CN111882474A - FDS function design method for cluster scheduling of automatic driving vehicles - Google Patents
FDS function design method for cluster scheduling of automatic driving vehicles Download PDFInfo
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Abstract
The invention provides an FDS function design method for cluster scheduling of automatic driving vehicles. Acquiring basic data and operation data of an automatic driving vehicle cluster, and configuring a transportation plan of the FDS according to the basic data and the operation data of the automatic driving vehicle based on a basic framework of an intelligent structure; monitoring the vehicle in real time according to a preset road side system to acquire road condition data and abnormal data of the vehicle; according to the road condition data and the abnormal data, a vehicle gauge level safety strategy of the vehicle is formulated; and planning the optimized driving of the FDS according to the vehicle gauge level safety strategy and the transportation plan of the FDS. The invention has the beneficial effects that: the invention designs FDS software into an MES system (production management execution system), which is a production management core system for realizing informatization and automation integration in the field of manufacturing industry.
Description
Technical Field
The invention relates to the technical field of integrated operation transportation, in particular to an FDS function design method for cluster scheduling of automatic driving vehicles.
Background
At present, although a system similar to the FDS is widely applied to cluster scheduling of indoor AGVs, such as the largest indoor AGV application item, No. kyoto warehouse, no cluster scheduling system of any autonomous mobile robot can demonstrate optimization of scheduling commands, that is, whether resource utilization maximization and production efficiency optimization are achieved by cluster scheduling or not.
In the field of automatic driving optimization scheduling, the FDS is a fleet scheduling system and is used for task allocation and intelligent traffic guidance of a cluster type automatic driving fleet. How to realize cluster scheduling, resource utilization maximization and production efficiency optimization, and FDS function application is a problem to be solved by those skilled in the art.
Disclosure of Invention
The invention provides an FDS function design method for cluster scheduling of automatic driving vehicles, which is used for solving the problem of difficulty in cluster scheduling of FDS.
An FDS function design method for cluster scheduling of autonomous vehicles, comprising:
acquiring basic data and operation data of an automatic driving vehicle cluster;
configuring a transportation plan of the FDS according to the basic data and the operation data based on the intelligently constructed basic framework;
monitoring the vehicle in real time according to a preset roadside system to acquire road condition data and abnormal data of the vehicle;
according to the road condition data and the abnormal data, a vehicle gauge level safety strategy of the vehicle is formulated;
and planning the optimized driving of the FDS according to the vehicle gauge level safety strategy and the transportation plan of the FDS.
As an embodiment of the present invention, the basic data includes: vehicle base data, process data, infrastructure data, and base maps; wherein the content of the first and second substances,
the vehicle basic data at least comprises vehicle speed per hour, vehicle turning radius and vehicle capacity;
the process data includes at least a loading process;
the infrastructure data at least comprises a communication base station and communication equipment;
the base map includes a base map database.
As an embodiment of the present invention, the configuration of the FDS transportation plan according to the basic data and the job data based on the basic framework of the intelligent configuration includes:
acquiring an intelligent construction basic framework, and determining a vehicle allocation plan, a process implementation plan, a basic communication plan and a driving path plan allocated by the FDS according to the basic data;
acquiring an intelligent construction basic framework, and determining the FDS production operation scheme and the task flow according to the operation data; wherein the content of the first and second substances,
the production operation scheme comprises a transportation scheme and a road maintenance scheme;
the transportation scheme comprises fleet scale and fleet path planning;
the task flow comprises a task flow and task basic data configuration.
As an embodiment of the present invention, the monitoring the vehicle in real time according to a preset roadside system to obtain road condition data and abnormal data of the vehicle includes:
acquiring real-time road condition data through the road side system; wherein the content of the first and second substances,
the real-time road condition data comprises a real-time vehicle state and a real-time vehicle scheduling condition; wherein the content of the first and second substances,
the real-time vehicle states include: the temperature of the engine, the residual oil quantity, the tire pressure and the state of the vehicle-mounted equipment;
the real-time vehicle dispatch conditions include: real-time global path planning and real-time vehicle task scheduling;
acquiring abnormal data according to the real-time vehicle state and the real-time vehicle scheduling condition; wherein the content of the first and second substances,
the exception data includes: vehicle anomalies, information system anomalies, and mission anomalies.
As an embodiment of the present invention, the vehicle abnormality includes a real-time driving abnormality; wherein the content of the first and second substances,
the real-time driving abnormality includes: the method comprises the following steps that (1) the central controller IPC is abnormal, a sensing module is abnormal, communication is abnormal, positioning is abnormal, a CAN bus is abnormal and the vehicle condition is abnormal;
the information system anomaly comprises: scheduling exceptions and infrastructure exceptions;
the task exception comprises: task execution exceptions and task allocation exceptions.
