Rule-integrated unmanned container truck intersection cooperation method and system, and storage medium
By building a vehicle crossing rule model based on time-dependent and spatial dependence, combined with the intersection collaborative pass model, the problems of slow traffic speed and task delay at port intersections are solved, and efficient port operations are achieved.
Patent Information
- Application Number
- CN202411838092.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-13
- Publication Date
- 2025-03-25
AI Technical Summary
Unmanned gatherings are prone to congestion or collision when passing through port intersections, which affects the port operation efficiency, and the delay in completing difficult tasks will affect subsequent operation tasks.
The unmanned cab-collection intersection collaboration method adopts a comprehensive rule, and predicts vehicle traffic rules by building a time-dependent and space-dependent vehicle traffic intersection rule model, and constructs a collaborative crossing model to schedule unmanned cab-collection cards in real time to improve the pass speed and task completion efficiency.
The speed of unmanned lock-up cards passing through port intersections has been improved, the delay in completing difficult tasks has been avoided, and the port operation efficiency and task completion have been improved.
Smart Images
Figure CN119694121A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of unmanned truck collection, and in particular to an unmanned truck collection intersection coordination method, system and storage medium with comprehensive rules. Background Art
[0002] With the continuous development of autonomous driving technology, the number of unmanned container trucks used in port operations is increasing. When unmanned container trucks pass through intersections, congestion or collisions are likely to occur, which will affect the port's operating efficiency. At the same time, each unmanned container truck in the port has different tasks. The completion of more difficult tasks takes more time than lighter tasks. In the case of passing intersections, it is possible that more difficult tasks will be delayed for a long time before completion, thereby affecting subsequent port operations. Therefore, how to control and optimize the intersection coordination of unmanned container trucks has become a problem that we urgently need to solve. Summary of the invention
[0003] In view of the above problems, the present invention provides a comprehensive rule-based unmanned container truck intersection coordination method, system and storage medium, which can not only improve the speed of unmanned container trucks passing through the intersection of the port, but also solve the problem that difficult tasks may be delayed for a long time before completion, thereby affecting subsequent port operations.
[0004] In order to achieve the above-mentioned purpose and other related purposes, the technical solution provided by the present invention is as follows:
[0005] A comprehensive rule-based unmanned truck intersection coordination method, the method comprising:
[0006] U1. When an unmanned container truck drives to an intersection while performing an operation task at a port, it collects data information about the vehicle's historical operation trajectory, and obtains data information about the vehicle's movement status, the degree of completion of the vehicle's operation task, and the traffic conditions at the intersection in real time;
[0007] U2. Based on the data information of the historical operation trajectory of the vehicle, the data information of the completion degree of the vehicle's execution of the operation task and the data information of the traffic conditions at the intersection, a rule model of the vehicle passing intersection based on time dependence is constructed, and the first rule of the vehicle passing intersection is predicted to obtain data information of the first rule of the vehicle passing intersection;
[0008] U3. Based on the data information of the historical operation trajectory of the vehicle, the data information of the movement state of the vehicle and the data information of the traffic condition of the intersection, a rule model of the vehicle traffic intersection based on space dependence is constructed, and the second rule of the vehicle traffic intersection is predicted to obtain data information of the second rule of the vehicle traffic intersection;
[0009] U4. Based on the data information of the first rule of the vehicle traffic intersection and the data information of the second rule of the vehicle traffic intersection, a vehicle intersection collaborative passing model is constructed, the vehicle traffic status is planned, and the data information of the planned vehicle traffic status is obtained.
