WO2024090004A1 - Design assistance method, design assistance system, and program - Google Patents

Abstract

Provided are a design assistance method, a design assistance system, and a program with which it is possible to design an ODD that suppresses an increase in the cost of developing automated driving services and improves key performance indicators of business proprietors. This design assistance system acquires environmental data from an environmental measurement device for measuring the environment of a service provision area managed by a customer, and customer requirements, and outputs improved values of key performance indicators of the customer. This design assistance system is characterized by comprising: an automated driving control function database that stores programs for performing automated driving control of a vehicle traveling in the service provision area; an area environmental data generation unit that is provided with an area digital map generation unit for generating a digital map of the service provision area using the environmental data; an automated driving ODD automatic definition unit that generates and outputs an operational design domain, which constitutes environmental constraint conditions for operating an automated driving service, from information about the digital map; an ODD adjustment unit that evaluates the sufficiency of the automated driving control function specifications stored in pairs in an automated driving control program, with respect to the operational design domain output from the automated driving ODD automatic definition unit, and changes the operational design domain on the basis of the evaluation result; an automated driving control system evaluation unit that evaluates the operational design domain on the basis of the customer requirements; and a KPI evaluation unit that generates a customer requirement evaluation formula for evaluating the customer's key performance indicators, on the basis of the customer requirements, calculates the customer requirement evaluation formula on the basis of the value output from the automated driving control system evaluation unit, and outputs the operational design domain and the customer's key performance indicators. This design assistance system is further characterized in that: the ODD adjustment unit changes the operational design domain on the basis of the value of the customer requirement evaluation formula calculated and output by the KPI evaluation unit, so as to improve the value of the customer requirement evaluation formula; and the KPI evaluation unit outputs improved values of the customer's key performance indicators on the basis of the changed operational design domain.

Description

DESIGN ASSISTANCE METHOD, DESIGN ASSISTANCE SYSTEM, AND PROGRAM

The present invention relates to a design support method, design support system, and program for the Operational Design Domain (ODD) of control systems for automatically driving transport robots, automobiles, and other work vehicles.

In recent years, control systems have been developed to realize automated driving of automobiles and automated driving of various industrial vehicles such as transport robots and construction machinery. The automation of industrial vehicles is expected to reduce costs by making the site unmanned, and to improve work efficiency by standardizing work efficiency. In addition, automated driving of automobiles is expected to improve traffic congestion and reduce accidents.

The configuration and specifications of the control systems that realize automation vary widely depending on the target vehicle and the environment in which it operates, and designing them requires know-how such as matching the vehicle's control characteristics with its performance to suit the environment, which requires a significant amount of work.

In particular, to align the vehicle's control characteristics with its environmental performance, it is necessary to define the ODD, which is the environmental condition that guarantees the operation of the autonomous driving control system. However, it is also costly for the development engineers to investigate the environment in which the autonomous vehicle will be introduced and confirm its compatibility with the specifications of the autonomous driving control system.

The design support system described in Patent Document 1 is known as a method for defining and updating an ODD. Patent Document 1 describes a technology for creating a data set from an environmental map and defining an ODD for a condition space through a safety evaluation of an autonomous driving control system. In addition, the defined ODD can be updated when additional data is received. This type of design support system makes it possible to automatically define an ODD from an environmental map without relying on individual know-how, thereby reducing the number of people required for development and lowering development costs.

Publication No. WO2021147301A1

According to the design support system described in Patent Document 1, which defines an ODD based on a reliability evaluation (such as operation rate) from an environmental data set, the ODD that matches the environment in which the autonomous driving service is provided requires an autonomous driving control system with high functionality, which may not satisfy the key performance indicators indicated by the operator of the autonomous driving service. For example, this may result in increased development costs or a decrease in operation rate.

Therefore, the present invention aims to provide a design support method, design support system, and program that can design an ODD that suppresses increases in development costs for autonomous driving services and improves key performance indicators for business operators.

In view of the above, the present invention provides a design support system that receives environmental data from an environmental measurement device that measures the environment of a service provision area managed by a customer and customer requests and outputs improvement values of the customer's key performance indicators, comprising an automatic driving control function database that stores a program for automatic driving control of vehicles traveling in the service provision area, an area environmental data generation unit that has an area digital map generation unit that uses the environmental data to generate a digital map of the service provision area, an automatic driving ODD automatic definition unit that generates and outputs an operation design area that is an environmental constraint condition for operating an automatic driving service from information on the digital map, and an automatic driving control program that generates and outputs an operation design area that is an environmental constraint condition for operating an automatic driving service for the operation design area output from the automatic driving ODD automatic definition unit. The design support system is characterized in that it includes an ODD adjustment unit that evaluates the fulfillment of the driving control function specifications and changes the operation design domain based on the evaluation results, an automatic driving control system evaluation unit that evaluates the operation design domain based on the customer requirements, and a KPI evaluation unit that generates a customer requirement evaluation formula that evaluates the customer's key performance indicators based on the customer requirements, calculates the customer requirement evaluation formula based on the value output from the automatic driving control system evaluation unit, and outputs the operation design domain and the customer's key performance indicators, and the ODD adjustment unit makes changes to the operation design domain so as to improve it over the previous value of the customer requirement evaluation formula based on the value of the customer requirement evaluation formula calculated and output by the KPI evaluation unit, and the KPI evaluation unit outputs an improvement value of the customer's key performance indicator based on the changed operation design domain.

　The present invention also provides a design support method that obtains environmental data from an environmental measurement device that measures the environment of a service area managed by a customer and customer requirements, and outputs an improvement value of the customer's key performance indicators using a computer device, the design support method comprising: an automatic driving control function database that stores an automatic driving control program for automatically controlling the driving of vehicles that run in the service area; a calculation unit of the computer device uses the environmental data to generate a digital map of the service area, generates an operation design domain that is an environmental constraint condition for operating the automatic driving service from the information of the digital map, evaluates the satisfaction of the automatic driving control function specifications stored in the automatic driving control program in pairs for the operation design domain, changes the operation design domain based on the evaluation results, evaluates the operation design domain based on the customer requirements, generates a customer requirements evaluation formula that evaluates the customer's key performance indicators based on the customer requirements, calculates the customer requirements evaluation formula based on the value output from the automatic driving control system evaluation unit, obtains the operation design domain and the customer's key performance indicators, and modifies the operation design domain so as to improve it from the previous value of the customer requirements evaluation formula based on the value of the customer requirements evaluation formula, and obtains the improvement value of the customer's key performance indicators based on the modified operation design domain.

