This on-vehicle system is to be mounted in a vehicle and is provided with an electronic control device and an externality recognition sensor. The externality recognition sensor is equipped with a sensing unit for acquiring pre-processing externality information through sensing operations. The on-vehicle system is further equipped with: a condition calculation unit that, on the basis of a vehicle position, a vehicle traveling direction, and map information, calculates a processing condition in which information specifying an area on a 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 compared with the pre-processing externality information.

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

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.

DESCRIPTION OF EMBODIMENTS

First Embodiment

FIG.1is a general configuration diagram of an on-vehicle system S1according to the present invention. The on-vehicle system S1is mounted in a vehicle and provided with an externality recognition sensor1, a navigation unit2, an electronic control device3, an actuator4, an input device5, and an own vehicle DB6. These are connected by signal lines as shown inFIG.1. Hereinafter, the vehicle in which the on-vehicle system S1is mounted is called as the “own vehicle” in order to distinguish it from other vehicles.

The externality recognition sensor1detects the position of a landmark present around the own vehicle or the like as externality information. The externality recognition sensor1is, for example, a camera or laser radar or the like. AlthoughFIG.1shows that the on-vehicle system S1includes only one externality recognition sensor1, the on-vehicle system S1may include a plurality of externality recognition sensors1. The navigation unit2outputs information such as route, terrain, and the latitude and longitude of the own vehicle. The electronic control device3derives the position of the landmark and determines the method for controlling the own vehicle.

The actuator4is a steering wheel, brake, and accelerator which change the orientation and speed of the vehicle. AlthoughFIG.1shows that the on-vehicle system S1includes only one actuator4, the on-vehicle system S1may include a plurality of actuators4. The input device5reads, writes, and rewrites information which is stored in a sensor storage unit12of the externality recognition sensor1and information which is stored in a device storage unit32of the electronic control device3. The input device is, for example, a personal computer. The on-vehicle system S1may include a plurality of input devices5. The own vehicle DB6is 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 DB6successively 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 sensor1includes a sensor processing unit11, a sensor storage unit12, a sensing unit13, and a condition reception unit14. The hardware configuration of the sensor processing unit11will be described later. The sensor storage unit12is a nonvolatile memory area and for example, a flash memory or EEPROM (Electrically Erasable Programmable Read-Only Memory). The sensor processing unit11includes a processing object determination unit111and an externality information output unit112. The sensor storage unit12stores a processing condition121, externality information122, and pre-processing externality information123.

The sensing unit13is a combination of sensor components, for example, a light source and a light receiving element. The sensing unit13performs sensing in a given processing cycle and stores the pre-processing externality information123in the sensor storage unit12. The condition reception unit14receives a processing condition322from the electronic control device3and stores it as the processing condition121in the sensor storage unit12. The condition reception unit14is, for example, a communication module which conforms to CAN (registered trademark) or IEEE802.3.

The electronic control device3includes a device processing unit31, a device storage unit32, and a condition transmission unit33. The hardware configuration of the device processing unit31will be described later. The device storage unit32is a nonvolatile memory area and for example, a flash memory or EEPROM. The device processing unit31includes a condition calculation unit311and a vehicle control unit312. The device processing unit31stores the information received from the externality recognition sensor1, navigation unit2and own vehicle DB6in the device storage unit32. The device storage unit32stores a condition creation source321, processing condition322, terrain323, route324, and externality information325. The condition transmission unit33is, for example, a communication module which conforms to CAN or IEEE802.3.

As will be described in detail, the processing condition121stored in the sensor storage unit12and the processing condition322stored in the device storage unit32are the same. Also, the externality information122stored in the sensor storage unit12and the externality information325stored in the device storage unit32are the same. Specifically, the processing condition322is created by the condition calculation unit311and the processing condition322is transmitted from the electronic control device3to the externality recognition sensor1by the condition transmission unit33and stored in the sensor storage unit12as the processing condition121. Also, the externality information122is created by the externality information output unit112and the externality information122is transmitted from the externality recognition sensor1to the electronic control device3and stored in the device storage unit32as the external information325. This embodiment assumes that the processing condition121and processing condition322are the same in all aspects including the data storage method and the externality information122and externality information325are 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 inFIG.1merely 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 unit11and sensor storage unit12are mounted in a device in which the electronic control device3is mounted.