[0010] Furthermore, in step U2, the construction of a rule model for a vehicle traffic intersection based on time dependence and the prediction of a first rule for a vehicle traffic intersection include:
[0011] U21. Based on the data information of the historical operation trajectory of the vehicle and the data information of the completion degree of the vehicle's operation task, establish a time-dependent first pass function Q of the vehicle,
[0012]
[0013] Among them, x1 is the data information of the historical operation trajectory of the vehicle, x2 is the data information of the completion degree of the vehicle's execution of the operation task, x3 is the data information of the traffic conditions at the intersection, α1, α2 and α3 are the first time-dependent factors of the vehicle's passage, and the time-dependent first passage state of the vehicle is characterized to obtain the data information of the time-dependent first passage state of the vehicle;
[0014] U22. Based on the data information of the degree of completion of the vehicle's task execution and the data information of the traffic conditions at the intersection, establish a time-dependent second traffic function W of the vehicle,
[0015]
[0016] Among them, x2 is the data information of the completion degree of the vehicle's execution task, x3 is the data information of the traffic conditions at the intersection, β1, β2 and β3 are the second time-dependent factors of the vehicle's passage, and the time-dependent second passage state of the vehicle is characterized to obtain the data information of the time-dependent second passage state of the vehicle;
[0017] U23. Based on the data information of the time-dependent second traffic state of the vehicle and the data information of the time-dependent first traffic state of the vehicle, a rule function R of the vehicle traffic intersection is established,
[0018]
[0019] Among them, z1 is the data information of the time-dependent first traffic state of the vehicle, z2 is the data information of the time-dependent second traffic state of the vehicle, δ1, δ2 and δ3 are the time rule factors of the vehicle intersection, and the first rule of the vehicle intersection is predicted to obtain the data information of the first rule of the vehicle intersection.
[0020] Furthermore, the time rule factors δ1, δ2 and δ3 of the vehicle traffic intersection are:
[0021] Among them, z1 is the data information of the time-dependent first traffic state of the vehicle, and z2 is the data information of the time-dependent second traffic state of the vehicle.
[0022] Furthermore, the constraints of the second time-dependent factors β1, β2 and β3 of the vehicle passage are:
[0023]
[0024] The constraint function f of the first time dependent factors α1, α2 and α3 of the vehicle traffic is,
[0025] The value range of the constraint function f is (2,3).
[0026] Furthermore, in step U3, the construction of a rule model for a vehicle intersection based on spatial dependence and the prediction of a second rule for the vehicle intersection include:
[0027] U31. Based on the data information of the historical operation trajectory of the vehicle and the data information of the motion state of the vehicle, establish the first pass function P of the vehicle's dependent space,
[0028]
[0029] Among them, x1 is the data information of the historical operation trajectory of the vehicle, x4 is the data information of the vehicle's motion state, γ1, γ2 and γ3 are the first spatial dependency factors of the vehicle's passage, which characterize the first spatial constraint state of the vehicle's passage and obtain the data information of the first spatial constraint state of the vehicle's passage;
[0030] U32. Based on the data information of the vehicle motion state and the data information of the traffic conditions at the intersection, establish a second space-dependent function S of the vehicle,
[0031]
[0032] Among them, x3 is the data information of the traffic conditions at the intersection, x4 is the data information of the vehicle movement state, η1, η2 and η3 are the second spatial dependency factors of vehicle traffic, which characterize the second spatial constraint state of vehicle traffic and obtain the data information of the second spatial constraint state of vehicle traffic;
[0033] U33. Based on the data information of the second space constraint state of the vehicle passage and the data information of the first space constraint state of the vehicle passage, establish a second rule function F for the vehicle passage intersection,
[0034]
[0035] Among them, r1 is the data information of the first spatial constraint state of vehicle passage, r2 is the data information of the second spatial constraint state of vehicle passage, λ1, λ2 and λ3 are the spatial constraint rule factors of vehicle passage, and the second rule of the vehicle passage intersection is predicted to obtain the data information of the second rule of the vehicle passage intersection.