　Furthermore, in the present invention, "a design support program for receiving environmental data from an environmental measurement device that measures the environment of a service provision area managed by a customer and customer requests and outputting an improvement value of the customer's key performance indicators, comprising an automatic driving control function program which is an automatic driving control program for automatic driving control of vehicles traveling in the service provision area, an area environmental data generation program having an area digital map generation unit that generates a digital map of the service provision area using the environmental data, an automatic driving ODD automatic definition program that generates and outputs an operation design area that is an environmental constraint condition for operating an automatic driving service from information on the digital map, and an evaluation result obtained by evaluating the satisfaction of the automatic driving control function specifications stored in the automatic driving control program in pairs for the operation design area. a KPI evaluation program that generates a customer requirement evaluation formula for evaluating a customer's key performance indicators based on the customer requirements, calculates the customer requirement evaluation formula based on the value output from the automatic driving control system evaluation program, and outputs the operation design area and the customer's key performance indicators, the ODD adjustment program modifies the operation design area so as to improve it over the previous value of the customer requirement evaluation formula based on the value of the customer requirement evaluation formula calculated and output by the KPI evaluation program, and the KPI evaluation program outputs an improved value of the customer's key performance indicators based on the modified operation design area.

In contrast to the conventional method of providing autonomous driving services only under an ODD based on the environment in which the autonomous driving service is provided, the present invention provides a design support system that can automatically design an ODD that can improve the business owner's key performance indicators. This makes it possible to provide an autonomous driving service that improves the business owner's key performance indicators.

FIG. 1 is a diagram showing an example of the configuration of a design support system according to a first embodiment of the present invention. FIG. 1 is a diagram showing an example of an automated transport area providing cargo transport services. FIG. 13 is a diagram showing an example of a shape digital map. FIG. 4 is a diagram showing an example of a data structure of an automatic driving control function database. FIG. 13 is a diagram showing an example of a traceability table showing the relationship between autonomous driving control function data, ODD items, and KPI values. FIG. 2 is a flowchart showing a design support method according to the first embodiment of the present invention. FIG. 2 is a diagram showing an example of use of the output of the design support system 1. FIG. 1 illustrates an example of a work site providing freight transportation services. FIG. 13 is a diagram showing an example of a work site after an environment change. FIG. 1 illustrates an example of a public highway environment in which freight transportation services are provided. FIG. 13 is a diagram showing an example of a traceability table.

Below, an embodiment of the present invention will be explained with reference to the drawings. However, the design support method, design support system, and program according to the embodiment of the present invention will be explained using a design example of an automated cargo transport service in a logistics warehouse using an automated transport vehicle.

The present invention can be applied to the design of all services related to machines capable of autonomous driving in specific environments, and the application of the present invention is not limited to automated guided vehicle services.

In the following, in Example 1, the basic configuration of a design support method and a design support system according to an embodiment of the present invention will be described, in Example 2, the case where the service provision area is a work site will be described, in Example 3, the case where the service provision area is a general public road will be described, and in Example 4, the program of the design support system will be described.

FIG. 1 is a diagram showing an example of the configuration of a design support system 1 according to an embodiment of the present invention. In the first embodiment, a design support system 1 is described that is applied to the creation of an automated cargo transport service in a logistics warehouse (area) 10 using automated transport vehicles.

The design support system 1 in Figure 1 includes an area environment data generation unit 3, an automatic driving control function database DB, an automatic driving control system evaluation unit 5, a customer information input unit 6, an automatic automatic driving ODD definition unit 7, an ODD adjustment unit 8, and a KPI evaluation unit 9, and provides design support by importing the output of an environmental measurement device 2 from an external logistics warehouse (area) 10 and customer requirements.

The design support system 1, which is composed of a computer device, stores a design support program in an internal ROM for automatically designing an ODD for an autonomous vehicle, and is a system that realizes a design support method by executing processing according to the program in a CPU. The program will be described in Example 5.

The configuration shown in Figure 1 will be explained in detail below. However, since the parts of the present invention are indicated by thick lines and parts of existing technology are indicated by thin lines, the parts of existing technology indicated by thin lines will be explained first.

The design support system 1 is connected to the environmental measuring device 2 via a signal line, and acquires environmental information D1 for the area 10 for which the design support system 1 provides services. The area 10 for which the services are provided is, for example, the automated transport area for which cargo transport services are provided as shown in FIG. 2. Trucks 18 enter and leave the automated transport area 10 from the outside, and cargo is carried in and out between the trucks 18 and a cargo storage area 16 by forklifts 17. Furthermore, cargo in the cargo storage area 16 is transported by automated transport vehicle 11 to an appropriate designated storage location, moving along a route that avoids obstacles such as shelves 12 within the automated transport service provision area 15.

The automated guided vehicle 11 is equipped with cameras and LiDAR as environmental measurement devices 2B, and cameras and LiDAR are placed at appropriate locations within the area 10 as fixed environmental measurement devices 2A, which allow the environment within the area to be understood. Environmental information D1 measured by these environmental measurement devices 2A and 2B is transmitted to the design support system 1.

In this way, the environmental measuring device 2 may obtain environmental information about the automatic transport area 10 by driving the automatic transport vehicle 11 along a route specified by the area data collection unit 3a described below, or the environmental measuring device 2 may be installed at any location within the automatic transport area 10 to collect environmental information about the automatic transport area 10.

Here, the environmental information D1 refers to the road surface and structure positions and shapes on which the automated guided vehicle 11 travels, the brightness of lighting in the travel area, and the availability of infrastructure such as Wi-Fi. Therefore, the environmental measurement device 2 is not limited to cameras and LiDAR, but also includes devices for measuring radio waves and the brightness of lighting. Furthermore, the environmental measurement device 2 may be installed on either the vehicle or the equipment side, and the signal line between the environmental measurement device 2 and the design support system 1 may be a wired or wireless connection.

