JP2022074513A - Calculation device - Google Patents

Abstract

To provide a calculation device which can reduce delay in calculation.SOLUTION: A calculation device has: a processing part 33 which executes prescribed processing for at least two data respectively; and a storage part 22 which holds at least two data outputted from at least one other processing part (31, 32). When any one of at least two data is written in the storage part 22, the processing part 33 executes prescribed processing for the written data to calculate first processing result even if the other data of at least two data is not written in the storage part 22, and when the other data is written in the storage part 22, the processing part executes prescribed processing for the other data to calculate second processing result, and outputs either the first processing result or the second processing result.SELECTED DRAWING: Figure 4

Description

The present invention relates to an arithmetic unit in which data is exchanged between a plurality of arithmetic modules.

In an arithmetic unit in which data is exchanged between a plurality of arithmetic modules, it is possible to loosely couple the arithmetic modules in order to enable independent modification or expansion for each arithmetic module. To that end, the Publisher / Subscriber model has been proposed. In the Publisher / Subscriber model, each of the arithmetic modules that become the publisher stores the data to be passed to the subscriber as a message in one of the predetermined topics. Each of the arithmetic modules to be a subscriber reads the message required by itself from the topic and executes the processing for the message (see, for example, Patent Document 1).

Japanese Unexamined Patent Publication No. 2019-28599

In the above arithmetic unit, when a subscriber executes a process triggered by having two or more messages, the subscriber executes the process separately for each message. However, the process is not started until all the messages are collected. Therefore, if the delivery of the message from any of the publishers is delayed, the subscriber cannot start processing and the delay will increase.

Therefore, an object of the present invention is to provide an arithmetic unit capable of reducing an arithmetic delay.

According to one embodiment, an arithmetic unit is provided. This arithmetic unit has a processing unit that executes predetermined processing for each of at least two data units, and a storage unit that holds at least two data output from at least one other processing unit. Then, when any one of at least two data is written to the storage unit, the processing unit determines the written data even if the other data of the at least two data is not written to the storage unit. Processing is executed to calculate the first processing result, and when other data is written to the storage unit, a predetermined processing is executed for the other data to calculate the second processing result, and the first processing result is calculated. Output either the processing result or the second processing result.

The arithmetic unit according to the present invention has an effect that the delay in arithmetic can be reduced.

It is a schematic block diagram of the vehicle control system in which the arithmetic unit according to this embodiment is mounted. It is a hardware block diagram of the electronic control device which is one Embodiment of an arithmetic unit. It is a functional block diagram of the processor of the electronic control apparatus regarding the vehicle control processing including the arithmetic processing by this embodiment. (A) and (b) are diagrams for explaining the outline of the execution timing of the planned travel route setting process for each detection result by the route setting unit which is an example of the processing unit, respectively. It is an operation flowchart of the travel schedule route setting process which is an example of the calculation process by this embodiment. It is an operation flowchart of the vehicle control processing including the travel schedule route setting processing.

Hereinafter, the arithmetic unit will be described with reference to the drawings. In this arithmetic unit, when a processing unit that executes a predetermined process for each of at least two data writes any of the data to the memory, the other data of the data is written to the memory. Even if it is not, the process is executed for the data written in the memory and the first process result is calculated. Then, when other data is written to the memory, the processing unit executes processing on the other data to calculate the second processing result, and either the first processing result or the second processing result. Is output. As described above, this arithmetic unit reduces the delay of the arithmetic by starting the processing even if all the data are not prepared.

In the following, an example in which the arithmetic unit is applied to the vehicle control system will be described. In this example, the arithmetic unit detects an image obtained by a camera mounted on the vehicle for photographing the peripheral area of the vehicle and a distance to an object mounted on the vehicle and surrounding the vehicle. From the distance measurement signal obtained by the distance sensor of, the route on which the vehicle is scheduled to travel (hereinafter, simply referred to as the planned travel route) is set. At that time, this arithmetic unit obtains either the detection result of another vehicle based on the image or the detection result of an object around the vehicle such as another vehicle traveling around the vehicle based on the distance measuring signal. Then, the process of setting the planned travel route is executed based on the previously obtained detection result, and if necessary, the planned travel route is calculated based on the other detection result. Then, this arithmetic unit drives the vehicle along one of those planned travel routes.