FIG.2is a diagram which shows the hardware configurations of the sensor processing unit11and device processing unit31. The sensor processing unit11includes a CPU10001as a central processing unit, a ROM10002as a read-only memory, and a RAM10003as a readable and writable memory. The CPU10002expands the program stored in the ROM10002into the RAM10003and executes it to realize a processing object determination unit111and an externality information output unit112.

However, instead of the combination of the CPU10001, ROM10002, and RAM10003, the sensor processing unit11may 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 CPU10001, ROM10002, and RAM10003, the sensor processing unit11may be realized by a different combination, for example, a combination of the CPU10001, ROM10002, RAM10003, and an FPGA.

The device processing unit31includes a CPU30001as a central processing unit, a ROM30002as a read-only memory, and a RAM30003as a readable and writable memory. The CPU30002expands the program stored in the ROM30002into the RAM30003and executes it to realize a condition calculation unit311and a vehicle control unit312. However, instead of the combination of the CPU30001, ROM30002, and RAM30003, the device processing unit31may be realized by an FPGA or ASIC. Also, instead of the combination of the CPU30001, ROM30002, and RAM30003, the device processing unit31may be realized by a different combination, for example, a combination of the CPU30001, ROM30002, RAM30003, and an FPGA.

Next, the data which is stored in the sensor storage unit12and device storage unit32will be outlined. The condition creation source321has previously been stored in the device storage unit32and the condition creation source321is not changed in the scope in which this embodiment is described. In this embodiment, the navigation unit2has created the route324in advance through user operation. The route324is information which indicates the travel route along which the own vehicle travels. The terrain324is information on nodes in an area including the route324. The processing condition322is created by the condition calculation unit311in reference to the position of the own vehicle, the condition creation source321, terrain323, and route324. Since the processing condition322is also influenced by the position of the own vehicle, the processing condition322is created with high frequency, for example, every 200 ms.

As mentioned above, the processing condition322and processing condition121are the same. The pre-processing externality information123is information on the area around the own vehicle which is collected by the externality recognition sensor1, and updated with high frequency, for example, every 200 ms. The externality information122is created by the externality information output unit112on the basis of the processing condition121and pre-processing externality information123. The externality information output unit112is transmitted to the electronic control device3and stored as the externality information325in the device storage unit32. The electronic control device3enters the externality information325into the vehicle control unit312. However, instead, the electronic control device3may not use the externality information325and may send the externality information325to another device connected to the electronic control device3.

FIG.3is a diagram which shows an example of the condition creation source321. The condition creation source321has a plurality of records and each record has fields for condition3211, range derivation equation3212, priority3212, and processing granularity3214. The condition to which what is written in the record is applied is stored in the field for condition3211. For example, “IN ROUTE & INTERSECTION” written in the first record inFIG.3indicates a condition that the node is included in the route324and terrain323and the attribute of the node in the terrain323is “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 equation3212. The functions f1and f2shown inFIG.3are 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 sensor1to derive the landmark position is stored in the field for priority3213. 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 sensor1is stored in the field for processing granularity3214. 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.

FIG.4is a diagram which shows an example of the processing condition121and processing condition322. Although the composition of the processing condition322is explained below, the composition of the processing condition121is the same. The processing condition322has a plurality of records and each record has fields for priority3221, processing granularity3222, area3223, and node3224. The fields for priority3221and processing granularity3222correspond to the fields for priority3213and processing granularity3214in the condition creation source321shown inFIG.3. The field for area3223stores information on the object area to which the priority and processing granularity in the record are applied.

In the example shown inFIG.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 area3223. 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 area3223. The identifier of the node nearest to the area indicated in the field for area3223is stored in the field for node3224. However, the processing condition121and processing condition322may not have the field for node3224.