The environmental information D1 measured by the environmental measuring device 2 is input to the area environmental data generating unit 3.
The area environment data generating section 3 is composed of an area data collecting section 3a, an area digital map generating section 3b, and a service provision area specifying section 3c. The service provision area specifying section 3c which is involved in the present invention will be described later.

Among these, the area data collection unit 3a collects environmental information D1 of the automatic transport area 10 from an environmental measurement device 2B mounted on an automatic transport vehicle 11 traveling within the automatic transport area 10 that provides cargo transport services, for example, as shown in FIG. 2. The environmental measurement device 2B may obtain the environmental information D1 of the automatic transport area 10 by having the automatic transport vehicle 11 travel along a route specified by the area data collection unit 3a, or the environmental measurement device 2 may be installed at any location within the automatic transport area 10 to collect the environmental information D1 of the automatic transport area 10. Note that FIG. 2 also shows on-site reference coordinates 19 for defining the position within the area.

The area digital map generator 3b aggregates the environmental information D1 collected by the area data collector 3a, and constructs a shape digital map in which obstacles such as shelves 12 installed in the automatic transport area 10 are represented, for example, as a collection of three-dimensional points.

Figure 3 shows, as an example of a digital shape map, shape data of a shelf 12 generated based on an image acquired by an image sensor or the like mounted on an automated guided vehicle 11. This data is obtained by extracting the outline 13 based on the image of the shelf 12, and data such as the external dimensions of the shelf 12 and aisle width data 20 are treated as the digital shape map.

In addition, it is advisable to store and manage the information acquired by the environmental measuring device 2 in a digital map regarding environmental information related to radio waves such as Wi-Fi in the automatic transport area 10, such as managing each area according to whether or not wireless infrastructure is available. For example, a Wi-Fi antenna 21 is installed in the shooting area in FIG. 3, and it is advisable to also manage environmental information related to radio waves in this location.

The autonomous driving control function database DB in FIG. 1 stores autonomous driving control function data D2. As shown in FIG. 4, an example of autonomous driving control function data D2 is stored in a relational database format, including the autonomous driving control function ID (D21), function name D22, function specifications D23, autonomous driving control program D24 for the function, sensors D25 required to realize the function, and KPIs (D26, D27). The autonomous driving control function is, for example, a function to acquire the position of the vehicle in the autonomous transport area 10, and control of the autonomous transport vehicle 11 to acquire luggage from the shelf 12.

The automatic driving control system evaluation unit 5 in FIG. 1 includes an operation evaluation unit 5a, and has a function of evaluating the automatic driving performance in the automatic transport area 10 when some of the automatic driving control functions as automatic driving control programs registered in the automatic driving control function database DB are installed on an automatic transport vehicle 11. The operation evaluation unit 5a may be configured, for example, as a vehicle motion simulator capable of performing simulations on a computer, or may be a computing device that performs evaluation based on the functional specifications of the automatic driving control functions registered in the automatic driving control function database DB.

The above configuration indicated by thin lines is related to the existing technology. Based on this premise, the present invention will be described in detail below. First, the customer information input unit 6 sets key performance indicators (hereinafter, KPIs) as variables based on request input from the customer to whom the service is provided.
The KPIs are, for example, the introduction cost and running cost of the service, safety, operation rate, the number of cargo shipments per unit time, etc. The customer information input unit 6 also defines a formula for calculating the KPIs.

The customer information input unit 6 also identifies the area in which the service is provided based on the input request for the service, and outputs information about the area to the service provision area identification unit 3c. For example, the customer information input unit 6 may be equipped with a system that identifies the area using a graphical user interface (GUI), such as by specifying a rectangle on a map. In this case, area 10 in FIG. 2 is identified as the area in which the service is provided.

When the service provision area is the automatic transport area 10 in FIG. 2, the customer may use the GUI to specify the automatic transport service provision area 15 and the cargo storage area 16. At this time, the forklift 17 is specified to only enter the cargo storage area 16 within the automatic transport service provision area 15. Furthermore, the customer can specify that the forklift 17 is to be manually operated, and that the forklift 17 will transport cargo from the cargo storage area 16 to the truck 18.

As a result, the service provision area identification unit 3c in Figure 1 receives information on the service area 10 and identifies the area. For example, the area is identified by specifying a certain area based on the area's latitude and longitude position and size from a position on a map specified by the GUI provided in the customer information input unit 6, or by specifying a route by specifying the latitude and longitude of multiple points. In Figure 2, as an example, on-site reference coordinates 19 are provided in the automatic transport service provision area 15, and the coordinates of the four corners of the automatic transport service provision area 15 are specified by the on-site reference coordinates 19.

The identified area information is provided to the area data collection unit 3a, which collects environmental information within the area. The area information is also provided to the area digital map generation unit 3b, and the area digital map generation unit 3b specifies the range within which the digital map is to be generated.

As a result, the area environment data generation unit 3 organizes, for example, the current area configuration (area digital map, obstacles, etc.) and in-area environment information of the area 10 for which the service is provided, as well as what (where) and how the driving environment is to be changed from this state based on customer requests, along with the requested items, and passes this information to the automatic driving ODD definition unit 7 for the next stage of processing.

The automated driving ODD automatic definition unit 7 in FIG. 1 includes an operational environment characteristic extraction unit 7a and an operational environment change unit 7b. The operational environment characteristic extraction unit 7a defines the ODD based on the digital map generated by the area digital map generation unit 3b and environmental information D1. Items of the ODD include, for example, the minimum width 20 of the passageway through which the automated transport vehicle 11 in FIG. 3 passes, the presence or absence of infrastructure equipment such as a WiFi antenna 21 required for the automated transport vehicle 11 to use WiFi, the presence or absence of workers in the automated transport service provision area 15 in FIG. 2, and the maximum vehicle speed defined by the safety rules of the automated transport area 10.

