CN116343514A - Vehicle dispatching management method and system for unmanned vehicle - Google Patents
Vehicle dispatching management method and system for unmanned vehicle Download PDFInfo
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- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096708—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
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Abstract
The invention discloses a vehicle dispatching management method and system for unmanned, wherein the method comprises the following steps: acquiring task priority and constraint conditions of the unmanned vehicle; controlling the unmanned vehicle to reach a destination according to a pre-planned unmanned vehicle driving path and starting time; detecting vehicles in a destination parking lot, obtaining a parking space of the unmanned vehicle, and automatically parking the unmanned vehicle into the parking space based on a parking rule; the method comprises the steps of monitoring vehicles and tasks in real time, obtaining real-time states of the vehicles and the tasks, and monitoring and processing abnormal conditions in real time; the system comprises a dispatching preparation module, a road driving dispatching module, a parking dispatching module and a state monitoring module. The vehicle transportation is more efficient, safe and reliable, the scheduling and sequencing of the lowest total running cost of all unmanned vehicles are realized, and intelligent and efficient scheduling and parking of a plurality of vehicles are realized.
Description
Technical Field
The invention relates to the technical field of vehicle management, in particular to a vehicle dispatching management method and system for unmanned vehicles.
Background
Vehicle dispatch management refers to the management process of planning and controlling vehicles to optimize their use and efficiency. Vehicle dispatch management generally includes the following aspects:
1. vehicle dispatch plan: and (3) making a vehicle dispatching plan according to the business demands and vehicle resources of the company, and arranging vehicle transportation tasks including route planning, loading and unloading time, transportation quantity and the like.
2. Vehicle scheduling implementation: and (5) implementing a vehicle dispatching plan to guide a driver to complete the transportation task of the vehicle according to the plan.
3. Vehicle monitoring: the position, the running speed, the running route and the like of the vehicle are monitored in real time by technical means such as GPS and the like, so that the safety and smoothness of the transportation of the vehicle are ensured.
4. Vehicle maintenance management: and the vehicle is regularly maintained and serviced, so that the safety and reliability of the running of the vehicle are ensured.
5. Vehicle dispatch data analysis: by analyzing the vehicle transportation data, the bottleneck and the problem of vehicle transportation are known, the vehicle dispatching plan and the transportation route are optimized, the transportation efficiency is improved, and the cost is reduced.
The existing vehicle dispatching management method is based on a fixed path to dispatch and manage vehicles, and the overall efficiency of vehicle dispatching is low. For example, chinese patent No. 202010941886.5 discloses a vehicle parking scheduling management method and related components thereof, which calculates a shortest path based on a shortest path algorithm, uses a corresponding empty parking space as an optimal scheduling parking space, generates scheduling information, and sends the scheduling information to a current vehicle, thereby improving the utilization rate of the parking space. However, the method has the following defects in specific application: in the vehicle parking scheduling management method, the algorithm is utilized to perform path optimization to realize optimal vehicle scheduling, and the method can help vehicles to schedule orderly, but when a plurality of vehicles schedule together, the vehicles can stop and wait too much, and further optimization space exists in the aspect of overall efficiency.
For the problems in the related art, no effective solution has been proposed at present.
Disclosure of Invention
Aiming at the problems in the related art, the invention provides a vehicle dispatching management method and a vehicle dispatching management system for unmanned vehicles, which are used for overcoming the technical problems existing in the related art.
For this purpose, the invention adopts the following specific technical scheme:
according to one aspect of the present invention, there is provided a vehicle schedule management method for unmanned vehicles, the method comprising the steps of:
s1, acquiring task priority and constraint conditions of an unmanned vehicle;
s2, controlling the unmanned vehicle to reach a destination according to a pre-planned driving path and starting time of the unmanned vehicle;
s3, detecting the vehicle in a parking lot of a destination, obtaining a parking space of the unmanned vehicle, and automatically parking the unmanned vehicle into the parking space based on a parking rule;
and S4, monitoring the vehicle and the task in real time, acquiring the real-time state of the vehicle and the task, and monitoring and processing the abnormal situation in real time.