As an embodiment of the present invention, the monitoring the vehicle in real time according to a preset roadside system to obtain road condition data and abnormal data of the vehicle further includes:
positioning the vehicle of the FDS in real time through map updating to obtain real-time position data;
displaying the real-time state of the vehicle in real time according to the real-time position data;
and when the real-time state displayed in real time is abnormal data, performing real-time alarm, real-time optimization and real-time vehicle scheduling on the abnormal data.
As an embodiment of the present invention, the setting of the vehicle specification level safety policy of the vehicle according to the road condition data and the abnormal data includes:
according to the abnormal data, a local safety strategy of the vehicle is constructed based on the modularization self-checking of a software and hardware vehicle-mounted system of the vehicle and the closed-loop checking of a vehicle-mounted control system;
acquiring vehicle distance and road section abnormal data based on the road condition data, and constructing a global safety strategy of the vehicle according to the road section abnormal data and the vehicle distance;
constructing a service safety plan of the vehicle based on the sequential spatial configuration and the time sequence of the monitored multi-vehicle operation of the road side system;
and fusing and generating a vehicle gauge level safety strategy of the vehicle according to the local safety strategy of the vehicle, the global safety strategy of the vehicle and the service safety plan of the vehicle.
As an embodiment of the present invention, the constructing a local safety policy of a vehicle based on a modular self-check of a software and hardware vehicle-mounted system of the vehicle and a closed-loop check of a vehicle-mounted control system according to the abnormal data includes:
acquiring software and hardware abnormal data of the vehicle in the abnormal data;
based on a modular design principle, the safety strategy design of the vehicle-mounted system is carried out through the modular self-check of the vehicle and the closed-loop check of the vehicle-mounted control system;
based on the principle of anthropomorphic safe driving, a safety strategy design of safe driving of the vehicle is carried out through a perception system of the vehicle; wherein the content of the first and second substances,
the safe driving of the vehicle at least comprises the steps of autonomous following of the vehicle, overtaking, obstacle avoidance, obstacle detouring, safe distance judgment, dynamic tracking of external moving objects, behavior prediction and safety strategy design of autonomous path planning;
and synthesizing the safety strategy design of the vehicle-mounted system and the safety strategy design of safe driving of the vehicle to form a local safety strategy of the vehicle.
As an embodiment of the present invention, the acquiring the distance between vehicles and the abnormal data of the road section based on the road condition data, and constructing the global security policy of the vehicle according to the abnormal data of the road section and the distance between vehicles includes:
planning the vehicle flow in a preset matrix map according to the road condition data to form an anti-blocking strategy of the vehicle;
planning the driving sequence of the vehicle according to the obstacle condition in the road condition data to form an obstacle prevention strategy of the vehicle;
planning the tasks of the FDS according to the abnormal road section data to form a road section task strategy of the vehicle;
planning the vehicle distance according to the vehicle distance, and forming a distance control strategy of the vehicle based on double constraints of the vehicle distance and a linear relation between distance control and real-time speed;
and integrating the anti-blocking strategy, the obstacle-preventing strategy, the road section task strategy of the vehicle and the distance control strategy of the vehicle to form a global safety strategy of the vehicle.
As an embodiment of the present invention, the planning of the optimized driving of the FDS according to the vehicle-scale safety strategy and the transportation plan of the FDS includes:
determining a first optimized path of the FDS through a transportation plan and a vehicle gauge level safety strategy of the FDS;
determining a second optimized path of the FDS according to the operation data and the vehicle gauge level safety strategy;
and planning the optimized driving of the FDS by the first optimized path and the second optimized path through a combined mathematical theory.
The invention has the beneficial effects that: by FDS function design, based on intelligent manufacturing methodology, based on design of safety strategy and exception handling scheme of vehicle gauge, final purpose of lean production can be realized by application of optimal combination mathematics, and optimization and reliability of cluster scheduling can be verified by theory and practice. The invention provides a basic functional architecture, a guidance method and a business process for a cluster dispatching command system of an automatic driving vehicle; in the FDS function application design, FDS software is designed into an MES system (production management execution system), which is a production management core system for realizing informatization and automation integration in the field of similar manufacturing industry.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a flowchart of a method for FDS function design for cluster dispatch of autonomous vehicles according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating configuration base data according to an embodiment of the present invention;
FIG. 3 is a schematic illustration of a transportation planning implementation of the present invention;
FIG. 4 is a schematic illustration of a transportation plan configuration according to an embodiment of the present invention;
FIG. 5 is a schematic illustration of monitoring for real-time monitoring in an embodiment of the present invention;
FIG. 6 is a diagram illustrating abnormal data according to an embodiment of the present invention;
FIG. 7 is a schematic diagram illustrating the operation of the anti-blocking system according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of safety planning regulation in an embodiment of the present invention;
FIG. 9 is a schematic diagram of path optimization according to an embodiment of the present invention;
FIG. 10 is a functional diagram of an FDS in an embodiment of the present invention;
FIG. 11 is a schematic diagram of the basic architecture of the intelligent manufacturing in an embodiment of the present invention;
FIG. 12 is a schematic diagram of data closed loop feedback according to an embodiment of the present invention;
FIG. 13 is a graph illustrating yield statistics in an embodiment of the present invention;
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
The invention is mainly applied to task allocation and real-time intelligent traffic guidance of a manually driven vehicle, an automatically driven vehicle, an AGV or a similar autonomous mobile robot in cluster operation, and is particularly suitable for an application scene of realizing an optimized autonomous transport system by taking lean production as a primary target.