The operation environment change unit 7b has a function of outputting changes related to ODD items to the operation environment characteristic extraction unit 7a when there is a change in the automatic transport area 10 related to the ODD items. For example, if there is a change in the layout of the shelves 12 in the automatic transport area 10 and the minimum value of the aisle width 20 in FIG. 3 is changed, the minimum value is output. Also, when a change is made to the automatic transport area 10, such as installing a fixed surveillance camera 2A in the automatic transport area 10 in FIG. 2, the change is extracted. The installation of a fixed surveillance camera 2A means that the ODD item's infrastructure sensor support, that is, the automatic driving of the automatic transport vehicle 11 can use infrastructure sensor support, and this change is defined as the presence or absence of infrastructure sensor support for the ODD item through the operation environment characteristic extraction unit 7a.

Furthermore, the operation environment change unit 7b also has a function to calculate, based on the digital map, candidates for installing infrastructure sensors such as the surveillance cameras 2A that provide infrastructure sensor support in the automatic transport area 10. For example, based on the digital map, if there is an area within the automatic transport service provision area 15 where multiple automatic transport vehicles 11 have difficulty detecting each other due to blind spots caused by shelves 12, the type and installation location of sensors such as the surveillance cameras 2A to be placed so as to eliminate the blind spots is output as candidates. The types of sensors that can be used for infrastructure sensor support and their use are stored in the automatic driving control function database DB.

The ODD adjustment unit 8 in FIG. 1 has a function of adjusting and determining the ODD items D3 of the automated guided vehicles 11 in the service to be provided and the automated driving control function data D2 of the automated driving control function installed in the automated guided vehicles 11, based on the ODD items D3 from the driving environment characteristics extraction unit 7a and the automated driving control function data D2 from the automated driving control function database DB. The adjustment is made so as to improve the customer KPI evaluation value from the KPI evaluation unit 9, which will be described later.

The adjustment method is, for example, based on the process shown in traceability tables 23a and 23b, which show the relationship between the automatic driving control function data D2, ODD item D3, and KPI values D26 and D27 shown in Figure 5.

Traceability table 23a lists multiple autonomous driving control functions ( IDs 1, 2, 3) referenced from the autonomous driving control function database DB on the vertical axis, and lists the ID (D21) of the autonomous driving control function data D2, function name D22, and KPI values D26, D27 on the horizontal axis. The KPI values for each autonomous driving control function, D27, are the KPI values that will arise from installing that function. For example, KPI1 in D26 is the cost of installing the function (k yen), and KPI2 in D27 is the impact on power consumption and service operation time (h), etc.

In the illustrated example, whether the ID (D21) of the autonomous driving control function data D2 is 1, 2, or 3, the impact KPI2 on power consumption and service operation time (h) is 0, and the impact KPI on the cost of installing the function (k￥) is -4, -3, or -8.

Traceability table 23a also shows a list of ODD items D3 ( ODD items 1, 2, 3) for multiple automatic driving control functions ( IDs 1, 2, 3) on the horizontal axis, and shows the correspondence between the ODD items and the automatic driving control functions on the vertical axis, depending on whether or not there is an ODD item and what the numerical value influences. This example shows a case where ODD items 1 and 3 are applied to automatic driving control functions 1 and 2, and ODD item 2 is applied to automatic driving control function 3.

The traceability table 23a also includes, for odd item D3, KPI values (customer KPI evaluation values 13) that will arise as a result of changing odd item D3. In this example, the KPI impact on the cost of installing the function (k￥) after changing odd item D3 is 0 for all odd items 1, 2, and 3, meaning that there will be no increase in cost due to the change. In contrast, the KPI impact 2 on power consumption and service operating time (h) after changing odd item D3 is +12, +4, and +12 for odd items 1, 2, and 3, respectively.

According to the KPI value (customer KPI evaluation value 13) after applying the ODD items in traceability table 23a in Figure 5, the improvement effect of ODD item 2 is not so great, but the improvement effects of ODD items 1 and 3 are significant. Finally, based on this evaluation result, traceability table 23b shows that the application of ODD item 2 to autonomous driving control function 2 has been excluded. The new applied KPI value at this time is shown as customer KPI evaluation value 17.

The KPIs for each item in the traceability table 23a are set by transmitting the KPIs set in the customer information input unit 6 to the ODD adjustment unit 8 via the KPI evaluation unit 9 and the automatic driving control function database DB.

Flowchart 24 in FIG. 6 shows an example of a process performed by the ODD adjustment unit 8, the automatic driving control system evaluation unit 5, and the KPI evaluation unit 9 to determine a combination of ODD items and automatic driving control functions to improve the customer KPI evaluation value.

Flowchart 24 consists of steps S100 to S107, with steps S100, S101, S102, S105, S106, and S107 being processed by ODD adjustment unit 8. Step S103 is a process within the automated driving control system evaluation unit 5, and step S104 is a process within the KPI evaluation unit 9.

This series of processes starts from step S100, and in step S101, a temporary storage variable Ep of the KPI evaluation value is initialized to 0. In step S102, the combination of the automatic driving control function and the ODD item on the vertical and horizontal axes of the traceability table 23 is changed. In step S103, the ODD item D3 and the automatic driving control function D2 selected by the automatic driving control system evaluation unit 5 are evaluated. In step S104, the KPI evaluation unit 9 calculates a customer KPI evaluation value from the evaluation result of the automatic driving control system evaluation unit 5 and assigns it to the variable E. An example of the formula for calculating the customer KPI evaluation value E is as follows:
[Equation 1]
E = Σwi · Ki (i ∈ 1 ... L) (1)
Here, Ki is each KPI value, and wi is a weight for each KPI calculated by the customer information input unit 6 based on the information entered by the customer in the customer information input unit 6, and is set based on the importance or priority of the customer, for example. The weight wi may also be used as a parameter for normalizing KPI values having different units. L is the number of KPIs.

In step S105, it is determined whether the customer KPI evaluation value has improved and converged sufficiently, and if the condition is true, it is determined that the customer KPI has been improved to the maximum extent, and the combination of ODD item D3 and automatic driving control function D2 at that time is output, and the process ends in step S108. If the conditional expression in step S105 is false, the process proceeds to step S107, the calculated customer KPI evaluation value E is substituted for the temporary saved variable Ep, and the process returns to step S102, and a combination that will improve the customer KPI evaluation value D2 is searched for again.

