TWI745879B - Automatic driving system and automatic driving method - Google Patents

Abstract

An automatic driving method for an automatic driving system disposed on a vehicle is provided. The method includes: obtaining a positioning information and moving information of the vehicle; generating, according to the positioning information, an environment information corresponding to a real world outside the vehicle, a digital map and a target location, a navigation plan; identifying, according to the positioning information, a current path node corresponding to the vehicle in a current scheduled path of the navigation plan, and a monitoring path among the current scheduled path; selecting a target driving parameter group among a plurality of driving parameter group according to a maximum velocity variation absolute value corresponding to the monitoring path of the navigation plan, so as to apply the target driving parameter group to control a movement of the vehicle.

Description

Autopilot system and autopilot method

The present invention relates to a vehicle control method, and in particular to an automatic driving system configured on the vehicle and an automatic driving method used by the automatic driving system.

With the advancement of technology, in order to avoid traffic accidents caused by human negligence and improve the efficiency of the vehicles themselves. Autonomous driving technology has gradually become a trend. In general automatic driving, the control force is adjusted according to the current position error and speed error to correct the movement of the vehicle. However, in some cases, the excessive control force generated in order to correct the error may cause discomfort to the occupant.

Based on this, in the process of automatic driving, how to achieve a balance between the strength of the control force and the ride comfort along with the road conditions is the goal of the people in the field.

The present invention provides an automatic driving system and an automatic driving method used by the automatic driving system, which can dynamically select a corresponding driving parameter group according to changes in a planned path, so as to apply the selected driving parameter group to control a vehicle Mobile.

An embodiment of the present invention provides an automatic driving system configured on a vehicle, which is suitable for performing automatic driving operations on the vehicle. The system includes a driving unit, a positioning system, an inertial navigation system, and a processor. The driving unit is used to control the movement of the vehicle. The positioning system is used to obtain positioning information of the vehicle. The inertial navigation system is used to obtain movement information of the vehicle. The processor is electrically connected to the driving system, the positioning system, and the inertial navigation system. Wherein in the automatic driving operation, the processor is used to generate a navigation plan based on the positioning information, an environmental information corresponding to the real world outside the vehicle, a digital map, and a target location, and the processing The device is used to identify the current path point corresponding to the vehicle in the current planning path of the navigation plan and a monitoring path in the current planning path according to the positioning information, and the processor is used to identify the current path point in the current planning path according to the navigation plan. In the picture, a target driving parameter group is selected from a plurality of driving parameter groups corresponding to the absolute value of a maximum speed change in the monitoring path, so as to instruct the driving system to apply the target driving parameter group to control all of the vehicle.述动。 Said mobile.

An embodiment of the present invention provides an automatic driving method applicable to an automatic driving system configured on a vehicle. The method includes: obtaining positioning information and movement information of the vehicle; generating a navigation plan based on the positioning information, an environmental information corresponding to the real world outside the vehicle, a digital map, and a target location; The positioning information identifies the current path point corresponding to the vehicle in the current planning path of the navigation plan and a monitoring path in the current planning path; according to the monitoring path corresponding to the monitoring path in the navigation plan A maximum speed change absolute value is used to select a target driving parameter group from a plurality of driving parameter groups, so as to apply the target driving parameter group to control the movement of the vehicle.

In an embodiment of the present invention, the navigation path includes the current planning path and multiple planning speeds respectively corresponding to multiple path points in the current planning path.

In an embodiment of the present invention, the monitoring path is a part of the future path that the vehicle intends to enter in the current planned path, and the part of the future path is the vehicle in the future path. The path to be moved during a monitoring period after the current time point.

In an embodiment of the present invention, the method further includes: identifying the current speed of the vehicle according to the movement information; and determining the length of the monitoring period according to the current speed, wherein all of the monitoring period The length is proportional to the current speed.