FIG.5is a diagram which shows an example of intersection C. Since terrain323and route324are explained using the example of intersection C shown inFIG.5, intersection C is first explained. The intersection C shown inFIG.5is 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 inFIG.5, different nodes are set in each traveling direction on the roads. Specifically, node N11to node N18are set. For example, while node N11and node N18are both ends of the road shown on the lower side of the figure, they are set as different nodes because node N11is a node on the side for entering the intersection and node N18is a node on the side for leaving the intersection. Here, the ends of the road mean the ends nearest to the intersection.

Node N11covers lane L111, lane L112, and lane L113. Node N12covers lane L121and lane L122. The latitude of the end of lane L111is “La1” and the longitude of the end of lane L111is “Lo1”. Since lane L111, lane L112, and lane L113are arranged side by side horizontally, the latitude of the ends of lane L112and lane L113is also “La1”. The longitude of the end of lane L112is “Lo2” and the longitude of the end of lane L113is “Lo3”. The longitudes of lane L121and lane L122covered by node N12are both “Lo4”. The latitude of lane L121is “La2” and the latitude of lane L122is “La3”.

FIG.6is a diagram which shows an example of terrain323. Terrain323is comprised of a plurality of records and each record has fields for node3231, attribute3232, lane3233, latitude3234, longitude3235, and azimuth3236.

The sign which denotes a representative point on the terrain is stored in the field for node3231. 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 inFIG.5where four roads intersect has eight nodes (4×2).

The field for attribute3232indicates 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 attribute3232and 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 inFIG.5, for node N11, which is located in a position to enter the intersection C from the lower side in the figure, “linear” is stored in the attribute3232. For node12, which is located in a position to move leftward from the intersection C in the figure, “intersection” is stored in the attribute3232.

The information to identify the lanes covered by the node in the record is stored in the lane3233. For example, since node N11in the intersection C shown inFIG.5covers three lanes, these lanes are written in the terrain323shown inFIG.6. The latitudes of the ends of the lanes in the record are stored in the latitude3234. The longitudes of the ends of the lanes in the record are stored in the longitude3235. The direction of the lanes in the record is stored in the azimuth3236. 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.

FIG.7is a diagram which shows an example of route324. Route324indicates the order in which the vehicle passes the nodes on the route along which the vehicle runs. For route324, the identifier of the node3231in the terrain323is used. In the example shown inFIG.7, the nodes are listed in the order in which the vehicle runs, from top to bottom.

FIG.8is a diagram which shows an example of externality information122and externality information325. Although the composition of externality information122is explained below, the composition of externality information325is the same. Externality information122is comprised of a plurality of records and each record has fields for X coordinate1221, Y coordinate1222, and probability1223. The landmark position information with reference to the own vehicle is stored in the X coordinate1221and Y coordinate1222. 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 probability1223. In the example shown inFIG.8, when the value stored in the probability1223is larger, correctness is higher. For example, when the externality recognition sensor1is a laser radar, the index stored in the probability1223is determined on the basis of the magnitude of reflection intensity difference between the road surface around the landmark position and the landmark position.

Next, the information which is stored in the range derivation equation3212inFIG.3will be explained. As for the range derivation equation, there are a plurality of variations other than f1and f2shown inFIG.3and each of them uses the terrain323, route324, and the position of the own vehicle. Next, two examples of range derivation equation will be explained referring toFIG.9toFIG.12.

FIG.9is a diagram which shows an example of the range calculated by range derivation equation f1andFIG.10is a diagram which shows an example of the range calculated by range derivation equation f2.FIG.11is a flowchart which shows the calculation process of range derivation equation f1andFIG.12is a flowchart which shows the calculation process of range derivation equation f2.FIG.9andFIG.10show the intersection C shown above, and the terrain323is the one shown inFIG.6.