Further, the task priority and constraint condition of the unmanned vehicle are obtained, which comprises the following steps:
s11, before the unmanned vehicle is dispatched, the dispatching requirements and constraint conditions of the unmanned vehicle are defined, and a dispatching scene is obtained;
s12, collecting task destinations, driving paths and starting time of scheduling tasks according to the obtained scheduling scene to obtain task information;
and S13, determining the number of the unmanned vehicles, the load capacity and the endurance mileage according to the scheduling scene and the task information.
Further, the vehicle detection in the parking lot of the destination, and the obtaining of the parking space of the unmanned vehicle includes the following steps:
setting a binocular camera for shooting measurement at a parking lot entrance of a destination, and calibrating the binocular camera in advance;
sending a request for acquiring the size information of the unmanned vehicle, and if the size information of the unmanned vehicle is fed back, determining a parking space of the unmanned vehicle according to the size information;
if the size information of the unmanned vehicle cannot be obtained through feedback, the unmanned vehicle is driven into the measuring area;
performing size measurement on the unmanned vehicle in the measurement area according to the calibrated binocular camera;
and after the size measurement is completed, determining the parking space of the unmanned vehicle according to the measured size information of the unmanned vehicle.
Further, the step of measuring the size of the unmanned vehicle in the measurement area according to the calibrated binocular camera includes the following steps:
acquiring two unmanned vehicle images from different positions through the calibrated binocular camera, and obtaining projection points on the two unmanned vehicle images;
acquiring any point P on unmanned vehicle w And obtain point P w Optical axis coordinates in two camera coordinate systems of the binocular camera, and homogeneous coordinates of two projection points under respective coordinate systems and points P are obtained simultaneously w Homogeneous coordinates in world coordinate system;
the method comprises the steps of calibrating and giving a projective transformation matrix when a binocular camera shoots two unmanned vehicle images, combining the projective transformation matrix with a linear theory of camera imaging, and utilizing two optical axis coordinates, homogeneous coordinates of two projection points under respective coordinate systems and a point P w Obtaining straight lines passing through two groups of optical center points and projection points in the binocular camera by homogeneous coordinates under a world coordinate system, and obtaining point P w Is the intersection of two straight lines, and the point P is obtained w Is a three-dimensional coordinate of (2);
and determining three-dimensional coordinates of each vertex on the unmanned vehicle, and calculating to obtain the three-dimensional data size of the unmanned vehicle.
Further, when the binocular camera for image capturing and measuring is set at the entrance of the parking lot of the destination and the binocular camera is calibrated in advance, a square pattern with regular arrangement is used as a calibration plate, the size of the square is known, and the vertex of the square is used as a calibration reference point.
Further, the automatic parking of the unmanned vehicle into the space based on the parking rule comprises the following steps:
carrying out communication connection on each unmanned vehicle entering a parking lot, and acquiring the positioning of the other party;
enabling each unmanned vehicle to drive to a target parking space according to a shortest path principle;
calculating the total running cost of all unmanned vehicles:
U N ＝∑ i∈N U i (s i )
wherein s is i A policy set for the ith unmanned vehicle;
U i minimum running cost function for ith unmanned vehicle, U N The running cost function of all unmanned vehicles is adopted, and N is a non-zero natural number;
all unmanned vehicles cooperate, and the scheduling order with the lowest total running cost is obtained according to a cooperation model:
wherein P is the total running cost obtained by cooperation of all unmanned vehicles;
s i a policy set for the ith unmanned vehicle;
U i minimum running cost function for ith unmanned vehicle, N is a non-zero natural number
σ is the initial scheduling order and,
a running cost function ordered for the initial schedule of the ith unmanned vehicle.
Further, when the scheduling sequence with the lowest total running cost is obtained through calculation, the optimal scheduling sequence of the cooperation model is obtained through a genetic algorithm.
Wherein, the fitness function in the genetic algorithm is:
wherein ω is a cooperative model scheduling threshold;
U i g for the running cost function of the ith unmanned vehicle when using the g-th strategy, U i A minimum running cost function for the ith unmanned vehicle;
when the condition in the fitness function is satisfied, the optimal scheduling ordering is achieved.