In an embodiment of the present invention, the driving parameter group of the target driving parameter group is selected from the plurality of driving parameter groups according to the absolute value of the maximum speed change corresponding to the monitoring path in the navigation plan. The steps include: further selecting the target driving parameter set from the plurality of driving parameter sets according to the environmental information, wherein the environmental information includes at least one or more of the following information: the ground on which the vehicle is currently traveling The coefficient of friction; the slope of the ground on which the vehicle is currently traveling; and the external force experienced by the vehicle.

In an embodiment of the present invention, each of the plurality of driving parameter groups includes at least: a position error weight value; a speed error weight plant; an acceleration output weight value; and an acceleration change amplitude weight value.

Based on the foregoing, the automatic driving system and the automatic driving method provided by the embodiments of the present invention can identify the current path point of the corresponding vehicle in the current planning path of the generated navigation plan and the monitoring path in the current planning path, A target driving parameter group is selected from a plurality of driving parameter groups according to the absolute value of the maximum speed change corresponding to the monitoring path, so as to apply the target driving parameter group to control the movement of the vehicle, so that the A balance is achieved between the strength of the control force of the vehicle and the ride comfort, thereby enhancing the autopilot efficiency of the vehicle and the passenger's riding experience.

FIG. 1 is a block diagram of a vehicle and an automatic driving system according to an embodiment of the present invention. 1, specifically, the automatic driving system 11 configured in the vehicle 10 includes a processor 110, and a positioning system 120 coupled (electrically connected) to the processor 110, an inertial navigation system 130, and input/output The unit 140, the communication circuit unit 150, the storage device 160, the main memory 170, and the driving unit 180.

The processor 110 is a hardware with computing capabilities (such as a chipset, a processor, etc.), which is used to manage the overall operation of the vehicle 10 and the automatic driving system 11 (eg, control the operation of other hardware components in the vehicle 10). In this embodiment, the processor 110 is, for example, a core or multi-core central processing unit (CPU), a microprocessor (micro-processor), or other programmable processing unit (Programmable Processing Unit). ), Digital Signal Processor (DSP), Programmable Controller, Application Specific Integrated Circuits (ASIC), Programmable Logic Device (PLD) or other similar devices .

The positioning system 120 includes a signal for receiving a signal (GPS signal) from a global positioning system to calculate the current world coordinates of the vehicle 10 based on the received GPS signal.

The inertial navigation system 130 is an auxiliary navigation system that uses an accelerometer and a gyroscope to measure the acceleration and angular velocity of an object (for example, the vehicle 10), and continuously calculates the position, attitude, and velocity of the moving object. That is, the inertial navigation system 130 does not require an external reference frame and can provide movement information (eg, speed, acceleration, angular velocity, attitude) about the vehicle 10. In this embodiment, the positioning system 120 (or the processor 110) can provide the inertial navigation system 130 with initial positioning information and speed of the vehicle 10, so that the inertial navigation system 130 can pass through the motion sensors (such as accelerometers and gyroscopes). The information of the vehicle 10 is integrated and calculated, and the current position, attitude, azimuth angle, speed, and angular velocity are continuously updated to obtain the movement information of the vehicle 10. The updated current position and speed can also be integrated into auxiliary positioning information and sent back to the positioning system 120. The positioning system 120 can correct the current positioning information based on the received auxiliary positioning information to enhance the accuracy of the positioning information sent to the processor 110. In addition, the corrected positioning information can also be sent back to the inertial navigation system 130 to correct errors caused by the inertial navigation system 130 continuously calculating the auxiliary positioning information, thereby improving the accuracy of the auxiliary positioning information. In other words, after the positioning system 120 and the inertial navigation system 130 are integrated, the processor 110 can accurately obtain the current world coordinates of the vehicle 10.

The input/output unit 140 is, for example, a touch screen (or a device that integrates input devices such as a screen and a touchpad), which is used to allow the user to input data or to control what the user wants to perform through the input/output unit 140 operate. In addition, the input/output unit 140 can also display/play information (for example, audio/video/text information related to the navigation plan). In this embodiment, the user/passenger can also perform input operations/input commands on the input/output unit 140 to set other detailed information related to the navigation plan, such as destination, comfort level, or instruct the automatic driving system to generate navigation plan. Various forms of information content related to the digital map of the navigation plan can be displayed/played through the input/output unit 140. In an embodiment, the input/output unit 140 may also include a speaker and a microphone.