[0036] Furthermore, the constraints of the vehicle passage space constraint rule factors λ1, λ2 and λ3 are as follows:
[0037]
[0038] Furthermore, in step U4, the construction of the intersection cooperative passing model of vehicles and the planning of the traffic status of vehicles include:
[0039] U41. Based on the data information of the first rule of the vehicle crossing and the data information of the second rule of the vehicle crossing, establish a comprehensive rule function G of the vehicle crossing,
[0040]
[0041] Among them, q1 is the data information of the first rule of the vehicle-passing intersection, q2 is the data information of the second rule of the vehicle-passing intersection, μ1, μ2 and μ3 are weight coefficients of the vehicle-passing intersection, and the comprehensive rule of the vehicle-passing intersection is characterized to obtain the data information of the comprehensive rule of the vehicle-passing intersection;
[0042] U42. Based on the data information of the comprehensive rules of the vehicle passing through the intersection, establish the coordinated passing function H of the vehicle at the intersection,
[0043]
[0044] Among them, h is the data information of the comprehensive rules of vehicle traffic intersections, ρ1, ρ2 and ρ3 are the planning factors for the coordinated passage of vehicles at intersections;
[0045] U43. Based on the coordinated passing function H of the vehicle at the intersection, the traffic status of the vehicle is planned to obtain data information of the planned traffic status of the vehicle.
[0046] Furthermore, the planning factors ρ1, ρ2 and ρ3 for the coordinated passage of the vehicles at the intersection are:
[0047]
[0048] Among them, h is the data information of the comprehensive rules for vehicle traffic intersections.
[0049] In order to achieve the above-mentioned objectives and other related objectives, the present invention also provides an unmanned truck intersection coordination system with comprehensive rules, including a computer device, which is programmed or configured to execute the steps of any one of the unmanned truck intersection coordination methods with comprehensive rules.
[0050] In order to achieve the above-mentioned purpose and other related purposes, the present invention also provides a computer-readable storage medium, on which is stored a computer program programmed or configured to execute any one of the comprehensive rules of the unmanned truck intersection coordination method.
[0051] The present invention has the following positive effects:
[0052] 1. The present invention predicts the first rule of the vehicle intersection by constructing a rule model of the vehicle intersection based on time dependence, and predicts the second rule of the vehicle intersection by combining the rule model of the vehicle intersection based on space dependence. It can not only flexibly dispatch the unmanned container truck according to the vehicle movement state and the situation of the intersection in real time, thereby improving the speed of the unmanned container truck passing through the intersection, but also solves the problem that a difficult task may be delayed for a long time before completion, thereby affecting the subsequent port operation tasks.
[0053] 2. The present invention plans the traffic status of vehicles by constructing a coordinated intersection passage model for vehicles. It can not only adjust and plan the coordinated intersection passage of vehicles according to the comprehensive rules of vehicles, thereby ensuring the safe passage of vehicles through intersections, but also make adaptive adjustments according to different traffic conditions, thereby improving the operating efficiency of unmanned container trucks. BRIEF DESCRIPTION OF THE DRAWINGS
[0054] Figure 1 It is a schematic diagram of the method flow of the present invention;
[0055] Figure 2 A schematic diagram of a process of constructing a rule model for a vehicle traffic intersection based on time dependence according to the present invention;
[0056] Figure 3 A schematic diagram of a flow chart of constructing a rule model for a vehicle traffic intersection based on space dependence according to the present invention;
[0057] Figure 4 The present invention is a flow chart of constructing a vehicle cooperative intersection passing model. DETAILED DESCRIPTION
[0058] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.
[0059] Example 1: Figure 1 As shown, a comprehensive rule-based unmanned truck intersection coordination method comprises:
[0060] U1. When an unmanned container truck drives to an intersection while performing an operation task at a port, it collects data information about the vehicle's historical operation trajectory, and obtains data information about the vehicle's movement status, the degree of completion of the vehicle's operation task, and the traffic conditions at the intersection in real time;
[0061] U2. Based on the data information of the historical operation trajectory of the vehicle, the data information of the completion degree of the vehicle's execution of the operation task and the data information of the traffic conditions at the intersection, a rule model of the vehicle passing intersection based on time dependence is constructed, and the first rule of the vehicle passing intersection is predicted to obtain data information of the first rule of the vehicle passing intersection;
[0062] U3. Based on the data information of the historical operation trajectory of the vehicle, the data information of the movement state of the vehicle and the data information of the traffic condition of the intersection, a rule model of the vehicle traffic intersection based on space dependence is constructed, and the second rule of the vehicle traffic intersection is predicted to obtain data information of the second rule of the vehicle traffic intersection;
[0063] U4. Based on the data information of the first rule of the vehicle traffic intersection and the data information of the second rule of the vehicle traffic intersection, a vehicle intersection collaborative passing model is constructed, the vehicle traffic status is planned, and the data information of the planned vehicle traffic status is obtained.