In the above explanation, the combination of both ODD item D2 and automatic driving control function D3 is adjusted, but the customer KPI evaluation value E may be improved by changing only ODD item D2.

Returning to FIG. 1, the flow of FIG. 6 will be described in more detail. The automatic driving control system evaluation unit 5 shown in FIG. 1 includes an operation scenario generation unit 5b, which automatically creates a test scenario for evaluation by the operation evaluation unit 5a based on the ODD item D2 received from the ODD adjustment unit 8, and transmits the test scenario to the operation evaluation unit 5a.

For example, the number of vehicles in operation in the test scenario is set according to the number of ODD vehicles in operation. In addition, in the case of an ODD defined as a situation in which a worker may be present in the automated transport service provision area 15, the test scenario describes and evaluates whether the automated transport vehicle 11 can be safely controlled when the worker is walking in various locations.

The KPI evaluation unit 9 collects the results of the operation evaluation unit 5a, calculates each KPI value, and calculates the customer KPI evaluation value E using, for example, formula (1). Furthermore, if the ODD adjustment unit 8 determines that the customer KPI evaluation value E has been sufficiently improved, the KPI evaluation unit 9 outputs the ODD, the automatic driving control function, and the customer KPI evaluation value as the calculation results of the design support system 1.

The ODD, autonomous driving control function, and customer KPI evaluation value finally obtained in this way are shown in traceability table 23b in Figure 5, which presents another case as the final proposal, excluding the application of ODD item 2 to autonomous driving control function 2.

The effects of the present invention employing the above series of processes will now be described. As a specific example of the effects, it is assumed here that an automated transport vehicle 11 is newly introduced to the work site shown in FIG. 2, and an automated cargo transport service is provided within the automated transport area 10. In this assumed example, since it is unclear whether the environmental conditions in the automated transport area 10 are sufficient to satisfy the driving performance of the automated transport vehicle 11, there is a problem that the introduction requires labor and costs increase. Furthermore, even if an automated cargo transport service is introduced at such an introduction cost, it is unclear whether the performance will meet the KPI values desired by the customer until it is introduced and operational, and adjustments to improve the KPI values also incur costs.

However, in this embodiment, by using the design support system 1 shown in FIG. 1, it is possible to determine whether the environmental conditions of the automated transport area 10 are sufficient to satisfy the driving performance of the automated transport vehicle 11 before the automated transport vehicle 11 is introduced into the automated transport area 10, and it is also possible to estimate the performance of the automated cargo transport service that maximizes the KPI values required by the customer, thereby reducing the labor and costs that would have been incurred in adjustments after introduction.

In the design support system 1, the customer first inputs KPIs and services they wish to introduce into the customer information input unit 6, and the area environment data generation unit 3 collects and analyzes environmental information in advance. Based on that environmental information, the ODD automatic definition unit 7 can automatically define the ODD. The performance satisfaction relationship between the ODD defined in the ODD adjustment unit 8 and the functions that can be installed on the automated guided vehicle 11 stored in the automatic driving control function database DB is evaluated, and based on the customer KPI evaluation value estimated through the automatic driving control system evaluation unit 5 and the KPI evaluation unit 9, a combination of the ODD and automatic driving control function that maximizes the satisfaction of the customer KPI evaluation value can be automatically designed.

An example of calculating a combination that improves the customer KPI evaluation value is shown using the traceability tables 23a and 23b in Figure 5. Three types of automatic driving control functions (ID: 1, 2, 3) are listed on the vertical axis of traceability table 23a. For each automatic driving control function, the KPI values for the KPIs indicated by the customer, namely installation cost (KPI1) and service provision time (KPI2), are set. On the horizontal axis, ODD items 1 to 3 and KPI values determined by whether or not each ODD item is taken into consideration are set. The orthogonal table of the vertical and horizontal axes shows the correspondence. In formula (1), if the customer KPI evaluation value of traceability table 23a is calculated with all weights set to 1, the value becomes 13.

By improving the customer KPI evaluation value according to the flowchart 24 in FIG. 6 based on this customer KPI evaluation value, a combination like that shown in traceability table 23b can be calculated. In traceability table 23b, attention is focused on ODD item 2 as an example. When comparing the KPI2 value related to ODD item 2 with the KPI1 value of the automatic driving control function CCC required to deal with ODD item 2, it can be seen that the value for improving the customer KPI evaluation value is negative.

Therefore, according to the flowchart 24 in FIG. 6, as in the traceability table 23b in FIG. 5, an automated cargo transport service that does not consider ODD item 2 is provided by not equipping the automated transport vehicle 11 with an automated driving control function CCC. This reduces the service provision time for KPI 2, but when the customer KPI evaluation value in the traceability table 23b is calculated by setting all weights to 1 in equation (1), the result is 17, which is an improved value compared to the traceability table 23a.

In this way, by launching an automated cargo transport service based on a combination of ODD and automated driving control functions, which are the output of the design support system 1, the customer can minimize the post-implementation adjustments that have previously occurred, and can quickly launch a service that meets the customer's KPIs to the greatest extent possible. For example, if the KPI is cost, a design solution can be obtained before actual operation that alleviates ODD by excluding pedestrians within the automated transport area 10 from the area using rules, while minimizing the need for additional function development and performance improvements to the automated driving control function.

As a processing result of the design support system 1 shown in FIG. 1, various improvement information related to area environment improvement is presented from the design support system 1. Of these, the improvement information provided by the KPI evaluation unit 9 is improvement information D4 related to the autonomous driving control function, improvement information D5 related to the ODD, and customer KPI (D6), and the improvement information provided by the autonomous driving control system evaluation unit 5 is infrastructure sensor information D7 related to sensor placement and sensor type.

FIG. 7 is a diagram showing an example of how the output of the design support system 1 is used. The improvement information D4 relating to the autonomous driving control function in the upper part of FIG. 7 is provided directly to the autonomous vehicle 11, or indirectly to the autonomous vehicle 11 via the control system 30.