The invention provides a vehicle cluster dispatching command system based on automatic driving vehicles, as shown in figure 11, the invention provides a basic functional architecture, a guidance method and application design of a business process in an FDS system through an intelligent manufacturing infrastructure, and FDS software is designed into an MES system (production management execution system), which is similar to a production management core system for realizing informatization and automation integration in the field of manufacturing industry. FDS is a motorcade dispatching system and is used for task allocation and intelligent traffic guidance of a cluster type automatic driving motorcade. As shown in fig. 12, an informationized and automated closed-loop feedback mode is formed in the FDS function design based on the data intercommunication interconnection between the upper-level informationization and the lower-level automation of the MES system, so as to achieve the maximum production efficiency with reference to the MES system, and assist the present invention in achieving the purpose of maximizing the transportation efficiency in the function design.
The FDS function design is similar to two-in-one MES + SCADA two-level system in the drawing 11, the FDS can be independently used as a bottom-layer basic automation control system SCADA system, and can also be designed to be a system integrating MES + SCADA, so that production management (transportation management and bottom control in the invention) is realized. Based on a basic system architecture of intelligent manufacturing, the FDS is described as an MES + SACADA fusion system in an emphatic mode, so that production management planning is achieved, and vehicle path planning and state monitoring of the bottom layer are performed at the same time.
As shown in fig. 10: when the FDS function is designed, the FDS function design is designed into MES + SCADA fusion software similar to the production and manufacturing industry, the system is started up to realize informatization-automation fusion, a transportation plan is formulated through basic data configuration, real-time road condition monitoring and operation process optimization, vehicle maintenance, abnormal condition processing and a statistical statement system are used for counting the transportation volume of the final transportation plan, the whole FDS function system is subjected to system maintenance, and then closed circulation of data is realized, namely the informatization (scheduling, commanding and task data) and automation data (vehicle unit data) are fused up-down and down-up, closed data circulation analysis is realized, continuous optimization of an operation process and a vehicle control algorithm can be realized, and refinement is achieved.
The FDS function design overall process of the invention is as follows: according to a unique intelligent manufacturing methodology, on the basis of design of a safety strategy and an exception handling scheme of a vehicle gauge level, the final purpose of lean production can be realized through application of optimal combination mathematics, and the optimization and reliability of cluster scheduling can be verified through theory and practice.
Fig. 1 is a flow chart of a method of designing FDS functions for cluster dispatch of autonomous vehicles, including:
step 100: acquiring basic data and operation data of an automatic driving vehicle cluster;
in the step of functional design, basic data of the FDS function, which may also be project data and task data, and jobs to be performed are first configured and collected based on the cluster of autonomous driving vehicles, and the job data in the autonomous driving optimization scheduling system is transportation data.
Step 101: configuring a transportation plan of the FDS according to the basic data and the operation data based on the intelligently constructed basic framework; therefore, the invention converts the distributed regulation and control of the FDS vehicles into the transportation plan in the form of the operation plan based on the intelligent constructed basic framework, and implements the transportation plan in a project operation mode, so that the transportation plan can be continuously adjusted and optimized under a better condition.
Step 102: monitoring the vehicle in real time according to a preset roadside system to acquire road condition data and abnormal data of the vehicle; the road side system is a road condition monitoring system which is preset. Roadside means road conditions, and a roadside system means monitoring of road conditions, such as road congestion and road anomalies. Additional functions will be planned depending on the application scenario. For example: taking mine automatic driving application as an example, the roadside system is used for monitoring road conditions, such as road congestion, road traffic accidents, road collapse, fire, smoke abnormity and the like. Additionally related to the production process, the pose of the excavating equipment is abnormal, and the like. Significance of roadside system existence: the system provides fixed-position independent third-party visual real-time monitoring for the FDS and the automatic driving vehicle, feeds back real-time monitoring data, and provides real road condition and operation state feedback for the FDS and the vehicle.
Step 103: according to the road condition data and the abnormal data, a vehicle gauge level safety strategy of the vehicle is formulated; the vehicle-level safety strategy provided by the invention carefully fuses the FDS and the safety mechanism of the vehicle, outputs a systematic safety strategy scheme, forms a closed-loop safety mechanism from global planning-local autonomous and local planning-global decision, and can greatly improve the driving safety level of the autonomous vehicle.