[0064] In this embodiment, if Figure 2 As shown, in step U2, the construction of a rule model for a vehicle traffic intersection based on time dependence and the prediction of a first rule for a vehicle traffic intersection include:
[0065] U21. Based on the data information of the historical operation trajectory of the vehicle and the data information of the completion degree of the vehicle's operation task, establish a time-dependent first pass function Q of the vehicle,
[0066]
[0067] Among them, x1 is the data information of the historical operation trajectory of the vehicle, x2 is the data information of the completion degree of the vehicle's execution of the operation task, x3 is the data information of the traffic conditions at the intersection, α1, α2 and α3 are the first time-dependent factors of the vehicle's passage, and the time-dependent first passage state of the vehicle is characterized to obtain the data information of the time-dependent first passage state of the vehicle;
[0068] U22. Based on the data information of the degree of completion of the vehicle's task execution and the data information of the traffic conditions at the intersection, establish a time-dependent second traffic function W of the vehicle,
[0069]
[0070] Among them, x2 is the data information of the completion degree of the vehicle's execution task, x3 is the data information of the traffic conditions at the intersection, β1, β2 and β3 are the second time-dependent factors of the vehicle's passage, and the time-dependent second passage state of the vehicle is characterized to obtain the data information of the time-dependent second passage state of the vehicle;
[0071] U23. Based on the data information of the time-dependent second traffic state of the vehicle and the data information of the time-dependent first traffic state of the vehicle, a rule function R of the vehicle traffic intersection is established,
[0072]
[0073] Among them, z1 is the data information of the time-dependent first traffic state of the vehicle, z2 is the data information of the time-dependent second traffic state of the vehicle, δ1, δ2 and δ3 are the time rule factors of the vehicle intersection, and the first rule of the vehicle intersection is predicted to obtain the data information of the first rule of the vehicle intersection.
[0074] In this embodiment, the time rule factors δ1, δ2 and δ3 of the vehicle traffic intersection are:
[0075]
[0076]
[0077] Among them, z1 is the data information of the time-dependent first traffic state of the vehicle, and z2 is the data information of the time-dependent second traffic state of the vehicle.
[0078] In this embodiment, the constraint conditions of the second time-dependent factors β1, β2 and β3 of the vehicle passage are:
[0079]
[0080] The constraint function f of the first time dependent factors α1, α2 and α3 of the vehicle traffic is,
[0081] The value range of the constraint function f is (2,3).
[0082] Example 2: Based on the unmanned truck intersection coordination method with comprehensive rules in Example 1, the present invention is further illustrated and described below.
[0083] like Figure 1 As shown, a comprehensive rule-based unmanned truck intersection coordination method comprises:
[0084] U1. When an unmanned container truck drives to an intersection while performing an operation task at a port, it collects data information about the vehicle's historical operation trajectory, and obtains data information about the vehicle's movement status, the degree of completion of the vehicle's operation task, and the traffic conditions at the intersection in real time;
[0085] U2. Based on the data information of the historical operation trajectory of the vehicle, the data information of the completion degree of the vehicle's execution of the operation task and the data information of the traffic conditions at the intersection, a rule model of the vehicle passing intersection based on time dependence is constructed, and the first rule of the vehicle passing intersection is predicted to obtain data information of the first rule of the vehicle passing intersection;
[0086] U3. Based on the data information of the historical operation trajectory of the vehicle, the data information of the movement state of the vehicle and the data information of the traffic condition of the intersection, a rule model of the vehicle traffic intersection based on space dependence is constructed, and the second rule of the vehicle traffic intersection is predicted to obtain data information of the second rule of the vehicle traffic intersection;
[0087] U4. Based on the data information of the first rule of the vehicle traffic intersection and the data information of the second rule of the vehicle traffic intersection, a vehicle intersection collaborative passing model is constructed, the vehicle traffic status is planned, and the data information of the planned vehicle traffic status is obtained.