As shown inFIG.9, with the range derivation equation f1, when the vehicle travels from node N11to node N12, an area A11is calculated and when the vehicle travels from node N11to node N14, an area A12is calculated. As shown inFIG.10, with the range derivation equation f2, when the vehicle travels from node N11to node N12, an area A21is calculated and when the vehicle travels from node N11to node N14, an area A22is calculated. The range derivation equation f1and range derivation equation f22calculate 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 f1as shown inFIG.11is explained below. Here, the node to which the own vehicle moves next is called “object node”. First, at Step S411the condition calculation unit311decides 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 S412and if it decides that the route is not straight, it goes to Step S413. At Step S412, the condition calculation unit311calculates 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 A12inFIG.9.

At Step S413, the condition calculation unit311extracts a combination of lanes with the shortest distance. In the example shown inFIG.9, among combinations of two lanes, each combination having one of the three lanes L111, L112, and L113covered by node N11and one of the two lanes L121and L122covered by node N12, 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 L113and lane L121in which the distance is the shortest is extracted.

At the next step S414, the condition calculation unit311determines, as an object area, a rectangular area in which the ends of the lanes of the combination extracted at Step S413are opposite corners. In the example shown inFIG.9, the rectangular area A11in which end E113of lane L113and end E121of lane L121are opposite corners is an object area. When Step S412or Step S414is completed, the process shown inFIG.11is ended.

The process of calculation by the range derivation equation f2as shown inFIG.12is explained below. However, explanations of the same steps as in the process of calculation by the range derivation equation f1are omitted. Since Step S421is the same as Step S411, its explanation is omitted. If a positive decision is made at Step S421, the condition calculation unit311goes to Step S422or if a negative decision is made at Step S421, it goes to Step S423. At Step S422, “the width of the lane on which the own vehicle is running” at Step S412is replaced by “the overall width of the node with which the own vehicle is running”. Therefore, the area A22shown inFIG.10is an object area.

At Step S423, conversely to Step S413, a combination of lanes in which the distance is the longest is extracted. In the example shown inFIG.10, lane L111and lane L122are extracted. The next step S424is the same as Step S414. However, since the combination of lanes extracted at the preceding step is different, in the example shown inFIG.10, the rectangular area A21in which end Ell′ of lane L111and end E122of lane L122are opposite corners is an object area.

FIG.13is a flowchart which shows operation of the on-vehicle system S1. The on-vehicle system S1performs the process shown inFIG.13in a given cycle, for example, 100 ms cycle. At Step S101, the condition calculation unit311acquires the terrain323, route324, the latitude, longitude, and azimuth of the own vehicle from the navigation unit2and acquires the speed, yaw rate, and steering angle of the own vehicle from the own vehicle DB.

At Step S102, the condition calculation unit311derives 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 S101and a preset sensing range. The sensing range is preset in the device storage unit32, 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 S102, 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 S103, the condition calculation unit311detects the nodes included in the latitude/longitude range as the processing object as calculated at Step S102, among the nodes included in the terrain323received at Step S101. For example, if the terrain323is expressed as shown inFIG.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 S102as the processing object is detected.

At Step S104, the condition calculation unit311calculates the processing condition322using the condition creation source321. For example, if the condition creation source321, terrain323, and route324are expressed as shown inFIG.3,FIG.6, andFIG.7respectively, the condition calculation unit311operates as follows. Namely, the condition calculation unit311search for a node which meets a condition among the conditions included in the condition creation source321in the order from top, calculates the range in accordance with the range derivation equation set in the same line, and records it as an area3223in the processing condition322. Furthermore, it records the priority3213and processing granularity3214set in the same line in the processing condition322, as priority3221and processing granularity3222.

For example, if the condition set in the first line of the condition creation source inFIG.3is “in route & intersection”, a node with “intersection” as the attribute in the terrain323inFIG.6is searched from among the nodes included in the route324inFIG.7and “N12” is extracted. Then, in the same manner, the range is derived in accordance with the range derivation equation “f1(La, Lo, θ) to derive the latitude range la1to La2and longitude range Lo3to Lo4. 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 source321inFIG.3are written in the processing condition322. 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 source321inFIG.3, priority3221and processing granularity3222can be determined as shown inFIG.4for all the lines of the condition creation source321inFIG.3.