Step 104: and planning the optimized driving of the FDS according to the vehicle gauge level safety strategy and the transportation plan of the FDS. The optimized driving of the invention is a global real-time optimized scheduling-optimized path planning: according to the vehicle gauge level safety strategy and the transportation plan of the FDS, by means of an optimal combination mathematical theory, aiming at the clustered task of the FDS, the optimal running path (a plurality of optimal mixed strategy algorithms) of the multitask vehicle can be theoretically calculated and demonstrated, and the optimal running path is supervised and realized. The combined mathematics is mainly applied to the existing algorithm, and the linear programming, dynamic programming, A, D and the like are covered
As an embodiment of the present invention, the basic data includes: vehicle base data, process data, infrastructure data, and base maps; wherein the content of the first and second substances,
the vehicle basic data at least comprises vehicle speed per hour, vehicle turning radius and vehicle capacity;
the process data includes at least a loading process;
the infrastructure data at least comprises a communication base station and communication equipment;
the base map includes a base map database.
The principle of the invention is as follows: the basis of the FDS functional design is basic data, and the basic data is obtained by an automatic driving optimization scheduling system in the prior art.
The invention has the advantages that the basic data is the bottom building with the FDS function, and all the task planning, vehicle movement, process setting, route maps, infrastructure and communication are regulated and configured through the basic data.
In one embodiment, as shown in a basic configuration data diagram of FIG. 2, in an automatic mine driving project
1. The basic data includes:
basic data of the vehicle such as capacity (tonnage, capacity), speed per hour, minimum turning radius, etc.
The process data comprises: a loading mode representing the relative attitude of the mine car with the excavating equipment as it approaches the excavating equipment.
Other communications base station settings, e.g. communications infrastructure data, indicating local operation
Mine area basic map: the map database is a unified basic map database of the automatic driving vehicle and the FDS, is consistent with the vehicle, and can be used for path planning.
As an embodiment of the present invention, the configuration of the FDS transportation plan according to the basic data and the job data based on the basic framework of the intelligent configuration includes:
acquiring an intelligent construction basic framework, and determining a vehicle allocation plan, a process implementation plan, a basic communication plan and a driving path plan allocated by the FDS according to the basic data;
acquiring an intelligent construction basic framework, and determining the FDS production operation scheme and the task flow according to the operation data; wherein the content of the first and second substances,
the production operation scheme comprises a transportation scheme and a road maintenance scheme;
the transportation scheme comprises fleet scale and fleet path planning;
the task flow comprises a task flow and task basic data configuration.
The principle of the invention is as follows: the invention is based on the basic framework of the intelligent construction, and converts the mode of specifying the production plan through basic data in the intelligent construction into the transportation plan in the invention. In the whole transportation plan, a vehicle allocation plan, a process implementation plan, a basic communication plan, a driving path plan, an operation scheme and a task flow allocated by the FDS under the FDS need to be formulated.
The invention has the beneficial effects that: in the functional design of the FDS, a transportation plan is designed and formulated, and vehicle allocation, process implementation, basic communication, a driving path, an operation scheme and a task flow of FDS allocation are appointed in advance, so that the project is convenient to regulate and control and the task is quickly completed during implementation.
In one embodiment, as shown in a transportation planning diagram of fig. 3 and a transportation planning configuration diagram of fig. 4, in an automated mine driving program:
according to the working scene of the automatic driving mine truck or other similar autonomous mobile robots, most of the reciprocating work at A, B points in the stage time domain can be calculated according to the production speed of A, B point excavation, such as the working efficiency of mine excavation equipment, and therefore the size of the fleet of points between AB points can be planned, and meanwhile, the fleet of points also depends on the loading speed of the vehicles, such as the shovel ratio.
As an embodiment of the present invention, the real-time monitoring the vehicle according to a preset roadside system, as shown in the monitoring schematic diagram of real-time monitoring shown in fig. 5, acquiring road condition data and abnormal data of the vehicle, includes:
acquiring real-time road condition data through the road side system; wherein the content of the first and second substances,
the real-time road condition data comprises a real-time vehicle state and a real-time vehicle scheduling condition; wherein the content of the first and second substances,
the real-time vehicle states include: the temperature of the engine, the residual oil quantity, the tire pressure and the state of the vehicle-mounted equipment;
the real-time vehicle dispatch conditions include: real-time global path planning and real-time vehicle task scheduling;
acquiring abnormal data according to the real-time vehicle state and the real-time vehicle scheduling condition; wherein the content of the first and second substances,
the exception data includes: vehicle anomalies, information system anomalies, and mission anomalies.
The principle of the invention is as follows: the real-time monitoring is carried out through a preset roadside system, so that equipment facilities such as a panoramic camera and a laser radar and a navigation satellite (Beidou navigation, GPS navigation and the like) are erected to obtain the position of a vehicle implementing a transportation plan, the real-time state of the vehicle, the road section condition of the vehicle, the road section traffic flow and the like. And the abnormal condition of the vehicle state can be acquired through the information system of the vehicle. And determining whether the task is abnormal or not according to the abnormal conditions of the vehicle abnormality and the information system abnormality.