[0088] In this embodiment, if Figure 3 As shown, in step U3, the construction of a rule model for a vehicle intersection based on spatial dependence and the prediction of a second rule for the vehicle intersection include:
[0089] U31. Based on the data information of the historical operation trajectory of the vehicle and the data information of the motion state of the vehicle, establish the first pass function P of the vehicle's dependent space,
[0090]
[0091] Among them, x1 is the data information of the historical operation trajectory of the vehicle, x4 is the data information of the vehicle's motion state, γ1, γ2 and γ3 are the first spatial dependency factors of the vehicle's passage, which characterize the first spatial constraint state of the vehicle's passage and obtain the data information of the first spatial constraint state of the vehicle's passage;
[0092] U32. Based on the data information of the vehicle motion state and the data information of the traffic conditions at the intersection, establish a second space-dependent function S of the vehicle,
[0093]
[0094] Among them, x3 is the data information of the traffic conditions at the intersection, x4 is the data information of the vehicle movement state, η1, η2 and η3 are the second spatial dependency factors of vehicle traffic, which characterize the second spatial constraint state of vehicle traffic and obtain the data information of the second spatial constraint state of vehicle traffic;
[0095] U33. Based on the data information of the second space constraint state of the vehicle passage and the data information of the first space constraint state of the vehicle passage, establish a second rule function F for the vehicle passage intersection,
[0096]
[0097] Among them, r1 is the data information of the first spatial constraint state of vehicle passage, r2 is the data information of the second spatial constraint state of vehicle passage, λ1, λ2 and λ3 are the spatial constraint rule factors of vehicle passage, and the second rule of the vehicle passage intersection is predicted to obtain the data information of the second rule of the vehicle passage intersection.
[0098] In this embodiment, the constraints of the vehicle passage space constraint rule factors λ1, λ2 and λ3 are:
[0099]
[0100] In this embodiment, if Figure 4 As shown, in step U4, the construction of the intersection cooperative passing model of the vehicle and the planning of the vehicle's traffic state include:
[0101] U41. Based on the data information of the first rule of the vehicle crossing and the data information of the second rule of the vehicle crossing, establish a comprehensive rule function G of the vehicle crossing,
[0102]
[0103] Among them, q1 is the data information of the first rule of the vehicle-passing intersection, q2 is the data information of the second rule of the vehicle-passing intersection, μ1, μ2 and μ3 are weight coefficients of the vehicle-passing intersection, and the comprehensive rule of the vehicle-passing intersection is characterized to obtain the data information of the comprehensive rule of the vehicle-passing intersection;
[0104] U42. Based on the data information of the comprehensive rules of the vehicle passing through the intersection, establish the coordinated passing function H of the vehicle at the intersection,
[0105]
[0106] Among them, h is the data information of the comprehensive rules of vehicle traffic intersections, ρ1, ρ2 and ρ3 are the planning factors for the coordinated passage of vehicles at intersections;
[0107] U43. Based on the coordinated passing function H of the vehicle at the intersection, the traffic status of the vehicle is planned to obtain data information of the planned traffic status of the vehicle.
[0108] In this embodiment, the planning factors ρ1, ρ2 and ρ3 for the coordinated passage of the vehicles at the intersection are:
[0109]
[0110] Among them, h is the data information of the comprehensive rules for vehicle traffic intersections.
[0111] In this embodiment, the present invention provides an unmanned truck intersection coordination system with integrated rules, including a computer device, which is programmed or configured to execute the steps of any one of the unmanned truck intersection coordination methods with integrated rules.