FIG. 1 is a schematic configuration diagram of a vehicle control system in which an arithmetic unit according to the present embodiment is mounted. Further, FIG. 2 is a hardware configuration diagram of an electronic control device, which is one embodiment of the arithmetic unit. In the present embodiment, the vehicle control system 1 mounted on the vehicle 10 and controlling the vehicle 10 measures the distance between the camera 2 for photographing the surroundings of the vehicle 10 and the objects around the vehicle 10. It has a distance sensor 3 and an electronic control unit (ECU) 4 which is an example of an arithmetic unit. The camera 2, the distance sensor 3, and the ECU 4 are communicably connected to each other via an in-vehicle network conforming to a standard such as a controller area network. The vehicle control system 1 further has a storage device (not shown) that stores a high-precision map representing features related to the running of the vehicle 10, such as a lane marking line, which is used for automatic driving control of the vehicle 10. You may be doing it. Further, the vehicle control system 1 is a receiver (not shown) for positioning the self-position of the vehicle 10 in accordance with a satellite positioning system such as a GPS receiver, and a wireless terminal for wireless communication with other devices (not shown). (Not shown), and a navigation device (not shown) for searching the planned travel route of the vehicle 10 may be provided.

The camera 2 is an example of an imaging unit, and is a two-dimensional detector composed of an array of photoelectric conversion elements having sensitivity to visible light, such as a CCD or C-MOS, and a shooting target on the two-dimensional detector. It has an imaging optical system that forms an image of a region. Then, the camera 2 is attached to the vehicle 10 so as to photograph the surroundings of the vehicle 10. For example, the camera 2 is attached to the vehicle interior of the vehicle 10 toward the front of the vehicle 10 so as to capture an area in front of the vehicle 10. Then, the camera 2 photographs the front region of the vehicle 10 at predetermined imaging cycles (for example, 1/30 second to 1/10 second), and generates an image in which the front region is captured. The vehicle 10 may be provided with a plurality of cameras having different shooting directions or focal lengths.

Each time the camera 2 generates an image, the camera 2 outputs the generated image to the ECU 4 via the in-vehicle network.

The distance sensor 3 can be a sensor that can measure the distance to an object existing in each direction, such as LiDAR or a radar. The distance sensor 3 is attached to the vehicle 10 so that the distance to an object existing in that direction can be measured for each direction of the measurement range set around the vehicle 10. Then, the distance sensor 3 is independent of the camera 2 and has a distance to an object located in that direction in each direction within the measurement range at predetermined measurement cycles (for example, 1/5 second to 1/20 second). To generate a distance measurement signal representing the distance measurement result. The vehicle 10 may be provided with a plurality of distance sensors installed so that the measurement ranges are different from each other.

Each time the distance sensor 3 generates a distance measurement signal, the distance sensor 3 outputs the generated distance measurement signal to the ECU 4 via the in-vehicle network.

The ECU 4 controls the running of the vehicle 10. In the present embodiment, the ECU 4 is an object detected from a series of time-series images obtained by the camera 2 and an object and a vehicle detected from a series of time-series ranging signals obtained by the distance sensor 3. A planned travel route of the vehicle 10 is set so as not to collide with the 10, and the vehicle 10 is automatically controlled so that the vehicle travels along the planned travel route. Therefore, the ECU 4 has a communication interface 21, a memory 22, and a processor 23. The communication interface 21, the memory 22, and the processor 23 may be configured as circuits different from each other, or may be integrally configured as one integrated circuit.

The communication interface 21 has an interface circuit for connecting the ECU 4 to the in-vehicle network. That is, the communication interface 21 is connected to the camera 2 and the distance sensor 3 via the in-vehicle network. Then, each time the communication interface 21 receives an image from the camera 2, the received image is passed to the processor 23. Further, each time the communication interface 21 receives a distance measurement signal from the distance sensor 3, the communication interface 21 passes the received distance measurement signal to the processor 23.