The communication circuit unit 150 is used for receiving communication signals via a wireless method. In this embodiment, the communication circuit unit 150 supports, for example, WiFi communication protocol, Bluetooth, Near Field Communication (NFC), and 3rd Generation Partnership Project (3GPP) standards. , The fourth generation communication system partner project (4th Generation Partnership Project; 4GPP) standard, the fifth generation communication system partner project (5th Generation Partnership Project; 5GPP) standard and other wireless communication circuit units. In this embodiment, the communication circuit unit 150 can be connected to the positioning reference device 20 (for example, via a connection C1) through wireless communication, and then obtain the positioning reference data D1 from the positioning reference device 20.

It should be noted that the external data D1 includes positioning reference data. For example, in one embodiment, the positioning system 120 may apply Real Time Kinematic (RTK) technology to calculate the world coordinates of the vehicle 10 based on the received positioning reference data D1 and GPS signals, thereby improving the obtained The accuracy of the reference world coordinates.

In one embodiment, the external data D1 further includes road condition information, environmental information, and digital maps. For example, the communication circuit unit 150 may receive external data D1 related to the navigation plan from the automatic driving management server 20 to enhance the generated navigation plan. For another example, in another embodiment, the external data D1 further includes reference information from other vehicles 20 around the vehicle 10. The reference information is, for example, motion information such as the speed, acceleration, and moving direction of the other vehicle 20. The processor 110 can adjust the current navigation plan based on the received movement information related to other vehicles 20 to improve the efficiency of the adjusted navigation plan and avoid traffic accidents caused by other vehicles.

The storage device 160 temporarily stores data through the instructions of the processor 110. The data includes system data for managing the vehicle 10, such as mobile information, positioning information, auxiliary positioning information, inertial information, environmental information, vehicle condition information, and digital maps. , Data from other electronic devices (such as external data D1), this disclosure is not limited to this. In addition, the storage device 160 can also record some data that needs to be stored for a long time through the instructions of the processor 110. For example, a map database, one or more driving parameter sets related to the automatic driving program executed by the automatic driving system 11, and firmware or software used to manage the vehicle 10. The storage device 160 may be any type of hard disk drive (HDD) or non-volatile memory storage device (eg, solid state drive). In an embodiment, the storage device 160 may also be, for example, hardware including a flash memory module. In one embodiment, the processor 110 may access the automatic driving program in the main memory 170 and execute the accessed automatic driving program to implement the automatic driving method provided by the embodiment of the present invention.

The main memory 170 is used to receive instructions from the processor 110 to temporarily store various forms of data. The main memory 170 is, for example, any form of fixed or removable random access memory (RAM) or other similar devices, integrated circuits, and combinations thereof. Due to the high-speed access characteristics of the main memory 170, various calculations and operations performed in this embodiment can be accelerated by accessing relevant data temporarily stored in the main memory 170.

The driving unit 180 is used to control the moving direction, speed and acceleration of the vehicle 10 by controlling the mechanical system and power system of the driving unit 180, that is, the driving unit 180 is used to control the movement/movement of the vehicle 10. In an embodiment, the driving unit 180 is configured to apply a corresponding driving parameter set according to an instruction of the processor 110 to control the motion force of the vehicle 10 according to the applied driving parameter set.

Fig. 2 is a flowchart of an automatic driving method according to an embodiment of the present invention. Please refer to FIG. 2, in step S210, the processor 110 may obtain the positioning information and movement information of the vehicle through the positioning system 120 and the inertial navigation system 130.