[0112] In this embodiment, the present invention provides a computer-readable storage medium storing a computer program programmed or configured to execute any one of the integrated rule-based unmanned truck intersection coordination methods.
[0113] Any reference to memory, storage, database or other media used in the embodiments provided in the present application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM) and memory bus dynamic RAM (RDRAM).
[0114] In summary, the present invention can not only improve the speed of unmanned container trucks passing through the intersection of the port, but also solve the problem that difficult tasks may be delayed for a long time before completion, thereby affecting subsequent port operations.
[0115] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.
Claims
1. A comprehensive rule-based unmanned truck intersection coordination method, characterized in that: The method comprises: U1. When an unmanned container truck drives to an intersection while performing an operation task at a port, it collects data information about the vehicle's historical operation trajectory, and obtains data information about the vehicle's movement status, the degree of completion of the vehicle's operation task, and the traffic conditions at the intersection in real time; U2. Based on the data information of the historical operation trajectory of the vehicle, the data information of the completion degree of the vehicle's execution of the operation task and the data information of the traffic conditions at the intersection, a rule model of the vehicle passing intersection based on time dependence is constructed, and the first rule of the vehicle passing intersection is predicted to obtain data information of the first rule of the vehicle passing intersection; U3. Based on the data information of the historical operation trajectory of the vehicle, the data information of the movement state of the vehicle and the data information of the traffic condition of the intersection, a rule model of the vehicle traffic intersection based on space dependence is constructed, and the second rule of the vehicle traffic intersection is predicted to obtain data information of the second rule of the vehicle traffic intersection; U4. Based on the data information of the first rule of the vehicle traffic intersection and the data information of the second rule of the vehicle traffic intersection, a vehicle intersection collaborative passing model is constructed, the vehicle traffic status is planned, and the data information of the planned vehicle traffic status is obtained.
2. The integrated rule-based unmanned truck intersection coordination method according to claim 1 is characterized in that: In step U2, the construction of a rule model for a vehicle traffic intersection based on time dependence and the prediction of a first rule for a vehicle traffic intersection include: U21. Based on the data information of the historical operation trajectory of the vehicle and the data information of the completion degree of the vehicle's operation task, establish a time-dependent first pass function Q of the vehicle, Among them, x1 is the data information of the historical operation trajectory of the vehicle, x2 is the data information of the completion degree of the vehicle's execution of the operation task, x3 is the data information of the traffic conditions at the intersection, α1, α2 and α3 are the first time-dependent factors of the vehicle's passage, and the time-dependent first passage state of the vehicle is characterized to obtain the data information of the time-dependent first passage state of the vehicle; U22. Based on the data information of the degree of completion of the vehicle's task execution and the data information of the traffic conditions at the intersection, establish a time-dependent second traffic function W of the vehicle, Among them, x2 is the data information of the completion degree of the vehicle's execution task, x3 is the data information of the traffic conditions at the intersection, β1, β2 and β3 are the second time-dependent factors of the vehicle's passage, and the time-dependent second passage state of the vehicle is characterized to obtain the data information of the time-dependent second passage state of the vehicle; U23. Based on the data information of the time-dependent second traffic state of the vehicle and the data information of the time-dependent first traffic state of the vehicle, a rule function R of the vehicle traffic intersection is established, Among them, z1 is the data information of the time-dependent first traffic state of the vehicle, z2 is the data information of the time-dependent second traffic state of the vehicle, δ1, δ2 and δ3 are the time rule factors of the vehicle intersection, and the first rule of the vehicle intersection is predicted to obtain the data information of the first rule of the vehicle intersection.
3. The integrated rule-based unmanned truck intersection coordination method according to claim 2 is characterized by: The time rule factors δ1, δ2 and δ3 of the vehicle traffic intersection are: Among them, z1 is the data information of the time-dependent first traffic state of the vehicle, and z2 is the data information of the time-dependent second traffic state of the vehicle.