The memory 22 is an example of a storage unit, and has, for example, a volatile semiconductor memory and a non-volatile semiconductor memory. The memory 22 stores an algorithm for vehicle control processing executed by the processor 23 of the ECU 4, various data and parameters used in the vehicle control processing. For example, the memory 22 stores map information, a parameter set for identifying a classifier used in vehicle control processing, and the like. Further, the memory 22 stores the image received by the ECU 4 from the camera 2 and the distance measurement signal received by the ECU 4 from the distance sensor 3 for a certain period of time. Furthermore, the memory 22 stores various data generated during the vehicle control process, such as information about the object detected from the image and information about the object detected from the ranging signal, for a certain period of time.

The processor 23 has, for example, one or a plurality of CPUs (Central Processing Units) and peripheral circuits thereof. The processor 23 may further include other arithmetic circuits such as a logical operation unit, a numerical operation unit, or a graphics processing unit (GPU). Then, the processor 23 executes the vehicle control process so as to automatically control the vehicle 10 based on the image received from the camera 2 and the distance measurement signal received from the distance sensor 3 while the vehicle 10 is traveling.

FIG. 3 is a functional block diagram of the processor 23 of the ECU 3 regarding vehicle control processing including arithmetic processing according to the present embodiment. The processor 23 has a first object detection unit 31, a second object detection unit 32, a route setting unit 33, and a vehicle control unit 34. Each of these parts of the processor 23 is, for example, a functional module realized by a computer program running on the processor 23. Alternatively, each of these parts of the processor 23 may be implemented as a dedicated arithmetic circuit of the processor 23.

The first object detection unit 31 is an example of another processing unit, and is a detection represented by an image by executing an object detection process for the received image each time the ECU 4 receives an image from the camera 2. The target object around the vehicle 10 (hereinafter, simply referred to as a detection target object) is detected. The object to be detected includes, for example, other vehicles and pedestrians. Further, the object to be detected may include features related to the traveling control of the vehicle 10, such as road markings such as lane marking lines, various road signs or traffic lights.

In the present embodiment, the first object detection unit 31 inputs an image to the first classifier. The first classifier outputs the certainty indicating the certainty that the detection target object of the type is included in the region for each type of the detection target object for various regions on the input image. Then, the first object detection unit 31 determines that the detection target object of any type is included in the region where the certainty of the detection target object of any type is equal to or higher than a predetermined threshold value. In the following, the area determined to include the object to be detected is referred to as an object area for convenience of explanation.

The first object detection unit 31 is a convolutional neural network (hereinafter, simply referred to as CNN) type architecture such as a Single Shot MultiBox Detector (SSD) or a Faster R-CNN as a first classifier. A so-called deep neural network (hereinafter, simply referred to as DNN) can be used. The first classifier is pre-learned according to a learning method such as an error back propagation method by using a large number of images (teacher images) showing an object to be detected.

The first object detection unit 31 determines the position and range of the object area in which the object to be detected is represented on the image, the type of the object included in the object area, and the first detection result indicating the certainty. , Write to the memory area preset for holding the detection result of the memory 22. The first detection result is an example of data to be subject to predetermined processing executed by the processing unit.

The second object detection unit 32 is another example of another processing unit, and each time the ECU 4 receives a distance measurement signal from the distance sensor 3, the second object detection unit 32 executes an object detection process for the received distance measurement signal. The detection target object represented by the ranging signal is detected.

In the present embodiment, the second object detection unit 32 inputs a ranging signal to the second classifier. The second classifier outputs the certainty indicating the certainty that the object to be detected is located in that direction for various directions included in the input distance measurement signal. Then, the second object detection unit 32 determines that the detection target object is located in the direction in which the certainty level is equal to or higher than a predetermined threshold value. In the following, the direction in which the object to be detected is determined to be located is referred to as an object direction for convenience of explanation.

The second object detection unit 32 can use, for example, a DNN having a CNN type architecture as the second classifier. Similar to the first classifier, the second classifier may be pre-learned according to a learning method such as an error back propagation method by using a large number of distance measurement signals (teacher data) representing the object to be detected.