The invention has the beneficial effects that: the method comprises the steps of acquiring road condition data and abnormal data in real time, finding abnormality according to the road condition data, regulating and controlling an optimized route, and regulating and controlling other vehicles according to the road condition data to solve the abnormality when the abnormality occurs, so as to assist in quickly completing a transportation task.
As an embodiment of the invention, as shown in the abnormal data diagram of FIG. 6: the vehicle abnormality includes a real-time driving abnormality; wherein the content of the first and second substances,
the real-time driving abnormality includes: the method comprises the following steps that (1) the central controller IPC is abnormal, a sensing module is abnormal, communication is abnormal, positioning is abnormal, a CAN bus is abnormal and the vehicle condition is abnormal;
the information system anomaly comprises: scheduling exceptions and infrastructure exceptions;
the task exception comprises: task execution exceptions and task allocation exceptions.
The real-time monitoring of the abnormity can be divided into three types of vehicle abnormity, information system abnormity and task abnormity, and a strategy for solving the abnormity can be quickly found according to specific abnormity and abnormity types in practical implementation.
In one embodiment, in a mine autopilot project:
and monitoring the operation state of the vehicle and the completion condition of the task in real time.
The vehicle state includes: vehicle conditions such as engine temperature, residual oil volume, tire pressure, and the like, and vehicle equipment status (such as an automatic driving model test, a sensing module, a navigation device, and the like).
The task states include: number of tasks executed, percentage of completion of task execution, Normal/abnormal
As an embodiment of the present invention, the monitoring the vehicle in real time according to a preset roadside system to obtain road condition data and abnormal data of the vehicle, as shown in fig. 5, further includes:
positioning the vehicle of the FDS in real time through map updating to obtain real-time position data;
displaying the real-time state of the vehicle in real time according to the real-time position data;
and when the real-time state displayed in real time is abnormal data, performing real-time alarm, real-time optimization and real-time vehicle scheduling on the abnormal data.
The real-time data acquisition of the invention is based on map data and mainly through online maps, such as Baidu maps, Tencent maps, Gagde maps and other network maps. The abnormal data is displayed to the transport personnel who finish the transport task and the control end for regulating and controlling the overall planning in real time through the communication equipment, so that all links in the transport plan can be flexibly allocated, and the time for processing the abnormal data is reduced.
As an embodiment of the present invention, the setting of the vehicle specification level safety policy of the vehicle according to the road condition data and the abnormal data includes:
according to the abnormal data, a local safety strategy of the vehicle is constructed based on the modularization self-checking of a software and hardware vehicle-mounted system of the vehicle and the closed-loop checking of a vehicle-mounted control system;
acquiring vehicle distance and road section abnormal data based on the road condition data, and constructing a global safety strategy of the vehicle according to the road section abnormal data and the vehicle distance;
constructing a service safety plan of the vehicle based on the sequential spatial configuration and the time sequence of the monitored multi-vehicle operation of the road side system;
and fusing and generating a vehicle gauge level safety strategy of the vehicle according to the local safety strategy of the vehicle, the global safety strategy of the vehicle and the service safety plan of the vehicle.
The vehicle gauge level safety strategy comprises two parts, namely an FDS global safety strategy (primary level) and an automatic driving vehicle local safety strategy (secondary level), so that an integral-local global safety design is formed. And a safety control strategy with auxiliary local regulation and main global regulation is realized.
In one embodiment: the roadside system is an independent intelligent roadside monitoring module, belongs to an independent real-time intelligent roadside monitoring system under the FDS, and is characterized in that equipment facilities such as a panoramic camera and a laser radar are erected through a roadside end to provide completely independent third-party safety guarantee for a vehicle-scale safety strategy, so that the probability of abnormity occurrence is reduced to 1.25 permillage (5% x 5% x 5%).
Taking the detection of a collision in vehicle tracking as an example, the probability of failure detection is calculated as:
perception system of the vehicle: detecting the failure probability of the front vehicle: estimating 5 percent;
the FDS system monitors the distance between vehicles: controlling the distance between vehicles and the vehicle speed per hour in real time, and controlling the failure probability to be estimated by 5%;
the road side system monitors the following distance: detecting the failure probability by 5%;
the three are independent, and the detection failure probability after fusion is 5% x 5% x 5% to 1.25 ‰.
As an embodiment of the present invention, the constructing a local safety policy of a vehicle based on a modular self-check of a software and hardware vehicle-mounted system of the vehicle and a closed-loop check of a vehicle-mounted control system according to the abnormal data includes:
acquiring software and hardware abnormal data of the vehicle in the abnormal data;
based on a modular design principle, the safety strategy design of the vehicle-mounted system is carried out through the modular self-check of the vehicle and the closed-loop check of the vehicle-mounted control system;
based on the principle of anthropomorphic safe driving, a safety strategy design of safe driving of the vehicle is carried out through a perception system of the vehicle; wherein the content of the first and second substances,
the safe driving of the vehicle at least comprises the steps of autonomous following of the vehicle, overtaking, obstacle avoidance, obstacle detouring, safe distance judgment, dynamic tracking of external moving objects, behavior prediction and safety strategy design of autonomous path planning;
and synthesizing the safety strategy design of the vehicle-mounted system and the safety strategy design of safe driving of the vehicle to form a local safety strategy of the vehicle.