Furthermore, when each unmanned vehicle entering the parking lot is in communication connection, the unmanned vehicle and the dispatching center are in real-time communication, so that the rapid transmission and processing of data are realized, and the communication of the unmanned vehicle is encrypted, data backup and battery capacity monitoring are performed.
Furthermore, when the opposite side is positioned, the unmanned vehicle is provided with a global positioning system, a laser radar and a vehicle-mounted camera to realize positioning, and the unmanned vehicle monitors traffic flow in real time by acquiring monitoring data of traffic monitoring facilities in road running.
According to another aspect of the present invention, there is provided a vehicle dispatch management system for unmanned vehicles, the system including a dispatch preparation module, a road travel dispatch module, a parking dispatch module, and a status monitoring module.
The scheduling preparation module is used for acquiring task priority and constraint conditions of the unmanned vehicle.
The road driving scheduling module is used for controlling the unmanned vehicle to reach the destination according to the pre-planned driving path and the starting time of the unmanned vehicle.
The parking scheduling module is used for detecting vehicles in a parking lot of a destination, acquiring parking spaces of the unmanned vehicles and automatically parking the unmanned vehicles into the parking spaces based on parking rules.
The state monitoring module is used for monitoring the vehicle and the task in real time, acquiring the real-time state of the vehicle and the task, and monitoring and processing abnormal conditions in real time.
The beneficial effects of the invention are as follows:
(1) The unmanned vehicle dispatching management method and system provided by the invention have the advantages that the vehicle transportation is more efficient, safer and more reliable, and the transportation benefit and the competitiveness of enterprises are improved; the invention makes full use of traffic monitoring facilities, a global positioning system, a laser radar and a vehicle-mounted camera, so that the distance and the positioning between unmanned vehicles can be judged.
(2) According to the invention, when the unmanned vehicle is parked, the size of the unmanned vehicle is obtained, the unmanned vehicle is determined to be in a proper parking space, and meanwhile, when the size of the unmanned vehicle cannot be obtained, the related vehicle can be accurately measured through the binocular camera, so that the vehicle without size data can be arranged to be in the proper parking space, automatic measurement is realized, and the parking efficiency is improved.
(3) According to the invention, the scheduling and sequencing of the minimum total running cost of all unmanned vehicles are realized through the cooperation model, so that a plurality of vehicles are intelligently and efficiently scheduled and parked, and the total efficiency is further optimized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for unmanned vehicle dispatch management according to an embodiment of the present invention;
fig. 2 is a functional block diagram of a vehicle dispatch management system for use in unmanned vehicles in accordance with an embodiment of the present invention.
In the figure:
1. a scheduling preparation module; 2. a road travel scheduling module; 3. a parking scheduling module; 4. and a state monitoring module.
Detailed Description
For the purpose of further illustrating the various embodiments, the present invention provides the accompanying drawings, which are a part of the disclosure of the present invention, and which are mainly used to illustrate the embodiments and, together with the description, serve to explain the principles of the embodiments, and with reference to these descriptions, one skilled in the art will recognize other possible implementations and advantages of the present invention, wherein elements are not drawn to scale, and like reference numerals are generally used to designate like elements.
According to an embodiment of the invention, a vehicle dispatching management method and system for unmanned vehicles are provided.
The invention will now be further described with reference to the drawings and detailed description, as shown in fig. 1, according to one embodiment of the invention, there is provided a vehicle dispatch management method for unmanned vehicles, the method comprising the steps of:
s1, acquiring task priority and constraint conditions of an unmanned vehicle;
wherein the constraint includes the following:
number of unmanned vehicles: the number of vehicles needs to be reasonably arranged according to the relation between the task amount and the number of vehicles, the vehicle operation cost, the usability and other factors.
Load capacity of each unmanned vehicle: the load capacity of the vehicle needs to be reasonably arranged according to the task type and task requirements in the scheduling scene.