Then, in step S220, the processor 110 may generate a navigation plan based on the positioning information, an environment information corresponding to the real world outside the vehicle, a digital map, and a target location. Specifically, the environmental information includes at least one or more of the following: (1) the friction coefficient of the ground on which the vehicle is currently traveling; (2) the slope of the ground on which the vehicle is currently traveling; (3) The external force received by the vehicle; (4) the traffic flow conditions corresponding to the planned route; (5) the speed limit corresponding to the planned route; (6) other environmental information that will affect the driving process (such as wind, temperature, humidity) , Weather, specific buildings, toll booths, etc.). In this embodiment, the friction coefficient of the ground on which the vehicle is currently traveling can be obtained by using a friction coefficient sensor or a friction force sensor. The gradient of the ground on which the vehicle is currently traveling and the external force received by the vehicle may be provided by the inertial navigation system 130. The traffic conditions corresponding to the planned route, the speed limit corresponding to the planned route, and other environmental information that may affect the driving process can be obtained through the communication circuit unit 150 from the external data D1 received from the connected server 20 or the Internet.

In this embodiment, the speed limit corresponding to the planned route and other environmental information that will affect the driving process can also be provided through a pre-stored digital map. The digital map is a digital map about the real world. The digital map can also be updated from the corresponding map server 20 via the communication circuit unit 150.

The target location is, for example, the address or world coordinates of a navigation target (including a building, a place, or a living body) corresponding to the input content (including a voice message or a text message) received through the input/output unit 140. For example, the user can give a voice command to the input/output unit 140 by speaking to set a navigation target. The processor 110 can recognize the navigation target in the voice command, and find the address or world coordinates of the navigation target from a digital map, the Internet, or other network connections, as the target location.

In addition, in an embodiment, the target position may be preset. For example, the user can pre-set the autopilot itinerary to be executed during a specific period, which contains detailed information (such as address or world coordinates) of the departure place and navigation target. The automatic driving system 11 may perform an automatic driving operation corresponding to the specific period according to the automatic driving schedule, so as to control the vehicle 10 to drive from the departure point to the navigation target.

The processor 110 may generate a navigation plan based on various collected information (such as the aforementioned environmental information, digital map, and target location). The navigation plan includes a planned route, and the planned route is used to indicate an optimized travel route between the departure point (or the current position of the vehicle 10) and the navigation target. In addition, the navigation plan sets a plurality of path points in the planned route, and a plurality of planned speeds and a plurality of movement patterns corresponding to the plurality of path points, respectively.

Fig. 3A is a schematic diagram of a planned route in a navigation plan according to an embodiment of the present invention. Please refer to FIG. 3A. For example, suppose the input/output unit 140 displays a digital map MAP1 (including roads RD1, RD2) according to the generated navigation plan, and the digital map includes information from vehicle CR1 (corresponding to vehicle 10). A planned path SP1 between the current position (corresponding to the current path point CPP(0)) and the navigation target TD1, and multiple path points PP(0)~PP(9) in the planned path SP1 and movement patterns (such as Arrows connecting the multiple path points PP(0)~PP(9)). In addition, as shown in the digital map MAP1, the vehicle CR1 is driving on the road RD1 in a straight way at the current route point CCP(0) at a planned speed of 60KM/H (as shown in the area R1 of the digital map MAP1). CR2 is driving in front of vehicle CR1 at a speed of 40 KM/H.

Fig. 3B is a schematic diagram of a navigation plan according to an embodiment of the present invention. Please refer to Figure 3B to continue the example of Figure 3A. For example, the generated navigation plan can record (as shown in Table T310) multiple waypoints PP(0)~PP(9) of the current planned path SP1. ) And multiple planned speeds V(0)-V(9) and movement patterns MP(0)-MP(9) corresponding to the multiple path points PP(0)-PP(9). The processor 110 may determine that the current waypoint (for example, CPP(0)) corresponds to the waypoint PP(0) according to the positioning information of the vehicle 10, and the driving unit 180 is instructed at the current waypoint CCP(0), using the corresponding Plan speed V(0) (such as "60" (KM/H)) and moving pattern MP(0) (such as "straight") to move.

Please return to FIG. 2. In step S230, the processor 110 identifies the current path point corresponding to the vehicle in the current planned path of a navigation plan and a monitored path in the current planned path according to the positioning information. . Specifically, as shown in FIGS. 3A and 3B, the processor 110 may recognize the monitoring path based on the current path point. In more detail, the monitored path is the future path that the vehicle intends to enter in the current planned path (for example, the corresponding path points PP(1)~PP(9) in the planned path SP1 in FIG. 3A The part of the path), wherein the part of the future path is the path that the vehicle intends to move during a monitoring period after the current time point.