The principle of the invention is as follows: the local safety strategy comprises the steps of designing the vehicle gauge level of software and hardware, mounting all core components in a bus mode on the basis of a strictly defined modular design principle, and realizing the near vehicle gauge level design of a vehicle-mounted system by modular self-checking and closed-loop checking of the vehicle-mounted control system. The method is characterized in that a personified safe driving principle is used, a perception system sensor is used for realizing a human-like visual system, and most human-like safe driving decisions are simulated, including autonomous following, overtaking, obstacle avoidance, obstacle detouring, safe distance judgment, dynamic tracking of external moving objects, behavior prediction, autonomous path planning and the like. And outputting an anthropomorphic safe driving strategy according to a reliable software and hardware vehicle-mounted system and an anthropomorphic safe driving principle, wherein the strategy is used for planning and deciding the autonomous driving of the vehicle.
The invention has the beneficial effects that: the near-vehicle-scale design of the vehicle-mounted system is realized, the safe driving decision of most people is simulated, and the anthropomorphic safe driving strategy is output as a local safe strategy.
As an embodiment of the present invention, the acquiring the distance between vehicles and the abnormal data of the road section based on the road condition data, and constructing the global security policy of the vehicle according to the abnormal data of the road section and the distance between vehicles includes:
planning the vehicle flow in a preset matrix map according to the road condition data to form an anti-blocking strategy of the vehicle;
planning the driving sequence of the vehicle according to the obstacle condition in the road condition data to form an obstacle prevention strategy of the vehicle;
planning the tasks of the FDS according to the abnormal road section data to form a road section task strategy of the vehicle;
planning the vehicle distance according to the vehicle distance, and forming a distance control strategy of the vehicle based on double constraints of the vehicle distance and a linear relation between distance control and real-time speed;
and integrating the anti-blocking strategy, the obstacle-preventing strategy, the road section task strategy of the vehicle and the distance control strategy of the vehicle to form a global safety strategy of the vehicle.
The invention has the advantages that the overall control strategy principle and the beneficial effects are as follows: in the anti-blocking strategy, based on a matrix map, the traffic flow of each road is counted in real time, and for a new transportation task, the FDS automatically selects to avoid a congested road section.
In the road section abnormality data of the vehicle, any road section abnormality is detected, the road section is closed after the road side system or the vehicle feeds back, and the new mission plan does not consider the road section.
In the vehicle spacing control strategy, the spacing of the vehicles is maintained at a certain number of meters. The functional strategy is maintained for the distance between multiple vehicles running on any same road section, and provides additional distance control for the autonomous safety strategy of the vehicles, so that the distance between the vehicles has double constraints, and the distance control and the real-time speed of the vehicles have a certain linear relation.
In the anti-blocking strategy of the vehicle, as shown in fig. 7, when the vehicle encounters a blue obstacle at the upper right corner, the vehicle will leave the center line to start obstacle detouring, but before the obstacle detouring is started, the FDS needs to be informed in advance, the FDS confirms when the obstacle detouring is started according to the speed per hour and the task execution priority of the oncoming vehicle, if the obstacle detouring is started immediately, the oncoming vehicle must stop in a certain specified area (which is calculated according to the road section where the obstacle detouring passes) on the oncoming vehicle specified by the FDS, and after the obstacle detouring vehicle returns to the normal driving path of the center line, the oncoming vehicle can continue to move forward; if the FDS decides that the oncoming vehicle advances, the barrier-detouring vehicle stops before the barrier after the barrier-detouring vehicle delays, and the barrier-detouring vehicle starts the barrier-detouring after waiting for the oncoming vehicle to pass.
In one embodiment, the service safety planning is carried out on the service, and in the mine automatic driving project: the business safety planning, here, refers to the sequential spatial configuration and timing of multi-vehicle operation, and the following fig. 8 shows the designed dumping process of the automatically driven mine card in the dumping site.
In the arc-shaped area at the upper part of the drawing 8, vehicles need to be backed to the edge, then the lifting hopper dumps the loaded earthwork, the interactive operation of at most 10 vehicles needs to be carried out, the reversing and reversing are selected, the operation space and the time sequence need to be designed independently, the process action of turning back and reversing is completed safely in the area, the operation efficiency requirement is met, the left drawing and the right drawing represent that a loader operating in a dump is used as a dump command center, the mine car is respectively dispatched to the designated position for operation, and after the dumping operation is completed, the loader (the command center) exits the dump according to the path designated by the loader.
In one embodiment, the mine autopilot project: the FDS is a mine autonomous transport system, and in the process of path optimization, the transportation volume is counted, which is equal to the yield statistics in the mine autonomous driving project, as shown in the attached figure 13; the statistical result can be used for financial settlement of working hours and transportation amount, and can also be used for continuous optimization of the operation process.