Range of unmanned vehicle: because unmanned vehicles generally belong to electric vehicles, the endurance mileage of the unmanned vehicles is an important constraint condition, and the driving route and the charging station of the vehicles need to be reasonably arranged according to task demands and scheduling scenes so as to ensure that the vehicles can complete tasks and return to a base.
Traffic regulations and restriction regulations: the unmanned vehicles need to follow traffic rules on roads, including traffic lights, lanes, speed limits and other rules, and also need to pass through the unmanned vehicles on the road sections allowed to run according to the rules.
Environmental safety: environmental safety needs to be considered, for example, to avoid vehicle operation in case of bad weather or road conditions.
In one embodiment, the acquiring task priority and constraint conditions of the unmanned vehicle includes the steps of:
s11, before the unmanned vehicle is dispatched, the dispatching requirements and constraint conditions of the unmanned vehicle are defined, and a dispatching scene is obtained;
s12, collecting task destinations, driving paths and starting time of scheduling tasks according to the obtained scheduling scene to obtain task information;
and S13, determining the number of the unmanned vehicles, the load capacity and the endurance mileage according to the scheduling scene and the task information.
S2, controlling the unmanned vehicle to reach a destination according to a pre-planned driving path and starting time of the unmanned vehicle;
s3, detecting the vehicle in a parking lot of a destination, obtaining a parking space of the unmanned vehicle, and automatically parking the unmanned vehicle into the parking space based on a parking rule; the parking rules are internal traffic rules defined by a parking lot, such as: entrance regulations, driving direction regulations, driving speed regulations, etc.
In one embodiment, the vehicle detection in the parking lot at the destination, and the obtaining the parking space of the unmanned vehicle includes the following steps:
setting a binocular camera for shooting measurement at a parking lot entrance of a destination, and calibrating the binocular camera in advance;
sending a request for acquiring the size information of the unmanned vehicle, and if the size information of the unmanned vehicle is fed back, determining a parking space of the unmanned vehicle according to the size information;
if the size information of the unmanned vehicle cannot be obtained through feedback, the unmanned vehicle is driven into the measuring area;
performing size measurement on the unmanned vehicle in the measurement area according to the calibrated binocular camera;
and after the size measurement is completed, determining the parking space of the unmanned vehicle according to the measured size information of the unmanned vehicle.
The binocular stereo vision is an imaging principle imitating human binocular vision, two cameras shoot the same scene at the same time, and then two images are fused into a three-dimensional image through a computer algorithm, so that the perception of the distance and depth of an object is realized.
In one embodiment, the measuring the size of the unmanned vehicle in the measuring area according to the calibrated binocular camera comprises the following steps:
the binocular camera is provided with two camera coordinate systems, two unmanned vehicle images are obtained from different positions through the calibrated binocular camera, and projection points on the two unmanned vehicle images are obtained;
acquiring any point P on unmanned vehicle w And obtain point P w Optical axis coordinates in two camera coordinate systems of the binocular camera, and homogeneous coordinates of two projection points under respective coordinate systems and points P are obtained simultaneously w Homogeneous coordinates in world coordinate system;
the method comprises the steps of calibrating and giving a projective transformation matrix when a binocular camera shoots two unmanned vehicle images, combining the projective transformation matrix with a linear theory of camera imaging, and utilizing two optical axis coordinates, homogeneous coordinates of two projection points under respective coordinate systems and a point P w Obtaining straight lines passing through two groups of optical center points and projection points in the binocular camera by homogeneous coordinates under a world coordinate system, and obtaining point P w Is the intersection of two straight lines, and the point P is obtained w Is a three-dimensional coordinate of (2);
and determining three-dimensional coordinates of each vertex on the unmanned vehicle, and calculating to obtain the three-dimensional data size of the unmanned vehicle.
In one embodiment, when the binocular camera for image capturing measurement is set at the entrance of the parking lot of the destination and the binocular camera is calibrated in advance, a square pattern with regular arrangement is used as a calibration plate, the size of the square is known, and the vertex of the square is used as a calibration reference point.