The second object detection unit 32 writes the second detection result, which represents the object orientation in which the object to be detected is represented and the certainty, into a memory area preset for holding the detection result in the memory 22. The second detection result is another example of the data to be the target of the predetermined processing executed by the processing unit.

The route setting unit 33 does not collide with the detection target object detected from the image or the detection target object detected from the ranging signal, particularly other vehicles or people traveling around the vehicle 10, and the destination. The planned travel route in the nearest predetermined section (for example, 500 m to 1 km) is set so that the vehicle 10 travels along the planned travel route up to. The planned travel route is represented, for example, as a set of target positions of the vehicle 10 at each time when the vehicle 10 travels in a predetermined section. The route setting unit 33 is an example of a processing unit that executes a predetermined process.

In the present embodiment, the route setting unit 33 tracks an object detected by the first object detection unit 31 or the second object detection unit 32 in order to generate a planned travel route, and in the latest predetermined section. , Predict the trajectory of the tracked object.

Therefore, the route setting unit 33 has an image generation cycle by the camera 2 (that is, a processing cycle of the first object detection unit 31) and a distance measurement signal generation cycle by the distance sensor 3 (that is, the second object detection unit 31). The first detection result and the second detection result are written to the memory 22 by referring to the memory area for holding the detection result of the memory 22 at each predetermined processing cycle independent of each of the processing cycles of 32). Check if it is. Then, when either the first detection result or the second detection result is written in the memory 22, the route setting unit 33 reads the written detection result from the memory 22 and erases the written detection result from the memory 22. do. Then, the route setting unit 33 sets the planned travel route based on the read detection result.

For example, when the read detection result is the first detection result based on the image, the route setting unit 33 performs tracking processing based on the optical flow such as the Lucas-Kanade method in the latest image obtained by the camera 2. By applying to the object area of interest and the object area in the past image, the object represented in the object area is tracked. Therefore, the route setting unit 33 extracts a plurality of feature points from the object region of interest, for example, by applying a filter for feature point extraction such as SIFT or Harris operator to the object region of interest. Then, the route setting unit 33 may calculate the optical flow by specifying the corresponding points in the object region in the past image for each of the plurality of feature points according to the applied tracking method. Alternatively, the route setting unit 33 may apply another tracking method applied to tracking a moving object detected from the image to the object area of interest in the latest image and the object area in the past image. , The object represented in the object area may be tracked.

The route setting unit 33 executes the viewpoint conversion process for each object being tracked by using information such as the mounting position of the camera 2 on the vehicle 10, so that the coordinates in the image of the object are the coordinates on the bird's-eye view image. Convert to (bird's eye coordinates). At that time, the route setting unit 33 obtains each image according to the position and posture of the vehicle 10 at the time of acquiring each image, the estimated distance to the detected object, and the direction from the vehicle 10 to the object. The position of the detected object can be estimated. The position and posture of the vehicle 10 at the time of acquiring each image may be estimated by collating the image obtained by the camera 2 with the high-precision map. Then, the route setting unit 33 estimates the predicted locus of the object up to a predetermined time by executing a prediction process using a Kalman Filter, a Particle filter, or the like for a series of bird's-eye view coordinates in the latest predetermined period. Can be done.

When the read detection result is the second detection result based on the distance measurement signal, the route setting unit 33 determines the position and posture of the vehicle 10 at the time of acquiring the latest distance measurement signal and the detected object. Based on the orientation and distance, the position of the detected object at the time of acquisition of the latest ranging signal is estimated. The position and posture of the vehicle 10 at the time of acquiring the latest ranging signal is based on, for example, the acceleration and yaw rate of the vehicle 10 in the period from the time of image acquisition immediately before that to the time of acquiring the latest ranging signal. It is estimated by adding the calculated change amount of the position and posture of the vehicle 10 to the position and posture of the vehicle 10 at the time of the latest image acquisition. Then, the route setting unit 33 determines that the object detected by the latest ranging signal is the object being tracked, which is the predicted locus closest to the position of the object, and the position at the time of acquiring the latest ranging signal. Is applied to the prediction process to update the prediction trajectory of the object being tracked.