The autonomous driving control function D4 includes control software and the sensor specifications required for it, and the autonomous driving control function D4 from the design support system 1 is newly installed in the autonomous driving vehicle 11. The control software is implemented in the calculation device 11a (controller, etc.) of the autonomous driving vehicle 11, and the sensor 11b is installed in the autonomous driving vehicle 11 according to the sensor specifications.

In response to this, the calculation device 11a of the autonomous vehicle 11 calculates a control command value for controlling the autonomous driving of the vehicle, sends the control command value to the control device 11a, and transmits a control signal to the actuator (not shown) of the vehicle (tire rotation speed and steering angle).

In the case of indirect use via the control system 30, the calculation device 31 and the control device 11a may be provided in separate devices. For example, the calculation device 31 may be provided in the control system 30, which is a device provided in a location separate from the autonomous vehicle 11. The control system 30 and the autonomous vehicle 11 can exchange signals via wireless communication, etc.

In this case, the control software for the autonomous driving control function D4 is implemented in the arithmetic device 31 of the management system 30, and a sensor is installed in the autonomous driving vehicle 11 based on the sensor specifications. A control command value for autonomous driving control calculated by the arithmetic device 31 of the management system 30 is transmitted to the autonomous driving vehicle 11 via wireless communication, and the control device 11a of the autonomous driving vehicle 11 transmits a control signal for driving the actuator of the host vehicle based on the control command value to the actuator. The sensor signal is transmitted to the arithmetic device 31 of the management system 30 via wireless communication and is used in the calculation of the autonomous driving control.

The second row from the top of Figure 7 shows an example of how improvement information D5 related to the ODD is used, in which the information is provided directly to the autonomous vehicle 11, or indirectly to the autonomous vehicle 11 via the control system 30.

In the case of indirect use, the ODD-related improvement information D5 is used by the control system 30, and the ODD deviation determination unit 32 provided in the control system 30 determines whether the environment (service provision area) in which the autonomous vehicle 11 is traveling satisfies the driving environment conditions defined in the ODD-related improvement information D5, based on the ODD-related improvement information D5 and various environmental information.

The control system 30 can exchange signals with the control device 11a of the autonomous vehicle 11 via wireless communication, and the ODD deviation determination unit 32 does not send any signal to the control device when the driving conditions are met, but sends an ODD deviation signal to the control device 11a of the autonomous vehicle 11 when the driving conditions are not met (when the vehicle deviates from the ODD).

When the control device 11a of the autonomous vehicle 11 receives the ODD deviation signal, it notifies the driver who is present to cancel the autonomous driving state that it will switch to manual driving, or it transitions from the autonomous driving state to an emergency stop state, generates a control signal to automatically and safely stop the vehicle, and sends it to the actuator. The ODD deviation determination unit may also be installed in the autonomous vehicle. The various environmental information includes weather, time, GNSS radio wave conditions, road shape and condition, and the presence or absence of unintended pedestrians.

The third row from the top of Figure 7 shows an example of using the customer KPI (D6). The customer KPI evaluation D6 (e.g., numerical evaluation result) is used to notify the customer of the customer KPI evaluation result via the display device 40. If the customer accepts the evaluation result notified on the display device, the customer issues an instruction to start downstream processes such as the automatic excavation control function, ODD, and infrastructure sensor. If the customer does not accept the evaluation result, the customer request in Figure 1 is changed and the design support system 1 is executed again.

The third row from the top of Figure 7 shows an example of how infrastructure sensor information D7 is used. Based on the infrastructure sensor information D7, a design firm or the like performs detailed design 50 (designing the pillars on which the sensors are attached, etc.) for installing infrastructure sensors in the service provision area, which is the subsequent process, and creates detailed drawings 51. After that, a construction firm installs 52 the infrastructure sensors in the service provision area based on the detailed drawings 51.

In the first embodiment, the ODD conditions are set according to the customer's wishes, but this may be a proposal to change the service conditions. Also, if the ODD is exceeded during implementation, it is advisable to stop the vehicle or stop automatic driving and hand over driving authority to the driver.

According to the present invention described above, it is possible to provide a design support system that can automatically design the ODD, which is an operational design area adjusted to balance maximizing the business owner's key performance indicators and ensuring reliability. This makes it possible to provide an automated driving service that improves the business owner's key performance indicators.

In Example 2, the service provision location is assumed to be as shown in FIG. 8. At a work site 25 as shown in FIG. 8, a shovel 27 excavates soil 26 every day, and the soil is loaded onto a dump truck 28 for transport, so that environmental information changes frequently. When shovels 27 and dump trucks 28 are automated, design support system 1 supports design before implementation as a service related to automated driving, but it is desirable to redefine the ODD to accommodate environmental changes after operation begins, and to maintain or improve the customer KPI evaluation value.

In order to solve the above problems, differences from the first embodiment and the configuration will be described with reference to Figures 1, 8, and 9. First, in the second embodiment, an environmental change detection unit 3d is newly provided within the area data collection unit 3a in Figure 1. The environmental change detection unit 3d means that when a change occurs in the environment of the area in which the service is provided, the area data collection unit 3a collects data again, the area digital map generation unit 3b generates a digital map again, and the design support system 1 is provided with a function of re-executing a series of processes.

According to this, when an automatically operated shovel 27 digs up soil 26 at work site 25 in FIG. 8, soil 26 disappears in area 29 in FIG. 9, resulting in an area where there is residual soil on the road surface. As a result, the road surface in area 29 may be more uneven than other areas. By redefining the state where such an uneven road surface exists within an area providing an autonomous driving service as ODD, it is possible to consider whether an autonomous dump truck 28 can normally travel through area 29, and it is necessary to quickly verify whether the functionality of dump truck 28 needs to be improved in order for the dump truck 28 to travel, or whether area 29 should be leveled to the same level as other areas to alleviate ODD.

For example, when the environmental change detection unit 3d of the design support system 1 detects a change in the area 29 at the work site 25 based on the environmental information D2 from the environmental measurement device 2 mounted on the dump truck 28, the area environmental data generation unit 3, the ODD automatic definition unit 7, the ODD adjustment unit 8, the automatic driving control system evaluation unit 5, and the KPI evaluation unit 9 are executed again to redesign and output the ODD and automatic driving control function that maintains or improves the customer KPI evaluation value.