In one embodiment, the automatically parking the unmanned vehicle into the parking space based on the parking rule includes the steps of:
carrying out communication connection on each unmanned vehicle entering a parking lot, and acquiring the positioning of the other party;
enabling each unmanned vehicle to drive to a target parking space according to a shortest path principle;
calculating the total running cost of all unmanned vehicles:
U N ＝∑ i∈N U i (s i )
wherein s is i A policy set for the ith unmanned vehicle;
U i minimum running cost function for ith unmanned vehicle, U N The running cost function of all unmanned vehicles is adopted, and N is a non-zero natural number;
all unmanned vehicles cooperate, and the scheduling order with the lowest total running cost is obtained according to a cooperation model:
wherein P is the total running cost obtained by cooperation of all unmanned vehicles;
s i a policy set for the ith unmanned vehicle;
U i minimum running cost function for ith unmanned vehicle, N is a non-zero natural number
σ is the initial scheduling order and,
a running cost function ordered for the initial schedule of the ith unmanned vehicle.
In one embodiment, when the scheduling sequence with the lowest total running cost is obtained through calculation, the optimal scheduling sequence of the cooperation model is obtained through a genetic algorithm; the genetic algorithm is an optimization algorithm simulating natural evolution, and the optimal solution or near optimal solution of the problem is found by simulating basic operations such as inheritance, crossover, mutation and the like in biological evolution.
Wherein, the fitness function in the genetic algorithm is:
wherein ω is a cooperative model scheduling threshold;
U i g for the running cost function of the ith unmanned vehicle when using the g-th strategy, U i A minimum running cost function for the ith unmanned vehicle;
when the condition in the fitness function is satisfied, the optimal scheduling ordering is achieved.
In one embodiment, when each unmanned vehicle entering the parking lot is in communication connection, the unmanned vehicle and the dispatching center communicate in real time, so that rapid data transmission and processing are realized, and the communication of the unmanned vehicle is encrypted, data backup and battery capacity monitoring are performed.
The unmanned vehicle communication generally adopts various traffic technologies, and utilizes the Bluetooth technology to carry out short-distance wireless communication or wireless local area network communication in short distance. When the mobile communication network is used for wireless communication in long distance, the mobile communication network has the advantages of stable signal and wide coverage range, but the problems of network congestion, signal interference and the like can influence the communication quality.
In one embodiment, when the position of the opposite side is obtained, the unmanned vehicle is provided with a global positioning system, a laser radar and a vehicle-mounted camera to realize the position, and the unmanned vehicle monitors the traffic flow in real time by obtaining the monitoring data of the traffic monitoring facility in the road running process.
And S4, monitoring the vehicle and the task in real time, acquiring the real-time state of the vehicle and the task, and monitoring and processing the abnormal situation in real time. For example: alarming after the fault of the vehicle is monitored, adjusting the parking plan when insufficient endurance mileage is monitored, and the like.
As shown in fig. 2, according to another embodiment of the present invention, a vehicle schedule management system for unmanned vehicles is disclosed, which includes a schedule preparation module 1, a road driving schedule module 2, a parking schedule module 3, and a state monitoring module 4.
The scheduling preparation module 1 is configured to obtain task priority and constraint conditions of an unmanned vehicle.
The road driving dispatching module 2 is configured to control the unmanned vehicle to reach the destination according to a pre-planned driving path and a start time of the unmanned vehicle.
The parking scheduling module 3 is configured to detect a vehicle in a parking lot at a destination, obtain a parking space of the unmanned vehicle, and automatically park the unmanned vehicle into the parking space based on a parking rule.
The state monitoring module 4 is used for monitoring the vehicle and the task in real time, acquiring the real-time state of the vehicle and the task, and monitoring and processing the abnormal situation in real time.