4. The integrated rule-based unmanned truck intersection coordination method according to claim 2 is characterized by: The constraint conditions of the second time-dependent factors β1, β2 and β3 of the vehicle passage are: The constraint function f of the first time dependent factors α1, α2 and α3 of the vehicle traffic is, The value range of the constraint function f is (2,3).
5. The integrated rule-based unmanned truck intersection coordination method according to claim 2 is characterized in that: In step U3, the construction of a rule model for a vehicle intersection based on spatial dependence and the prediction of a second rule for the vehicle intersection include: U31. Based on the data information of the historical operation trajectory of the vehicle and the data information of the motion state of the vehicle, establish the first pass function P of the vehicle's dependent space, Among them, x1 is the data information of the historical operation trajectory of the vehicle, x4 is the data information of the vehicle's motion state, γ1, γ2 and γ3 are the first spatial dependency factors of the vehicle's passage, which characterize the first spatial constraint state of the vehicle's passage and obtain the data information of the first spatial constraint state of the vehicle's passage; U32. Based on the data information of the vehicle motion state and the data information of the traffic conditions at the intersection, establish a second space-dependent function S of the vehicle, Among them, x3 is the data information of the traffic conditions at the intersection, x4 is the data information of the vehicle movement state, η1, η2 and η3 are the second spatial dependency factors of vehicle traffic, which characterize the second spatial constraint state of vehicle traffic and obtain the data information of the second spatial constraint state of vehicle traffic; U33. Based on the data information of the second space constraint state of the vehicle passage and the data information of the first space constraint state of the vehicle passage, establish a second rule function F for the vehicle passage intersection, Among them, r1 is the data information of the first spatial constraint state of vehicle passage, r2 is the data information of the second spatial constraint state of vehicle passage, λ1, λ2 and λ3 are the spatial constraint rule factors of vehicle passage, and the second rule of the vehicle passage intersection is predicted to obtain the data information of the second rule of the vehicle passage intersection.
6. The integrated rule-based unmanned truck intersection coordination method according to claim 5 is characterized by: The constraints of the vehicle passage space constraint rule factors λ1, λ2 and λ3 are:
7. The integrated rule-based unmanned truck intersection coordination method according to claim 1 is characterized in that: In step U4, the construction of the intersection cooperative passing model of vehicles and the planning of the traffic status of vehicles include: U41. Based on the data information of the first rule of the vehicle crossing and the data information of the second rule of the vehicle crossing, establish a comprehensive rule function G of the vehicle crossing, Among them, q1 is the data information of the first rule of the vehicle-passing intersection, q2 is the data information of the second rule of the vehicle-passing intersection, μ1, μ2 and μ3 are weight coefficients of the vehicle-passing intersection, and the comprehensive rule of the vehicle-passing intersection is characterized to obtain the data information of the comprehensive rule of the vehicle-passing intersection; U42. Based on the data information of the comprehensive rules of the vehicle passing through the intersection, establish the coordinated passing function H of the vehicle at the intersection, Among them, h is the data information of the comprehensive rules of vehicle traffic intersections, ρ1, ρ2 and ρ3 are the planning factors for the coordinated passage of vehicles at intersections; U43. Based on the coordinated passing function H of the vehicle at the intersection, the traffic status of the vehicle is planned to obtain data information of the planned traffic status of the vehicle.
8. The integrated rule-based unmanned truck intersection coordination method according to claim 7 is characterized by: The planning factors ρ1, ρ2 and ρ3 for the coordinated passage of the vehicles at the intersection are: Among them, h is the data information of the comprehensive rules for vehicle traffic intersections.
9. An integrated rule-based unmanned truck intersection coordination system, including computer equipment, characterized in that: The computer device is programmed or configured to execute the steps of the integrated rule-based unmanned truck intersection coordination method as described in any one of claims 1 to 8.
10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program programmed or configured to execute the unmanned truck intersection coordination method based on the comprehensive rules described in any one of claims 1 to 8.