This allows design policies to be developed in response to daily changes in the environment, such as leveling area 29 to the same level as other areas to mitigate ODD, and customer KPIs such as costs can be maintained at a level that satisfies them.

In Example 3, the location where the service is provided is assumed to be as shown in FIG. 10. In a general public road environment 30 as shown in FIG. 10, an autonomous vehicle 31 must travel in accordance with various traffic rules, including traffic lights 32. The traffic rules are defined as ODDs, just like the driving environment, and the autonomous vehicle 31 must be equipped with an autonomous driving control function that satisfies the ODDs provided in the general public road environment 30.

In order to run an autonomous vehicle 31 in such a general public road environment 30, it is necessary to deal with not only a wide variety of traffic rules, but also many ODD items such as weather and pedestrians, and therefore the number of autonomous driving control functions to be installed increases. When considering the autonomous driving control functions to be installed in an autonomous vehicle 31, design considerations are required, such as whether to develop a new one or adopt an autonomous driving control function that has already been developed. However, in the design support system 1 of the first embodiment, only functions registered in the autonomous driving control function database DB can be considered, so when providing an autonomous vehicle 31 for a general public road environment 30 where there is no design experience, the design support system 1 does not output an appropriate design, and there is a problem that a design solution that satisfies the customer's KPIs cannot be obtained.

In order to solve the above problem, the differences and configuration from the first embodiment will be explained with reference to FIG. 1. In the third embodiment, the KPI evaluation unit 9 in FIG. 1 of the first embodiment has a function of adding an automatic driving control program with modified function specifications or an automatic driving control program with a newly added function to the automatic driving control function database DB.

The general public road environment 30 in FIG. 10 includes traffic lights 32, and is therefore defined as an environment with traffic lights in the ODD. Therefore, the self-driving car 31 is required to have the functionality to recognize the signs of the traffic lights 32.

Recognizing traffic light 32 signs using an onboard camera of an autonomous vehicle 31 may be a costly feature depending on other ODD items such as weather and lighting. Therefore, an environment for recognition support using infrastructure equipment 33 is created, and an ODD that can use infrastructure support is provided.

When ODD item 4 shown in the traceability table 34 in FIG. 11 is an ODD indicating infrastructure support capable of information sharing with the traffic light 32, it is necessary to install the autonomous driving control function DDD35 corresponding to the ODD item 4 in the autonomous driving automobile 31. At this time, the traceability table 34 in FIG. 11 is assumed to be a design solution as a result of improving the customer KPI evaluation value according to the flowchart 24 in FIG. 6. If the autonomous driving control function DDD35 is a newly added function, the KPI evaluation unit 9 in FIG. 1 registers the autonomous driving control function DDD35 in the autonomous driving control function database DB. As a result, when using the design support system 1 to provide another autonomous driving service in an environment similar to the general public road environment 30, it becomes possible to select the use of the autonomous driving control function DDD35, so that a design solution that satisfies the customer KPI can be quickly obtained from the design support system 1 that provides the autonomous driving automobile 31 without incurring new function development costs.

In the above embodiments, the present invention has been described as being applied to automated transport vehicles, construction vehicles, and autonomous automobiles, but the present invention can also be applied to other autonomous vehicles, such as agricultural vehicles and autonomous work robots.

In Example 4, the program of the design support system will be explained. The program of the design support system is stored in the ROM of the computer device, and some of these programs execute the processes of the ODD adjustment unit 8, the automatic driving control system evaluation unit 5, and the KPI evaluation unit 9 shown in Figure 6. As for the other programs, although not shown, it is preferable to configure the programs in units of the calculation functions of each unit in Figure 1.

For example, it would be good to create a program that treats the area environment data generation unit 3 as a single unit, and to realize the functions of the area data collection unit 3a, area digital map generation unit 3b, and service provision area identification unit 3c as subprograms within this program. This concept should also be applied to the calculation functions of the other units.

Specifically, for example, it is preferable to provide an automatic driving control function program, which is a program for controlling automatic driving of vehicles traveling in a service provision area; an area environmental data generation program having an area digital map generation unit that uses environmental data to generate a digital map of the service provision area; an automatic driving ODD definition program that generates and outputs an operation design area that is an environmental constraint condition for operating an automatic driving service from digital map information; an ODD adjustment program that evaluates the satisfaction of the automatic driving control function specifications stored in the automatic driving control program in pairs for the operation design area and changes the operation design area based on the evaluation results; an automatic driving control system evaluation program that evaluates the operation design area based on customer requirements; and a KPI evaluation program that generates a customer requirement evaluation formula that evaluates the customer's key performance indicators based on the customer requirements, calculates the customer requirement evaluation formula based on the values output from the automatic driving control system evaluation program, and outputs the operation design area and the customer's key performance indicators.

1: Design support system 2: Environmental measurement device 3: Area environmental data generation unit 3a: Area data collection unit 3b: Area digital map generation unit 3c: Service provision area identification unit 3d: Environmental change detection unit 4: Automatic driving control function database 5: Automatic driving control system evaluation unit 5a: Operation evaluation unit 5b: Operation scenario generation unit 6: Customer information input unit 7: ODD automatic definition unit 8: ODD adjustment unit 9: KPI evaluation unit 10: Automatic transport area 11: Automatic transport vehicle 12: Shelf 13: Outline Line 15: Automated transport service provision area 16: Cargo storage area 17: Forklift 18: Truck 19: Site reference coordinates 20: Passage width 21: Wi-Fi antenna 22: Surveillance camera 23a, 23b: Traceability table 24: Flowchart 25: Work site 26: Soil and sand 27: Shovel 28: Dump truck 29: Area 30: General public road environment 31: Automated driving car 32: Traffic light 33: Infrastructure equipment 34: Traceability table 35: Automated driving control function DDD
S100 to S108: Step

Claims (12)