In summary, by means of the technical scheme, the vehicle dispatching management method and system for unmanned vehicles enable vehicle transportation to be more efficient, safe and reliable, and improve transportation benefits and competitiveness of enterprises; the invention makes full use of traffic monitoring facilities, a global positioning system, a laser radar and a vehicle-mounted camera, so that the distance and the positioning between unmanned vehicles can be judged. According to the invention, when the unmanned vehicle is parked, the size of the unmanned vehicle is obtained, the unmanned vehicle is controlled to a proper parking space, and meanwhile, when the size of the unmanned vehicle cannot be obtained, the related vehicle can be accurately measured through the binocular camera, so that the vehicle without size data can be arranged to the proper parking space, automatic measurement is realized, and the parking efficiency is improved. According to the invention, the scheduling and sequencing of the minimum total running cost of all unmanned vehicles are realized through the cooperation model, so that a plurality of vehicles are intelligently and efficiently scheduled and parked, and the total efficiency is further optimized.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (10)
1. A vehicle dispatch management method for unmanned vehicles, the method comprising the steps of:
s1, acquiring task priority and constraint conditions of an unmanned vehicle;
s2, controlling the unmanned vehicle to reach a destination according to a pre-planned driving path and starting time of the unmanned vehicle;
s3, detecting the vehicle in a parking lot of a destination, obtaining a parking space of the unmanned vehicle, and automatically parking the unmanned vehicle into the parking space based on a parking rule;
and S4, monitoring the vehicle and the task in real time, acquiring the real-time state of the vehicle and the task, and monitoring and processing the abnormal situation in real time.
2. The method for unmanned vehicle dispatch management of claim 1, wherein the acquiring task priority and constraints of the unmanned vehicle comprises the steps of:
s11, before the unmanned vehicle is dispatched, the dispatching requirements and constraint conditions of the unmanned vehicle are defined, and a dispatching scene is obtained;
s12, collecting task destinations, driving paths and starting time of scheduling tasks according to the obtained scheduling scene to obtain task information;
and S13, determining the number of the unmanned vehicles, the load capacity and the endurance mileage according to the scheduling scene and the task information.
3. The vehicle dispatching management method for unmanned vehicles according to claim 2, wherein the vehicle detection at the parking lot of the destination, the acquisition of the parking space of the unmanned vehicle, comprises the steps of:
setting a binocular camera for shooting measurement at a parking lot entrance of a destination, and calibrating the binocular camera in advance;
sending a request for acquiring the size information of the unmanned vehicle, and if the size information of the unmanned vehicle is fed back, determining a parking space of the unmanned vehicle according to the size information;
if the size information of the unmanned vehicle cannot be obtained through feedback, the unmanned vehicle is driven into the measuring area;
performing size measurement on the unmanned vehicle in the measurement area according to the calibrated binocular camera;
and after the size measurement is completed, determining the parking space of the unmanned vehicle according to the measured size information of the unmanned vehicle.
4. A vehicle dispatch management method for an unmanned vehicle according to claim 3, wherein the sizing of the unmanned vehicle in the measurement area according to the calibrated binocular camera comprises the steps of:
acquiring two unmanned vehicle images from different positions through the calibrated binocular camera, and obtaining projection points on the two unmanned vehicle images;
acquiring any point P on unmanned vehicle w And obtain point P w Optical axis coordinates in two camera coordinate systems of the binocular camera, and homogeneous coordinates of two projection points under respective coordinate systems and points P are obtained simultaneously w Homogeneous coordinates in world coordinate system;
calibrating and giving a projective transformation matrix when the binocular camera shoots two unmanned vehicle images, and combining the projective transformation matrix with the imagesLinear theory combination of machine imaging and utilizes two optical axis coordinates, homogeneous coordinates of two projection points in respective coordinate systems and point P w Obtaining straight lines passing through two groups of optical center points and projection points in the binocular camera by homogeneous coordinates under a world coordinate system, and obtaining point P w Is the intersection of two straight lines, and the point P is obtained w Is a three-dimensional coordinate of (2);
and determining three-dimensional coordinates of each vertex on the unmanned vehicle, and calculating to obtain the three-dimensional data size of the unmanned vehicle.
5. The method according to claim 4, wherein a binocular camera for image capturing measurement is provided at an entrance of a parking lot at a destination, and when the binocular camera is calibrated in advance, a square pattern with regular arrangement is used as a calibration plate, and the size of the square is known, and the vertex thereof is used as a reference point for calibration.