At Step S105, the condition calculation unit311estimates the position and azimuth of the own vehicle in the next cycle on the basis of the information received from the own vehicle DB6at Step S101and shifts and rotates the range calculated at Step S104for 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 DB6, 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 S104, for example, the latitude range La1to La2and longitude range Lo3to Lo4, into an own vehicle-centered coordinate system with the own vehicle position and azimuth in the next cycle, for example, the coordinate range X11to Xul in the traveling direction and the coordinate range Yll to Yul in the left-right direction.

At Step S106, the condition calculation unit311creates the processing condition322by combining the priority3221and processing granularity3222calculated at Step S104and the range corrected by shift/rotation at Step S105, and sends it to the processing object determination unit111.

At Step S107, the processing object determination unit111of the externality recognition sensor1derives the externality information122according to the processing condition322sent at Step S106. For example, if the processing condition is expressed as shown inFIG.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 unit12, 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 information122(X, Y) detected in the range is identified by the specified processing granularity. At this time, if the externality recognition sensor1has the function to set probability for each landmark position, probability may be set for each landmark position as shown inFIG.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 unit12. The rule is, for example, that processing should be repeated until the number of landmark positions reaches the upper limit number64or 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 S108, the externality information output unit112sends the externality information122derived at Step S107to the vehicle control unit312. The received landmark position information is stored as externality information325, for example, in the device storage unit32. The externality information325may be discarded after vehicle control processing by the vehicle control unit312.

According to the above first embodiment, the following effects are produced.

(1) The on-vehicle system S1is mounted in a vehicle and provided with an electronic control device3and an externality recognition sensor1. The externality recognition sensor1includes a sensing unit13for acquiring pre-processing externality information123through sensing operation. The on-vehicle system S1includes: a condition calculation unit311that, on the basis of the vehicle position, vehicle traveling direction, and map information, calculates a processing condition322in which information identifying an area on the map is associated with the processing priority of the pre-processing externality information123acquired by the externality recognition sensor; and a processing object determination unit111that, on the basis of the pre-processing externality information123and the processing condition121, creates externality information122having a smaller amount of information than the pre-processing externality information123. 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 information122smaller in the amount of information than the pre-processing externality information123is created and thus even when the electronic control device3does not have a high computing capacity, it can perform required processing.

(2) The processing condition121is the priority3221and processing granularity3222as spatial density of output which are associated with the area3223on 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 information122is information concerning landmarks, and processing of pre-processing externality information123is the process to derive the feature points of a landmark. Therefore, landmark information which depends on the processing condition322can be obtained as externality information122.

(4) A landmark is a lane mark present on a road and the processing granularity3222is point density in derivation of feature points of the lane mark. Therefore, when the processing granularity3222is higher, a larger number of feature points can be derived from one detected lane mark per unit length.

(5) The condition calculation unit311identifies the vehicle traveling direction on the basis of the position of the vehicle and the route324which 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 information122does not include information on the area on the right-turn side and the area for the vehicle to run straight.

(6) The electronic control device3includes a condition calculation unit311and a condition transmission unit33for transmitting the processing condition322to the externality recognition sensor1. The externality recognition sensor1includes a sensing unit13and a processing object determination unit111.

(7) The externality recognition sensor1is mounted in a vehicle and provided with: a sensing unit13that acquires pre-processing externality information through sensing operation; a condition reception unit14that acquires the processing condition121which 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 unit111that creates externality information122having a smaller amount of information than the pre-processing externality information123, on the basis of the pre-processing externality information123and processing condition121. Therefore, even in an environment with a lot of externality information such as an intersection, the externality recognition sensor1creates information on feature points of an area with high priority, namely externality information122smaller in the amount of information than the pre-processing externality information123, on the basis of the calculated processing condition322. Consequently, even when the electronic control device3does not have a high computing capacity, it can deal with an intersection with a lot of information.

The device storage unit32of the electronic control device3may store a plurality of condition creation sources321so that the condition calculation unit311decides which condition creation source321to be used, on the basis of the information indicating the country/region where the own vehicle is travelling, which is acquired from the navigation unit2. For example, the condition calculation unit311may calculate the processing condition322, using the condition creation source321which 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.