In other similar operation scenarios, the operation efficiency of the autonomous vehicle needs to be evaluated by the yield statistics, and the evaluation result is used to continuously improve the operation manner, such as continuously optimized path planning strategy, speed planning, operation frequency planning, and the like, and finally, the global production optimization is refined, so as to continuously improve the production efficiency.
As an embodiment of the present invention, the planning of the optimized driving of the FDS according to the vehicle-scale safety strategy and the transportation plan of the FDS includes:
determining a first optimized path of the FDS through a transportation plan and a vehicle gauge level safety strategy of the FDS;
determining a second optimized path of the FDS according to the operation data and the vehicle gauge level safety strategy;
and generating an optimized running path for planning the cluster type automatic driving fleet by the first optimized path and the second optimized path through a combined mathematical theory.
The invention adopts global real-time optimized scheduling-optimized path planning: the optimized path planning covers the operation actions of the automatic driving vehicle, such as path optimization of turning back and reversing, vehicle alignment, driving routes, global process maps and the like; the invention can theoretically calculate and demonstrate the optimized driving path (various optimized mixed strategy algorithms) of the multi-task vehicle aiming at the cluster task by means of the optimal combination mathematical theory and supervise and realize the optimized driving path. The combined mathematics is mainly applied to the existing algorithm, and the linear programming, dynamic programming, A, D and the like are covered.
In an embodiment, as shown in fig. 9, in the route optimization diagram, the map is a matrix map, and there are many routes from the starting point a to the point B, but to find the most efficient route, so that the shortest arrival time, the shortest route, the lowest cost, and the like need to be obtained according to different constraints, and different route lines may be generated, which is global route planning.
The global map of the working area is stored in the FDS and the vehicle-mounted system database of the automatic driving vehicle, and after the FDS of the system is consistent with the map data of the vehicle, the FDS can calculate the most efficient path according to different optimization strategies or fused optimization strategies and send the path to the vehicle for execution.
The dynamic path planning means that when a certain road section passing by is congested and abnormal, so that the road section cannot pass through, the FDS plans a new path in real time according to the current position of the vehicle again and sends the new path to the vehicle for execution. In the graphic area, as many as ten or more vehicles may be simultaneously operated, the FDS needs to consider the operation tasks of all the vehicles, determine different driving paths by optimized space and time sequence planning, guide a plurality of vehicles to simultaneously drive in an optimal path so as to achieve the highest overall operation efficiency, and realize the optimized operation path planning according to the operation research dynamic planning, linear planning, a and D algorithms.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. An FDS function design method for cluster scheduling of autonomous vehicles, comprising:
acquiring basic data and operation data of an automatic driving vehicle cluster;
configuring a transportation plan of the FDS according to the basic data and the operation data based on the intelligently constructed basic framework;
monitoring the vehicle in real time according to a preset road side system to acquire road condition data and abnormal data of the vehicle;
according to the road condition data and the abnormal data, a vehicle gauge level safety strategy of the vehicle is formulated;
and planning the optimized driving of the FDS according to the vehicle gauge level safety strategy and the transportation plan of the FDS.
2. The method of claim 1, wherein the FDS function design method for cluster dispatching of autonomous vehicles is characterized in that:
the basic data includes: vehicle base data, process data, infrastructure data, and base maps; wherein the content of the first and second substances,
the vehicle basic data at least comprises vehicle speed per hour, vehicle turning radius and vehicle capacity;
the process data includes at least a loading process;
the infrastructure data at least comprises a communication base station and communication equipment;
the base map includes a base map database.
3. The method of claim 1, wherein the FDS function design method for cluster dispatching of autonomous vehicles is characterized in that: the infrastructure based on intelligent construction, which configures transportation plan of FDS according to the basic data and operation data, includes:
obtaining an intelligent build infrastructure
Determining a vehicle dispatching plan, a process implementation plan, a basic communication plan and a driving path plan which are dispatched by the FDS according to the basic data;
determining the FDS production operation scheme and a task flow according to the operation data; wherein the content of the first and second substances,
the production operation scheme comprises a transportation scheme and a road maintenance scheme;
the transportation scheme comprises fleet scale and fleet path planning;
the task flow comprises a task flow and task basic data configuration.
4. The method of claim 1, wherein the FDS function design method for cluster dispatching of autonomous vehicles is characterized in that: according to predetermineeing the trackside system, to the vehicle carries out real time monitoring, acquires the road conditions data and the abnormal data of vehicle, includes:
acquiring real-time road condition data through the road side system; wherein the content of the first and second substances,
the real-time road condition data comprises a real-time vehicle state and a real-time vehicle scheduling condition; wherein the content of the first and second substances,
the real-time vehicle states include: the temperature of the engine, the residual oil quantity, the tire pressure and the state of the vehicle-mounted equipment;
the real-time vehicle dispatch conditions include: real-time global path planning and real-time vehicle task scheduling;
acquiring abnormal data according to the real-time vehicle state and the real-time vehicle scheduling condition; wherein the content of the first and second substances,
the exception data includes: vehicle anomalies, information system anomalies, and mission anomalies.