Based on the predicted locus of each object being tracked, the route setting unit 33 sets the predicted value of the distance between each of the objects being tracked up to a predetermined time ahead and the vehicle 10 to be a predetermined distance or more. , Set the planned travel route of the vehicle 10 so as to follow the planned travel route to the destination. At that time, the route setting unit 33 calculates the reciprocal of the sum of the distances to the object being tracked closest to the position on the planned travel route at each time up to a predetermined time as an evaluation function, and the evaluation function is minimized. Therefore, the planned travel route may be set according to a predetermined optimization method such as a dynamic planning method or a steepest descent method.

Further, the route setting unit 33 calculates the evaluation value of the generated planned travel route. For example, the route setting unit 33 determines the certainty of the detected object included in the first or second detection result, and the planned travel route at each time from the center of the lane in which the vehicle 10 is traveling to a predetermined time ahead. The evaluation value is calculated based on at least one of the sum of the deviation amounts up to the upper position (hereinafter, simply referred to as the total deviation amount). Specifically, when the route setting unit 33 sets the planned travel route using the first detection result, the route setting unit 33 sets the first weighting coefficient to the average value of the certainty of each object detected in the first detection result. The sum of the multiplied value and the value obtained by multiplying the reciprocal of the total sum deviation amount by the second weighting coefficient is calculated as the evaluation value. Similarly, when the route setting unit 33 sets the planned travel route using the second detection result, the route setting unit 33 multiplies the average value of the certainty of each object detected in the second detection result by the first weighting coefficient. The sum of the above values and the value obtained by multiplying the reciprocal of the total sum deviation amount by the second weighting coefficient is calculated as the evaluation value. In addition, either one of the first weighting coefficient and the second weighting coefficient may be set to zero. Further, the route setting unit 33 may calculate the total deviation amount by referring to the high-precision map and specifying the lane through which the planned travel route of the vehicle 10 passes.

The route setting unit 33 has a maximum allowable delay (for example, the elapsed time since the memory 22 reads the detection result of the first detection result and the second detection result that was used for setting the planned travel route first. , 100ms), it is confirmed whether or not the other detection result is written in the memory 22. If the other detection result is written, the route setting unit 33 reads the other detection result from the memory 22, sets the planned travel route based on the other detection result, and evaluates the travel schedule route. Is calculated. Then, the route setting unit 33 selects the planned travel route having the higher evaluation value among the planned travel route set based on the first detection result and the planned travel route set based on the second detection result. Output to the control unit 34. As a result, if either of the first detection result and the second detection result is written in the memory 22, the route setting unit 33 can start the setting process of the planned travel route, and thus the vehicle control process. The delay as a whole can be reduced.

In the route setting unit 33, the evaluation value of the planned travel route set based on the detection result used earlier among the first detection result and the second detection result causes the vehicle 10 to travel safely. If the evaluation threshold value or more is assumed to be possible, the planned travel route may be output to the vehicle control unit 34. Then, the route setting unit 33 may simply erase from the memory 22 without executing the process related to the setting of the planned travel route for the other of the first detection result and the second detection result. As a result, the route setting unit 33 can omit the setting process of the planned travel route based on the other detection result, so that the planned travel route can be output faster and the calculation amount can be reduced.

Further, when the other detection result is not written in the memory 22 even if the elapsed time reaches the allowable maximum delay, the route setting unit 33 is ahead of the first detection result and the second detection result. The planned travel route set based on the detection result used in is output to the vehicle control unit 34. As a result, even if it takes too much time to detect an object around the vehicle 10 with respect to either an image or a distance measurement signal, the route setting unit 33 outputs the planned travel route to the vehicle control unit 34 without delay. Can be done.

4 (a) and 4 (b) are diagrams for explaining the outline of the execution timing of the planned travel route setting process for each detection result by the route setting unit 33, respectively. In FIGS. 4 (a) and 4 (b), the horizontal axis represents time.

In the example shown in FIG. 4A, the route setting unit 33 starts the planned travel route setting process at the time t1. At this point, the first detection result is written in the memory 22. Therefore, the route setting unit 33 reads the first detection result from the memory 22, executes the planned travel route setting process based on the first detection result, and sets the planned travel route (first processing result). do.

