unit 33. The externality detection sensor 1 does not include the processing object determination unit 111, the externality information output unit 112, or the condition receiving unit 14. However, the externality detection sensor 1 does include a preprocessing externality information output unit 113, which sends the detected preprocessing externality information 123 to the electronic control device 3.

[0081] According to the fourth embodiment described above, the following effects are produced.

[0082] (11) The electronic control device 3 includes a condition calculation unit 311 and a processing object determination unit 313. The externality detection sensor 1 includes a preprocessing externality information output unit 113, which sends the preprocessing externality information 123 to the electronic control device 3. Therefore, the vehicle control unit 312 of the electronic control device 3 only takes the externality information 325, calculated by the processing object determination unit 313 using the processing condition 322, as the processing object, such that it can handle a crossover with many pieces of information.

[0083] (12) The electronic control device 3 is mounted in a vehicle and is connected to the externality detection sensor 1, which acquires the preprocessing externality information 123 through a sensing operation.The electronic control device 3 comprises the following: a condition calculation unit 311, which calculates a processing condition 322 based on the vehicle position, the vehicle direction of movement, and the map information, wherein information identifying an area in the map is assigned to the processing priority of the preprocessing externality information 123, which is acquired by the externality detection sensor 1; a preprocessing externality information acquisition unit 34, which acquires the preprocessing externality information 123 from the externality detection sensor 1; and a processing object determination unit 313, which, based on the preprocessing externality information 123 and the processing condition 322, creates externality information 325, which has a smaller amount of information than the preprocessing externality information 123.

[0084] In the embodiments and variants described above, the functional block configurations are merely examples. Some of the functional blocks shown separately in the figures can be integrated, or a functional block shown in the figures can be subdivided into two or more functional blocks. Furthermore, some of the functions in one functional block can be transferred to another functional block.

[0085] The embodiments and variants described above can be combined. Various embodiments and variants are described above, but the present invention is not limited to them. Further embodiments that fall within the scope of the technical concept of the present invention are also included within the scope of the present invention.

[0086] The full disclosure of the following application, which serves as the priority basis, is included here: Japanese patent application 2019-90541 (filed on May 13, 2019). Reference symbol list 1 externality detection sensor, 3 Electronic control device, 13 recording units, 14 Condition receiving unit, 33 Condition transmission unit, 34 Preprocessing externality information capture unit, 111 Processing object-determination unit, 112 Externality Information Output Unit, 113 Preprocessing Externality Information Output Unit, 121, 322 Processing conditions, 122, 325 Externality Information, 123 Preprocessing externality information, 311 Condition calculation unit, 313 Processing object-determination unit, 321 Condition generation source, 323 site, Route 324

Claims

[1] In-vehicle system designed to be installed in a vehicle and equipped with an electronic control device (3) and an externality detection sensor (1), wherein the externality detection sensor (1) includes a detection unit for acquiring preprocessing externality information (123) by a detection operation and The system includes the following: a condition calculation unit (311) that calculates a processing condition (121, 322) based on the vehicle's position, the vehicle's direction of travel, and map information, wherein information identifying an area on the map is assigned a processing priority of the preprocessing externality information (123) acquired by the externality detection sensor (1); and a processing object determination unit (111) that, based on the preprocessing externality information (123) and the processing condition (121, 322), creates externality information (122, 325) that contains a smaller amount of information than the preprocessing externality information (123), wherein the externality information (122, 325) contains a probability that indicates a degree of correctness, and the condition calculation unit (311) corrects the processing condition (121, 322) according to the probability, and wherein then, if the probability of a first area in the captured externality information (122, 325) is a predefined value or more, the condition calculation unit (311) lowers the priority of the first area in the processing condition (121, 322). [2] In-vehicle system according to claim 1, wherein the processing condition (121, 322) assigns the priority and the processing granularity as a spatial density of an output of the area in the map. [3] Vehicle-internal system according to claim 2, wherein the externality information (122, 325) is information regarding a point of reference and The processing of the preprocessing externality information (123) is a process for deriving feature points of the reference point. [4] In-vehicle system according to claim 3, wherein the orientation point is a lane marking present on a roadway and the processing granularity is a point density in the derivation of the feature points of the lane marking. [5] In-vehicle system according to claim 1, wherein the condition calculation unit (311) identifies the direction of travel of the vehicle based on the position of the vehicle and the previously calculated route of the vehicle or a steering angle of the vehicle. [6] In-vehicle system according to claim 1, wherein the electronic control device (3) comprises: the condition calculation unit (311) and a condition transmission unit that sends the processing condition (121, 322) to the externality detection sensor (1), wherein the externality detection sensor (1) comprises the detection unit and the processing object determination unit (111). [7] Vehicle-internal system according to claim 1, wherein the electronic control device (3) comprises the condition calculation unit (311) and the processing object determination unit (111) and The externality detection sensor (1) comprises a preprocessing externality information output unit (113) which sends the preprocessing externality information (123) to the electronic control device (3). [8] Externality detection sensor (1) designed to be mounted in a vehicle and comprising the following: a capture unit (13) that captures preprocessing externality information (123) through a capture operation; a receiving unit (14) that acquires a processing condition (121, 322) created on the basis of the vehicle's position, the vehicle's direction of travel, and map information, wherein information identifying an area in the map is assigned a processing priority of the preprocessing externality information (123) acquired by the externality detection sensor (1); and a processing object determination unit (111) that, based on the preprocessing externality information (123) and the processing condition (121, 322), creates externality information (122, 325) that has a smaller amount of information than the preprocessing externality information (123), where the externality information (122, 325) contains a probability that indicates a degree of correctness, and the condition calculation unit (311) corrects the processing condition (121, 322) according to the probability, and wherein then, if the probability of a first area in the captured externality information (122, 325) is a predefined value or more, the condition calculation unit (311) lowers the priority of the first area in the processing condition (121, 322). [9] Electronic control device (3) designed to be mounted in a vehicle and connected to an externality detection sensor (1) which acquires preprocessing externality information (123) by means of a sensing operation, wherein the electronic control device (3) comprises: a condition calculation unit (311) which calculates a processing condition (121, 322) based on a position of the vehicle, a direction of travel of the vehicle and map information, wherein information identifying an area in the map is assigned to a processing priority of the preprocessing externality information (123) acquired by the externality detection sensor (1); a preprocessing externality information acquisition unit (34) that acquires the preprocessing externality information (123) from the externality detection sensor (1); and a processing object determination unit (111) that, based on the preprocessing externality information (123) and the processing condition (121, 322), creates externality information (122, 325) that has a smaller amount of information than the preprocessing externality information (123), wherein the externality information (122, 325) contains a probability that indicates a degree of correctness, and the condition calculation unit (311) corrects the processing condition (121, 322) according to the probability, and wherein then, if the probability of a first area in the captured externality information (122, 325) is a predefined value or more, the condition calculation unit (311) lowers the priority of the first area in the processing condition (121, 322).

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