5. The FDS function design method for cluster dispatching of autonomous vehicles according to claim 4, characterized in that: the vehicle abnormality includes a real-time driving abnormality; wherein the content of the first and second substances,
the real-time driving abnormality includes: the method comprises the following steps that (1) the central controller IPC is abnormal, a sensing module is abnormal, communication is abnormal, positioning is abnormal, a CAN bus is abnormal and the vehicle condition is abnormal;
the information system anomaly comprises: scheduling exceptions and infrastructure exceptions;
the task exception comprises: task execution exceptions and task allocation exceptions.
6. The method of claim 1, wherein the FDS function design method for cluster dispatching of autonomous vehicles is characterized in that: according to predetermineeing the trackside system, to the vehicle carries out real time monitoring, acquires the road conditions data and the abnormal data of vehicle, still includes:
positioning the vehicle of the FDS in real time through map updating to obtain real-time position data;
displaying the real-time state of the vehicle of the FDS in real time according to the real-time position data;
and when the real-time state displayed in real time is abnormal data, performing real-time alarm, real-time optimization and real-time vehicle scheduling on the abnormal data.
7. The method of claim 1, wherein the FDS function design method for cluster dispatching of autonomous vehicles is characterized in that: the setting of the vehicle gauge safety strategy of the vehicle according to the road condition data and the abnormal data comprises the following steps:
according to the abnormal data, a local safety strategy of the vehicle is constructed based on the modularization self-checking of a software and hardware vehicle-mounted system of the vehicle and the closed-loop checking of a vehicle-mounted control system;
acquiring vehicle distance and road section abnormal data based on the road condition data, and constructing a global safety strategy of the vehicle according to the road section abnormal data and the vehicle distance;
constructing a service safety plan of the vehicle based on the sequential spatial configuration and the time sequence of the monitored multi-vehicle operation of the road side system;
and constructing a vehicle gauge level safety strategy of the vehicle according to the local safety strategy of the vehicle, the global safety strategy of the vehicle and the service safety plan of the vehicle.
8. An FDS function design method for cluster dispatching of autonomous vehicles according to claim 7, characterized in that: according to the abnormal data, based on modularization self-checking of a software and hardware vehicle-mounted system of the vehicle and closed-loop checking of a vehicle-mounted control system, a local safety strategy of the vehicle is constructed, and the method comprises the following steps:
acquiring software and hardware abnormal data of the vehicle in the abnormal data;
based on a modular design principle, the safety strategy design of the vehicle-mounted system is carried out through the modular self-check of the vehicle and the closed-loop check of the vehicle-mounted control system;
based on the principle of anthropomorphic safe driving, a safety strategy design of safe driving of the vehicle is carried out through a perception system of the vehicle; wherein the content of the first and second substances,
the safe driving of the vehicle at least comprises the steps of autonomous following of the vehicle, overtaking, obstacle avoidance, obstacle detouring, safe distance judgment, dynamic tracking of external moving objects, behavior prediction and safety strategy design of autonomous path planning;
and synthesizing the safety strategy design of the vehicle-mounted system and the safety strategy design of safe driving of the vehicle to form a local safety strategy of the vehicle.
9. The FDS function design method for cluster dispatching of autonomous vehicles according to claim 7, wherein: the method for acquiring the distance between vehicles and the abnormal data of the road section based on the road condition data and establishing the global safety strategy of the vehicles according to the abnormal data of the road section and the distance between the vehicles comprises the following steps:
planning the vehicle flow in a preset matrix map according to the road condition data to form an anti-blocking strategy of the vehicle;
planning the driving sequence of the vehicle according to the obstacle condition in the road condition data to form an obstacle prevention strategy of the vehicle;
planning the tasks of the FDS according to the abnormal road section data to form a road section task strategy of the vehicle;
planning the vehicle distance according to the vehicle distance, and forming a distance control strategy of the vehicle based on double constraints of the vehicle distance and a linear relation between distance control and real-time speed;
and integrating the anti-blocking strategy, the obstacle-preventing strategy, the road section task strategy of the vehicle and the distance control strategy of the vehicle to form a global safety strategy of the vehicle.
10. The method of claim 1, wherein the FDS function design method for cluster dispatching of autonomous vehicles is characterized in that: planning the optimized driving of the FDS according to the vehicle gauge level safety strategy and the transportation plan of the FDS, and comprises the following steps:
determining a first optimized path of the FDS through a transportation plan and a vehicle gauge level safety strategy of the FDS;
determining a second optimized path of the FDS according to the operation data and the vehicle gauge level safety strategy;
and planning the optimized driving of the FDS by the first optimized path and the second optimized path through a combined mathematical theory.
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