After that, the second detection result is written to the memory 22 at the time t2 before the elapsed time from the time t1 reaches the allowable maximum delay Dmax. After that, at time t3, the route setting unit 33 refers to the memory 22, reads the second detection result from the memory 22, executes the planned travel route setting process based on the second detection result, and travels. Set the scheduled route (second processing result). Then, the route setting unit 33 outputs the planned travel route having the higher evaluation value among the planned travel route set based on the first detection result and the planned travel route set based on the second detection result. do. However, as described above, when the evaluation value of the planned travel route based on the first detection result is equal to or higher than the evaluation threshold value, the route setting unit 33 executes the planned travel route setting process based on the second detection result. Instead, the planned travel route based on the first detection result may be output.

Even in the example shown in FIG. 4B, the route setting unit 33 starts the planned travel route setting process at the time t1. At this point, the first detection result is written in the memory 22. Therefore, the route setting unit 33 reads the first detection result from the memory 22 and executes the planned travel route setting process based on the first detection result. However, in this example, the second detection result is not written in the memory 22 even if the elapsed time from the time t1 reaches the allowable maximum delay Dmax. Therefore, when the elapsed time reaches the allowable maximum delay Dmax, the route setting unit 33 outputs the planned travel route based on the first detection result.

FIG. 5 is an operation flowchart of the planned travel route setting process by the route setting unit 33, which is an example of the calculation process according to the present embodiment.

The route setting unit 33 refers to the memory area for holding the detection result of the memory 22 and confirms whether or not at least one of the first detection result and the second detection result is written in the memory 22 (step). S101). When none of the detection results is written in the memory 22 (step S101-No), the route setting unit 33 re-executes the process of step S101 after the elapse of a predetermined time.

On the other hand, when at least one of the first detection result and the second detection result is written in the memory 22 (step S101-Yes), the route setting unit 33 reads the detection result of the other from the memory 22 and reads it out. The planned travel route (first processing result) is set based on the detection result, and the evaluation value of the planned travel route is calculated (step S102). Then, the route setting unit 33 determines whether or not the evaluation value is equal to or higher than the evaluation threshold value (step S103). If the evaluation value is equal to or greater than the evaluation threshold value (step S103-Yes), the route setting unit 33 outputs the set travel schedule route to the vehicle control unit 34 (step S104), and ends the travel schedule route setting process.

On the other hand, when the evaluation value is less than the evaluation threshold value (step S103-No), the route setting unit 33 refers to the memory 22 again, and the other of the first detection result and the second detection result is written in the memory 22. It is confirmed whether or not it is satisfied (step S105). When the other detection result is not written in the memory 22 (step S105-No), the route setting unit 33 reaches the allowable maximum delay after reading one detection result from the memory 22 in step S102. It is determined whether or not it has been done (step S106).

When the elapsed time has reached the allowable maximum delay (step S106-Yes), the route setting unit 33 transfers the planned travel route set based on the detection result previously read from the memory 22 to the vehicle control unit 34. It is output (step S104), and the planned travel route setting process is completed.

On the other hand, when the elapsed time has not reached the allowable maximum delay (step S106-No), the route setting unit 33 re-executes the processes after step S105 after the elapse of the predetermined time.

Further, in step S105, when the other detection result is written in the memory 22 (step S105-Yes), the other detection result is read from the memory 22, and the planned travel route (second) is based on the read detection result. (Processing result of) is set, and the evaluation value of the planned travel route is calculated (step S107). Then, the route setting unit 33 selects the planned travel route having the higher evaluation value among the planned travel route set based on the first detection result and the planned travel route set based on the second detection result. Output to the control unit 34 (step S108). Then, the route setting unit 33 ends the travel route setting process.