In an embodiment, the monitoring path/monitoring period is related to the current speed of the vehicle 10. Specifically, the processor 110 recognizes the current speed of the vehicle according to the movement information, wherein the processor 110 determines the length of the monitoring period MR1 according to the current speed, wherein the length of the monitoring period MR1 is The length is proportional to the current speed. 3B, for example, in one embodiment, the current speed V(0) of the vehicle 10 corresponding to the current waypoint CPP(0) is “60” (KM/H), and the monitoring path MR1/monitoring period MR1 is the path/period of "6 (for example, 60/10=6)" path points PP(1)~PP(6) (also known as monitoring path points) corresponding to the current speed V(0) "60". That is, in this embodiment, for the current speed, one waypoint is added every 10KM/H as the monitoring path MR1/monitoring path point included in the monitoring period MR1. In this way, when the current speed of the vehicle 10 is higher, the processor 110 will perform monitoring on the longer monitoring path/monitoring period.

Please return to FIG. 2 again. In step S240, the processor 110 selects a maximum speed change absolute value (also known as a speed change rate) corresponding to the monitored path of the navigation plan from a plurality of driving parameter groups A target driving parameter set is selected to apply the target driving parameter set to control the movement of the vehicle.

For example, referring to FIG. 3B, in the monitoring path MR1, the processor 110 may calculate the absolute value of the speed change of every two adjacent monitoring path points, and the processor 110 may calculate the absolute value of the speed change from the plurality of calculated absolute values of the speed change. Identify the largest one and use it as the absolute value of the maximum speed change |∆V _MAX |. For example, in the example of FIG. 3B, the processor 110 may calculate the absolute value of the maximum speed change |∆V _MAX | to be "10".

Fig. 4 is a schematic diagram of a navigation plan according to another embodiment of the present invention. 4, in this embodiment, the navigation plan can also record multiple driving parameter groups PG(1)~PG(4) and used to determine the multiple driving parameter groups PG(1)~PG(4) ) Speed change range (as shown in table T410). The multiple driving parameter groups PG(1) to PG(4) each include multiple driving weight values, for example, the driving parameter group PG(1) includes multiple driving weight values W _1.1 to W _1.N ; driving parameter group PG(2) includes multiple driving weight values W _2.1 ~W _2.N ; driving parameter group PG(3) includes multiple driving weight values W _3.1 ~W _3.N ; driving parameter group PG(4) includes multiple driving The weight value is W _4.1 ~ W _4.N. The processor 110 can find the target speed change range that includes the currently recognized absolute value of the maximum speed change |∆V _MAX | and the target driving corresponding to the target speed change range according to the multiple speed change ranges. Parameter group. N is a positive integer and is used to represent the total number of driving weight values in each driving parameter group.

For example, suppose that the threshold value TH1 in the speed change range of the driving parameter group PG(1) is "0" and the threshold value TH2 is "10"; it corresponds to the threshold in the speed change range of the driving parameter group PG(2) The value TH3 is "20"; the threshold value TH4 in the speed change range of the corresponding driving parameter group PG(3) is "30". In addition, following the example in Fig. 3B, the currently recognized absolute value of the maximum speed change |∆V _MAX | is "10".

In this example, the processor 110 can recognize that the absolute value of the maximum speed change |∆V _MAX | corresponds to the target driving parameter group PG(2), and select the target driving parameter group PG(2) to instruct the driving unit 180 to apply the target driving _{The multiple driving weight values W 2.1} to W _2.N in the parameter group PG(2) are used to control the movement of the vehicle 10.

In this embodiment, the multiple driving weight values of one driving parameter group (eg, driving parameter group PG(2)) at least include: position error weight value (eg, W _2.1 ); speed error weight replanting (eg , W _2.2 ); acceleration output weight value (for example, W _2.3 ); and acceleration change amplitude weight value (for example, W _2.4 ). For example, the processor 110 may calculate the corresponding acceleration force according to the currently detected position error and the position error weight value.