1. A design support system that receives environmental data from an environmental measurement device that measures the environment of a service provision area managed by a customer and customer requirements and outputs an improvement value of a customer's key performance indicator,
   an automatic driving control function database storing an automatic driving control program for automatically controlling the driving of a vehicle traveling in the service provision area;
   an area environmental data generating unit including an area digital map generating unit that generates a digital map of the service provision area using the environmental data;
   An automatic definition unit for automatic driving ODD that generates and outputs a driving design area that is an environmental constraint condition for operating an automatic driving service from the information of the digital map;
   An ODD adjustment unit that evaluates the fulfillment of the automatic driving control function specifications stored in the automatic driving control program in pairs for the operation design domain output from the automatic driving ODD automatic definition unit and changes the operation design domain based on the evaluation result;
   an automatic driving control system evaluation unit that evaluates the operation design domain based on the customer requirements;
   a KPI evaluation unit that generates a customer requirement evaluation formula for evaluating a customer's key performance indicator based on the customer requirement, calculates the customer requirement evaluation formula based on a value output from the automatic driving control system evaluation unit, and outputs the operation design domain and the customer's key performance indicator;
   The ODD adjustment unit makes a change to the operation design domain so as to improve the value of the customer request evaluation formula based on the value of the customer request evaluation formula calculated and output by the KPI evaluation unit,
   A design support system characterized in that the KPI evaluation unit outputs an improvement value of a customer's key performance indicator based on the changed operation design area.
2. 2. The design support system according to claim 1,
   A design support system characterized in that the autonomous driving ODD automatic definition unit generates and outputs an autonomous driving control function of the vehicle, the autonomous driving control system evaluation unit evaluates the autonomous driving control function of the vehicle based on the customer requirements, and the KPI evaluation unit outputs the autonomous driving control function and a customer's key performance indicators.
3. 2. The design support system according to claim 1,
   A design support system characterized in that the autonomous driving control system evaluation unit presents environmental improvements in the service provision area.
4. 2. The design support system according to claim 1,
   The ODD adjustment unit modifies the operation design area and the automatic driving control program based on the value of the customer request evaluation formula calculated and output by the KPI evaluation unit so as to improve the value of the customer request evaluation formula from the previous value,
   A design support system characterized in that the KPI evaluation unit outputs improvement values of the customer's key performance indicators based on the changed operation design area and the automatic driving control program.
5. 2. The design support system according to claim 1,
   A design support system characterized in that the autonomous driving control system evaluation unit uses the autonomous driving control program stored in the autonomous driving control function database and the generated digital map to perform autonomous driving in a virtual environment based on the operation design domain, the autonomous driving control program, and the digital map to evaluate the autonomous driving control system and the operation design domain.
6. 2. The design support system according to claim 1,
   A design support system characterized in that the automatic driving control system evaluation unit includes an operation scenario generation unit that generates an operation scenario to be evaluated from the operation design domain output from the ODD adjustment unit.
7. 2. The design support system according to claim 1,
   A design support system characterized in that the autonomous driving ODD automatic definition unit is provided with an operating environment change unit that outputs design information for at least one infrastructure sensor that is installed in the environment to collect environmental information from the digital map information and the autonomous driving control program.
8. The design support system according to claim 7,
   The design support system is characterized by comprising an infrastructure sensor system that aggregates information collected by all of the infrastructure sensors and shares the information with the vehicle.
9. 2. The design support system according to claim 1,
   said area environmental data generation unit collects data again when a change occurs in the environment of the area in which the service is provided, said area digital map generation unit generates a new digital map, and said design support system further comprises an environmental change detection unit which re-executes a series of processes.
10. 2. The design support system according to claim 1,
    A design support system characterized in that the KPI evaluation unit has a function of adding the modified autonomous driving control program to the autonomous driving control function database.
11. A design support method for obtaining environmental data from an environmental measurement device that measures the environment of a service provision area managed by a customer and customer requirements, and outputting an improvement value of a key performance indicator of the customer using a computer device, comprising:
    an automatic driving control function database storing an automatic driving control program for automatically controlling the driving of a vehicle traveling in the service provision area;
    The calculation unit of the computer device uses the environmental data to generate a digital map of the service provision area, generates an operation design domain that is an environmental constraint condition for operating an autonomous driving service from information on the digital map, evaluates the satisfaction of the autonomous driving control function specifications stored in the autonomous driving control program in pairs for the operation design domain, changes the operation design domain based on the evaluation results, evaluates the operation design domain based on the customer requirements, generates a customer requirement evaluation formula that evaluates key performance indicators of the customer based on the customer requirements, calculates the customer requirement evaluation formula based on the evaluation value of the autonomous driving control system, obtains the operation design domain and the customer's key performance indicators, and
    A design support method characterized by modifying the operation design area based on the value of the customer requirement evaluation formula so as to improve the value of the customer requirement evaluation formula from a previous value, and obtaining an improved value of the customer's key performance indicator based on the modified operation design area.
12. A design support program for obtaining environmental data from an environmental measurement device that measures the environment of a service provision area managed by a customer and customer requirements, and outputting an improvement value of a customer's key performance indicators,
    An automatic driving control function program which is an automatic driving control program for automatically controlling the driving of a vehicle traveling in the service provision area;
    an area environmental data generating program including an area digital map generating unit that generates a digital map of the service provision area using the environmental data;
    An automatic definition program for an autonomous driving ODD that generates and outputs a driving design area that is an environmental constraint condition for operating an autonomous driving service from the information of the digital map;
    An ODD adjustment program that evaluates the fulfillment of the automatic driving control function specifications stored in the automatic driving control program in pairs for the operation design domain and changes the operation design domain based on the evaluation result;
    an automatic driving control system evaluation program for evaluating the operation design domain based on the customer requirements;
    a KPI evaluation program that generates a customer requirement evaluation formula for evaluating a customer's key performance indicator based on the customer requirement, calculates the customer requirement evaluation formula based on a value output from the automatic driving control system evaluation program, and outputs the operation design domain and the customer's key performance indicator;
    The ODD adjustment program modifies the operation design domain so as to improve the value of the customer requirement evaluation formula based on the value of the customer requirement evaluation formula calculated and output by the KPI evaluation program,
    The KPI evaluation program is a design support program characterized by outputting an improvement value of a customer's key performance indicator based on the changed operation design area.

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