Upon receiving the planned travel route, the vehicle control unit 34 controls each unit of the vehicle 10 so that the vehicle 10 travels along the planned travel route. For example, the vehicle control unit 34 obtains the target acceleration of the vehicle 10 according to the planned travel route and the current vehicle speed of the vehicle 10 measured by the vehicle speed sensor (not shown), and opens the accelerator so as to be the target acceleration. Set the degree or brake amount. Then, the vehicle control unit 34 obtains the fuel injection amount according to the set accelerator opening degree, and outputs a control signal corresponding to the fuel injection amount to the fuel injection device of the engine of the vehicle 10. Alternatively, the vehicle control unit 34 outputs a control signal according to the set brake amount to the brake of the vehicle 10.

Further, when the vehicle 10 changes the course of the vehicle 10 in order to travel along the planned travel route, the vehicle control unit 34 obtains the steering angle of the vehicle 10 according to the planned travel route, and responds to the steering angle. The control signal is output to an actuator (not shown) that controls the steering wheel of the vehicle 10.

FIG. 6 is an operation flowchart of a vehicle control process including a planned travel route setting process executed by the processor 23.

The first object detection unit 31 of the processor 23 detects an object around the vehicle 10 represented by the image generated by the camera 2, and writes the detection result (first detection result) into the memory 22 (step). S201). Further, the second object detection unit 32 of the processor 23 detects an object around the vehicle 10 represented by the distance measurement signal generated by the distance sensor 3, and stores the detection result (second detection result) in the memory. Write to 22 (step S202).

The route setting unit 33 of the processor 23 sets the planned travel route based on at least one of the first detection result and the second detection result read from the memory 22 (step S203). Then, the vehicle control unit 34 of the processor 23 controls each unit of the vehicle 10 so that the vehicle 10 travels along the set planned travel route (step S204). Then, the processor 23 ends the vehicle control process.

As described above, this arithmetic unit writes any one of the plurality of data to the memory with respect to the predetermined processing executed for each of the plurality of data to be processed. If so, the predetermined processing is executed for the written data. Then, when the other data is written to the memory, the arithmetic unit also executes the predetermined processing on the other data. Then, this arithmetic unit outputs any of the obtained arithmetic results. Therefore, since this arithmetic unit can start a predetermined process even if a plurality of data are not prepared, the delay of the entire process can be reduced.

In the above embodiment, there are two types of data to be processed, but there may be three or more types of data to be processed. For example, when the vehicle 10 has three or more cameras having different focal lengths or shooting directions, the route setting unit 33 determines the planned travel route based on the detection result of the object from the image obtained for each camera. May be set. Also in this case, as in the above embodiment, when the first detection result of the object for the image from any camera is written in the memory 22, the route setting unit 33 receives the first detection result. Start setting the planned travel route. Further, when the second detection result of the object for the image from another camera is subsequently written in the memory 22, the route setting unit 33 may start setting the planned travel route for the second detection result as well. good. Then, the route setting unit 33 may output the planned travel route having the highest evaluation value based on the evaluation value of each planned travel route.

This arithmetic unit may be applied to other than the vehicle control system. This arithmetic unit is applied to various devices or systems that perform predetermined processing independently of their preprocessing for data obtained from each of a plurality of other processing units that are executed asynchronously with each other. It is possible. At that time, the device on which the other processing unit is mounted and the arithmetic unit may be communicably connected via a wired or wireless communication network. Then, data may be written from a device on which another processing unit is mounted to a storage unit of this arithmetic unit via a communication network.

As described above, those skilled in the art can make various changes within the scope of the present invention according to the embodiment.

1 Vehicle control system 2 Camera 3 Distance sensor 4 Electronic control device (arithmetic device)
21 Communication interface 22 Memory 23 Processor 31 First object detection unit 32 Second object detection unit 33 Route setting unit (processing unit)
34 Vehicle control unit

Claims (1)

A processing unit that executes predetermined processing for each of at least two data,
It has a storage unit that holds at least the two data output from at least one other processing unit, and has a storage unit.
When any of the at least two data is written to the storage unit, the processing unit may write the written data even if the other data of the at least two data is not written to the storage unit. When the other data is written to the storage unit, the predetermined process is executed on the other data to calculate the first process result, and the second process is executed. The processing result is calculated, and either the first processing result or the second processing result is output.
Arithmetic logic unit.

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