The position error is, for example, a value (eg, E) obtained by subtracting the currently detected position of the vehicle 10 from the predetermined position of the vehicle 10 at the current waypoint CPP(0). If the position error is a positive value, the acceleration force calculated by the processor 110 is the product of the position error multiplied by the position error weight value. Assuming that the position error is a positive value (for example, the current position is behind a predetermined position), the driving unit 180 or the processor 110 can calculate a positive acceleration force, and the driving unit 180 can control the vehicle 10 to generate a positive acceleration force based on this acceleration force. The acceleration to make the backward current position catch up with the predetermined position.

It is worth mentioning that in this embodiment, the automatic driving system 11 (processor 110) can continuously adjust/update the navigation plan according to the obtained positioning information, movement information, and environmental information.

3C is a schematic diagram of a planned route in a navigation plan according to another embodiment of the present invention. Please refer to Figure 3C. For example, following the example of Figure 3A, suppose that the vehicle CR1 is currently traveling to the waypoint PP(1). As shown in the digital map MAP2, the vehicle CR1 is at the current waypoint CCP(1) to plan At a speed of 50KM/H (as shown in the area R2 of the digital map MAP2), the vehicle travels on the road RD1 in a straight-going manner. In addition, the vehicle CR2 is driving in front of the vehicle CR1 at a speed of 40 KM/H, and (as indicated by the arrow A31) the processor 110 of the automatic driving system 11 corresponding to the vehicle CR1 knows that the vehicle CR2 will turn to the right according to the obtained environmental information. Cut into the planned path SP1 between the path point PP (4) and the path point PP (5). In this example, the processor 110 will adjust the speed (deceleration) of the vehicle CR1 to prevent the vehicle CR1 from hitting the vehicle CR2.

FIG. 3D is a schematic diagram of a navigation plan according to another embodiment of the present invention. Please refer to Figure 3D to continue the example of Figure 3C. For example, the adjusted/updated navigation plan can record (as shown in Table T320) multiple waypoints PP(1)~PP of the current planned path SP1 (9) Multiple planned speeds V(1)~V(9) and movement patterns MP(1)~MP(9) corresponding to the multiple path points PP(1)~PP(9). The processor 110 may determine that the current waypoint (for example, CPP(1)) corresponds to the waypoint PP(1) according to the positioning information of the vehicle 10, and the driving unit 180 is instructed at the current waypoint CCP(1), using the corresponding Plan the speed V(1) (such as "50" (KM/H)) and the movement pattern MP(1) (such as "straight") to move.

It should be noted that the current monitoring path MR2 is set based on the current speed V(1) "50" (KM/H), that is, a path containing "5" path points PP(2)~PP(6) . That is, as the current speed decreases from 60KM/H in Figure 3A to 50KM/H in Figure 3C, the current monitoring path MR2 is also shortened from a path containing 6 path points PP(1)~PP(6) to 5 The path of the way point PP(2)~PP(6).

In addition, in the example of Figs. 3C and 3D, the processor 110 adjusts the planned speed V(3) of the corresponding waypoint PP(3) from “50” to “30”, and adjusts the planned speed of the corresponding waypoint PP(4) V(4) is adjusted from "40" to "10", and the planned speed V(5) of the corresponding waypoint PP(5) is adjusted from "30" to "20" to update the navigation plan.

On the other hand, in the examples of Figs. 3C and 3D, the processor 110 can calculate the absolute value of the maximum speed change |∆V _MAX | To identify the corresponding target driving parameter group PG(3), and instruct the driving unit 180 to apply the target driving parameter group PG(3) to replace the original target driving parameter group PG(2) to control the movement of the vehicle 10.

It is worth mentioning that, referring to FIG. 4, multiple driving parameter groups PG(1) to PG(4) have different magnitudes based on the corresponding multiple speed change ranges. For example, the driving parameter group PG(1) is smaller than the driving parameter group PG(2), the driving parameter group PG(2) is smaller than the driving parameter group PG(3), and the driving parameter group PG(3) is smaller than the driving parameter group PG(4). In other words, a smaller driving parameter group will contain more comfortable weak parameters (smaller driving weight values), and a larger driving parameter group will contain more agile strong parameters (larger driving weight values).