In the above first embodiment, the externality recognition sensor1outputs information on the feature points of a landmark which is a stationary object, as externality information122. However, instead the externality recognition sensor1may detect a moving object, such as another vehicle, a pedestrian or bicycle and output the information.

In the above first embodiment, the processing condition322includes processing granularity3222. However, the processing condition322need not include processing granularity3222. Even if that is the case, the externality information122includes 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 toFIG.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 condition322is changed according to the externality information325in 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 S511, which is explained below, is added between Step S504and Step S505.

FIG.14is 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 S511to be carried out next to Step S504, the condition calculation unit311rewrites at least one of the priority and processing granularity calculated at Step S104according to the probability in the externality information325received from the externality information output unit112.

For example, the condition calculation unit311may 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 information325acquired 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 information122includes probability1223that indicates the degree of correctness. The condition calculation unit311corrects the processing condition according to probability1223. Therefore, the condition calculation unit311can correct the processing condition322according to the information on the surroundings which has been acquired in the past.

(9) If the probability for an area in the acquired externality information325is a prescribed value or more, the condition calculation unit311lowers the priority for the area in the processing condition322. 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 toFIG.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 condition322is 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.15is a flowchart which shows processing in the on-vehicle system according to the third embodiment. The steps up to Step S503are the same as in the first embodiment and their explanations are omitted. Next to Step S503, the condition calculation unit311decides 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 unit311decides that the steering angle is consistent with the route, it goes to Step S504or if it decides that the steering angle is not consistent with the route, it goes to Step S522.

At Step S504, as in the first embodiment, it calculates the range, priority, and processing granularity using the route information and goes to Step S505. At Step S522, the condition calculation unit311estimates a node ahead of the own vehicle. At the next step S523, the condition calculation unit311calculates the range, priority, and processing granularity using the node estimated at Step S522and goes to Step S505. Step S505and 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 unit311identifies 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 route324.

Fourth Embodiment

Next, the on-vehicle system according to the fourth embodiment will be described referring toFIG.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.16is a general configuration diagram of the on-vehicle system S4according to the fourth embodiment. All the elements of the on-vehicle system S4are included in the on-vehicle system S1according to the first embodiment. However, the locations of specific functions are different. Specifically, whereas in the first embodiment the processing object determination unit111is located in the externality recognition sensor1, in this embodiment it is located as a processing object determination unit313in the electronic control device3. The processing object determination unit313operates in the same way as the processing object determination unit111in the first embodiment.

In this embodiment, the electronic control device3need not send the calculated processing condition322to the externality recognition sensor1, so it need not include the condition transmission unit33. The externality recognition sensor1does not include the processing object determination unit111, externality information output unit112, and condition reception unit14. However, the externality recognition sensor1includes a pre-processing externality information output unit113that sends the acquired pre-processing externality information123to the electronic control device3.

According to the above fourth embodiment, the following effects are produced.

(11) The electronic control device3includes a condition calculation unit311and a processing object determination unit313. The externality recognition sensor1includes a pre-processing externality information output unit113that sends the pre-processing externality information123to the electronic control device3. Therefore, the vehicle control unit312of the electronic control device3takes only the externality information325calculated by the processing object determination unit313using the processing condition322, as the processing object, so that it can deal with an intersection with a lot of information.

(12) The electronic control device3is mounted in a vehicle and connected to the externality recognition sensor1that acquires the pre-processing externality information123through sensing operation. The electronic control device3includes: a condition calculation unit311that, on the basis of the vehicle position, vehicle traveling direction, and map information, calculates a processing condition322in which information identifying an area on the map is associated with the processing priority of the pre-processing externality information123acquired by the externality recognition sensor1; a pre-processing externality information acquisition unit34that acquires the pre-processing externality information123from the externality recognition sensor1; and a processing object determination unit313that, on the basis of the pre-processing externality information123and the processing condition322, creates externality information325having a smaller amount of information than the pre-processing externality information123.

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).

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