6. The vehicle dispatching management method for unmanned vehicles according to claim 5, wherein automatically parking the unmanned vehicle into the space based on the parking rule comprises the steps of:
carrying out communication connection on each unmanned vehicle entering a parking lot, and acquiring the positioning of the other party;
enabling each unmanned vehicle to drive to a target parking space according to a shortest path principle;
calculating the total running cost of all unmanned vehicles:
U N ＝∑ i∈N U i (S i )
wherein s is i A policy set for the ith unmanned vehicle;
U i minimum running cost function for ith unmanned vehicle, U N The running cost function of all unmanned vehicles is adopted, and N is a non-zero natural number;
all unmanned vehicles cooperate, and the scheduling order with the lowest total running cost is obtained according to a cooperation model:
wherein P is the total running cost obtained by cooperation of all unmanned vehicles;
s i a policy set for the ith unmanned vehicle;
U i for the smallest running cost function of the ith unmanned vehicle, N is a non-zero natural number,
σ is the initial scheduling order and,
a running cost function ordered for the initial schedule of the ith unmanned vehicle.
7. The method for unmanned vehicle scheduling management according to claim 6, wherein when the scheduling order with the lowest total running cost is obtained by calculation, the optimal scheduling order of the cooperation model is obtained by a genetic algorithm;
wherein, the fitness function in the genetic algorithm is:
wherein ω is a cooperative model scheduling threshold;
when the condition in the fitness function is satisfied, the optimal scheduling ordering is achieved.
8. The method for managing the unmanned vehicle dispatching of claim 7, wherein when each unmanned vehicle entering the parking lot is in communication connection, the unmanned vehicle and the dispatching center communicate in real time, so that the data can be quickly transmitted and processed, and the communication of the unmanned vehicle is encrypted, data backup and battery capacity monitoring are performed.
9. The method for managing unmanned vehicle dispatching according to claim 8, wherein the GPS, the laser radar and the onboard camera are installed on the unmanned vehicle to realize positioning when the positioning of the other party is obtained, and the traffic flow is monitored in real time by obtaining the monitoring data of the traffic monitoring facility while the unmanned vehicle is running on the road.
10. A vehicle dispatch management system for unmanned vehicles for implementing the vehicle dispatch management method for unmanned vehicles of any one of claims 1-9, characterized in that the system comprises a dispatch preparation module, a road travel dispatch module, a parking dispatch module, and a status monitoring module;
the scheduling preparation module is used for acquiring task priority and constraint conditions of the unmanned vehicle;
the road traveling scheduling module is used for controlling the unmanned vehicle to reach a destination according to a pre-planned traveling path and starting time of the unmanned vehicle;
the parking scheduling module is used for detecting vehicles in a parking lot of a destination, acquiring parking spaces of the unmanned vehicles and automatically parking the unmanned vehicles into the parking spaces based on parking rules;
the state monitoring module is used for monitoring the vehicle and the task in real time, acquiring the real-time state of the vehicle and the task, and monitoring and processing abnormal conditions in real time.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116757459A (en) * | 2023-08-22 | 2023-09-15 | 苏州观瑞汽车技术有限公司 | Intelligent scheduling scheme for automatic driving taxies and comprehensive evaluation method and system |
| CN117035369A (en) * | 2023-10-08 | 2023-11-10 | 上海伯镭智能科技有限公司 | Intelligent scheduling method for unmanned vehicle resources |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116757459A (en) * | 2023-08-22 | 2023-09-15 | 苏州观瑞汽车技术有限公司 | Intelligent scheduling scheme for automatic driving taxies and comprehensive evaluation method and system |
| CN116757459B (en) * | 2023-08-22 | 2023-12-01 | 苏州观瑞汽车技术有限公司 | Intelligent scheduling scheme for automatic driving taxies and comprehensive evaluation method and system |
| CN117035369A (en) * | 2023-10-08 | 2023-11-10 | 上海伯镭智能科技有限公司 | Intelligent scheduling method for unmanned vehicle resources |
| CN117035369B (en) * | 2023-10-08 | 2023-12-22 | 上海伯镭智能科技有限公司 | Intelligent scheduling method for unmanned vehicle resources |
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