When the driving parameter group PG(1) is smaller than the driving parameter group PG(2), the first driving weight value W _1.1 in the driving parameter group PG(1) will be smaller than the first driving parameter group PG(2). A driving weight value W _2.1 .

Based on the above-mentioned embodiment, since in the example of FIGS. 3A and 3B, the driving unit 180 applies the driving parameter group PG(2), and in the examples of FIGS. 3C and 3D, the driving unit 180 applies a greater than the driving parameter group PG( 2) The driving parameter group PG(3). Therefore, in the example of Figs. 3C and 3D, the processor 110 or the driving unit 180 will apply a position error weight value W _{3.1 that is greater than the original position error weight value W 2.1} , and for the same position error, in Fig. 3C, 3D In the example, the acceleration force calculated by the processor 110 (or the driving unit 180) will be based on the new position error weight value W _3.1 , which is greater than the acceleration force in the example of FIGS. 3A and 3B.

In other words, the automatic driving system and the automatic driving method provided by the present invention can reflect that the speed change rate in the monitoring path (monitoring period) is recognized to increase (for example, the processor 110 predicts that the vehicle needs to be larger during the monitoring period). Speed changes), and switch to a larger driving parameter group to use a stronger weight value to control the vehicle 10, thereby making the overall movement of the vehicle 10 more agile (for example, the corresponding acceleration force will be greater).

On the contrary, in response to the recognition that the speed change rate in the monitoring path (monitoring period) becomes smaller (for example, the processor 110 predicts that the vehicle needs a greater speed change during the monitoring period), and switching to a smaller driving parameter group, A weaker weight value is used to control the vehicle 10, so that the overall movement of the vehicle 10 is more comfortable (for example, the corresponding acceleration force will be smaller).

In summary, the automatic driving system and automatic driving method provided by the embodiments of the present invention can identify the current path point of the corresponding vehicle in the current planned path of the generated navigation plan and the monitoring in the current planned path Path, to select a target driving parameter group from a plurality of driving parameter groups according to the absolute value of the maximum speed change corresponding to the monitoring path, so as to apply the target driving parameter group to control the movement of the vehicle, and then A balance can be achieved between the strength of the vehicle's control force and the riding comfort, thereby enhancing the vehicle's automatic driving performance and passengers' riding experience.

10: Vehicles/Vehicles 11: Autonomous Driving System GPS: Global Positioning System Signal 110: Processor 120: Positioning System 130: Inertial Navigation System 140: Input/Output Unit 150: Communication Circuit Unit 160: Storage Device 170: Main Memory 180: driving unit 20: server/other vehicles/positioning reference device D1: external data C1: connection S210, S220, S230, S240: process steps of automatic driving method R1~R2: area RD1, RD2: road CR1 CR2: Vehicle CPP(0), CPP(1): Current waypoint PP(0)～PP(9): Waypoint TD1: Destination SP1: Planned route MAP1, MAP2: Digital map T310, T320, T410: Table MR1, MR2: monitoring path/monitoring period A31: arrow TH1~TH4: threshold value PG(1)~PG(4): driving parameter group W _1.1 ~ W _4.N : driving weight value | ∆V _MAX |: maximum speed Absolute value of change

FIG. 1 is a block diagram of a vehicle and an automatic driving system according to an embodiment of the present invention. Fig. 2 is a flowchart of an automatic driving method according to an embodiment of the present invention. Fig. 3A is a schematic diagram of a planned route in a navigation plan according to an embodiment of the present invention. Fig. 3B is a schematic diagram of a navigation plan according to an embodiment of the present invention. 3C is a schematic diagram of a planned route in a navigation plan according to another embodiment of the present invention. FIG. 3D is a schematic diagram of a navigation plan according to another embodiment of the present invention. Fig. 4 is a schematic diagram of a navigation plan according to another embodiment of the present invention.

S210, S220, S230, S240: Process steps of the automatic driving method

Claims (12)

An automatic driving system is configured on a vehicle and is suitable for performing automatic driving operations on the vehicle. The system includes: a driving unit for controlling the movement of the vehicle; and a positioning system for obtaining the Positioning information of the vehicle; an inertial navigation system for obtaining the movement information of the vehicle; and a processor electrically connected to the driving system, the positioning system, and the inertial navigation system, wherein the automatic During driving operation, the processor is used to generate a navigation plan based on the positioning information, an environmental information corresponding to the real world outside the vehicle, a digital map, and a target position, and the processor is used to generate a navigation plan based on the The positioning information identifies the current path point corresponding to the vehicle in the current planned path of the navigation plan and a monitored path in the current planned path, wherein the processor is used for identifying the current path point corresponding to the navigation plan according to the A maximum speed change absolute value of the monitoring path is used to select a target driving parameter group from a plurality of driving parameter groups, so as to instruct the driving system to apply the target driving parameter group to control the movement of the vehicle. The automatic driving system according to claim 1, wherein the navigation plan includes the current planned route and a plurality of planned speeds respectively corresponding to a plurality of way points in the current planned route. The automatic driving system according to claim 2, wherein the monitoring path is a part of the future path that the vehicle intends to enter in the current planned path, and the part of the future path is the part of the future path. The path that the vehicle intends to move during a monitoring period after the current time point. The automatic driving system according to claim 3, wherein the processor recognizes the current speed of the vehicle according to the movement information, wherein the processor determines the length of the monitoring period according to the current speed, wherein The length of the monitoring period is proportional to the current speed. The automatic driving system according to claim 4, wherein the processor further selects the target driving parameter set from the plurality of driving parameter sets based on the environmental information, wherein the environmental information includes at least one of the following information One or more: the coefficient of friction of the ground on which the vehicle is currently traveling; the gradient of the ground on which the vehicle is currently traveling; and the external force received by the vehicle. The automatic driving system according to claim 5, wherein each of the plurality of driving parameter groups includes at least: a position error weight value; a speed error weight plant; an acceleration output weight value; and an acceleration change amplitude weight value. An automatic driving method, applicable to an automatic driving system configured on a vehicle, the method comprising: obtaining positioning information and movement information of the vehicle; according to the positioning information, corresponding to an environment in the real world outside the vehicle Information, a digital map, and a target location to generate a navigation plan; according to the positioning information, one of the current path point corresponding to the vehicle in the current planned path of the navigation plan and the current planned path is identified Monitoring path; according to a maximum speed change absolute value of the monitoring path corresponding to the navigation plan, a target driving parameter group is selected from a plurality of driving parameter groups to apply the target driving parameter group to control the vehicle Mobile. The automatic driving method according to claim 7, wherein the navigation plan includes the current planned route and a plurality of planned speeds respectively corresponding to a plurality of way points in the current planned route. The automatic driving method according to claim 8, wherein the monitoring path is a part of the future path that the vehicle intends to enter in the current planned path, and the part of the future path is the The path that the vehicle intends to move during a monitoring period after the current time point. The automatic driving method according to claim 9, further comprising: recognizing the current speed of the vehicle according to the movement information; and determining the length of the monitoring period according to the current speed, wherein the monitoring period The length is proportional to the current speed. The automatic driving method according to claim 10, wherein the target driving is selected from the plurality of driving parameter groups according to the absolute value of the maximum speed change corresponding to the monitoring path in the navigation plan The step of the parameter group includes: further selecting the target driving parameter group from the plurality of driving parameter groups according to the environmental information, wherein the environmental information includes at least one or more of the following information: The coefficient of friction of the ground on which the vehicle is traveling; the gradient of the ground on which the vehicle is currently traveling; and the external force received by the vehicle. The automatic driving method according to claim 11, wherein each of the plurality of driving parameter groups includes at least: a position error weight value; a speed error weight plant; an acceleration output weight value; and an acceleration change amplitude weight value.

Images