Resource elastic allocation and barrier linkage control system and method for mixed traffic in parking lot, medium and equipment

Abstract

The application discloses a resource elasticity allocation and barrier linkage control system and method for mixed traffic in a parking lot, a medium and equipment, comprising a vehicle type identification module, a dynamic resource allocation module, a collaborative control decision module, an emergency passage management module and a multi-modal communication module. Through the fusion of the parking lot mixed traffic management system of the car-road cooperative communication, the double-layer game optimization and the elastic resource pool division, the independent resource pool and the dynamic quota adjustment mechanism of the automatic driving vehicle and the artificial driving vehicle are constructed, the charging pile-barrier collaborative optimization unit and the multi-level emergency response protocol are combined, the global optimization of the parking lot resource allocation and the traffic control is realized, and the problems of the outstanding resource competition contradiction in the mixed traffic scene, the separation of the barrier control and the resource allocation, the insufficient intelligentization of the emergency response mechanism and the multi-modal communication and decision collaborative delay short board are solved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of intelligent transportation, and particularly relates to a resource elasticity allocation and barrier linkage control system and method for mixed traffic in a parking lot, a medium and equipment. BACKGROUND

[0002] With the rapid development of automatic driving technology and the popularity of new energy vehicles, urban parking lots are facing the complex management challenges brought by the mixed traffic of traditional manually driven vehicles and automatic driving vehicles. In the prior art, the parking lot management system is mostly based on a static resource allocation mode for a single vehicle type, such as realizing the pre-allocation of fixed parking spaces through license plate recognition, or relying on the path guiding rules of manually driven vehicles. However, these two schemes have significant defects in the mixed traffic scenario:

[0003] (1) The resource competition contradiction of mixed traffic is prominent: there are essential differences between automatic driving vehicles and manually driven vehicles in terms of charging pile demand, path selection logic and response speed. The existing system does not divide dynamic resource pools for the two types of vehicles, resulting in frequent conflicts in the occupation of charging pile resources during peak hours.

[0004] For example, automatic driving vehicles usually need to accurately match the charging pile power and battery state, while manually driven vehicles rely on manual decision-making. The charging pile resource allocation lacks a priority elasticity adjustment mechanism. In addition, the modeling and dynamic scheduling of cruising parking behavior in the mixed traffic environment are still in the blank stage, which exacerbates the path congestion and resource waste in the parking lot.

[0005] (2) The barrier control and resource allocation are fragmented: the traditional parking lot barrier system only serves as a switching control node for vehicle entry and exit, and does not form a cooperative decision-making closed loop with parking space allocation and charging pile scheduling.

[0006] For example, in the parking mode of Baidu ViCAD 2.0, the parking lot end can realize parking space recognition and path planning, but the barrier release strategy is still based on fixed timing and cannot dynamically adjust the release interval or lane function switching according to the real-time traffic density. In the mixed traffic scenario, the unpredictability of manually driven vehicles (such as sudden braking and lane changing) further increases the response delay and path conflict risk of the parking lot barrier.

[0007] (3) The intelligentization of emergency response mechanism is insufficient: the existing parking lot management system relies on manual intervention for the emergency passage support of special vehicles (ambulances and fire engines), and lacks the ability of automatic clearing and resource recycling.

[0008] For example, the intelligent road classification standard (level 3) proposes that the cloud platform can take over the control of special vehicles, but does not define the preset path emptying rules of the emergency passage in the parking lot and the reverse release protocol of the charging pile resources, resulting in that the charging pile occupies resources and cannot be quickly released when an emergency occurs, and the time efficiency of the parking lot barrier system switching to the emergency mode is insufficient;

[0009] (4) Bottleneck of multi-modal communication and decision-making cooperation: Although the vehicle-road cloud integrated technology has realized cooperative perception and decision-making in high-level automatic driving (L4-L5), there are still shortcomings in low-latency communication and lightweight edge computing capability in the mixed traffic scene of the parking lot;

[0010] For example, the existing vehicle-road cloud system mostly adopts centralized cloud decision-making, which is difficult to meet the millisecond-level barrier control instruction synchronization demand in the parking lot; meanwhile, the visual feedback mechanism of the resource allocation strategy is missing, which makes the management party unable to monitor the optimization target weight (such as the dynamic balance of charging demand satisfaction rate and traffic fairness) in real time;

[0011] Therefore, we propose a resource elastic allocation and barrier linkage control system, method, medium and equipment for mixed traffic in the parking lot. SUMMARY

[0012] The purpose of the present application is to provide a resource elastic allocation and barrier linkage control system, method, medium and equipment for mixed traffic in the parking lot, to solve the problems raised in the background art.

[0013] To achieve the above purpose, the present application provides the following technical solution: a resource elastic allocation and barrier linkage control system for mixed traffic in the parking lot, comprising:

[0014] A vehicle type identification module: used for acquiring vehicle control mode information and driving behavior characteristic data, and generating a vehicle type label with automatic driving or manual driving classification attributes;

[0015] A dynamic resource allocation module: according to the vehicle type label, the charging pile resource pool is divided, the dynamic quota adjustment mechanism of automatic driving vehicles and manual driving vehicles is established, and the total reservation proportion of the parking lot resources is dynamically predicted and adjusted according to the real-time charging demand of the parking lot;

[0016] A cooperative control decision module: a double-layer decision-making model of the charging pile resource allocation layer and the barrier passage control layer is established, the charging pile resource allocation layer schedules the charging pile resources based on the remaining power of the vehicle and the power of the charging pile, and the barrier passage control layer generates barrier release instructions based on the priority of the vehicle type and the path conflict degree;

[0017] Emergency passage management module: trigger the preset path emptying mechanism by identifying the vehicle identity, perform the charging pile resource forced release operation, and control the parking lot barrier system to enter the emergency passage mode;

[0018] Multi-modal communication module: through the deployment of edge computing nodes, realize the real-time data interaction of vehicle terminal, parking lot charging pile and parking lot barrier system, and synchronously display the weight parameters and running state of the parking lot charging pile allocation strategy.

[0019] Preferably, the vehicle type recognition module comprises:

[0020] OBU interface analysis unit: through the RSU device arranged in the parking lot barrier system, receive the OBU diagnostic interface information of the vehicle terminal, real-time obtain the vehicle control mode identification code, and analyze and generate the initial classification identification of automatic driving or manual driving;

[0021] Visual feature analysis unit: through the array camera deployed at the entrance of the parking lot, collect vehicle trajectory video stream data, extract turning angle fluctuation rate and acceleration variance data, and constitute a driving behavior feature vector;

[0022] Double-check decision unit: time sequence matching and verification are performed on the initial classification identification result analyzed by the OBU interface analysis unit and the driving behavior feature vector result analyzed by the visual feature analysis unit, and a vehicle type label with a time stamp is generated.

[0023] Preferably, the dynamic resource allocation module comprises:

[0024] Resource pool division unit: the charging pile resources are divided into an automatic driving vehicle charging pile special pool and a manual driving vehicle charging pile special pool, wherein the capacity proportion of the automatic driving vehicle charging pile special pool is dynamically adjusted within a first preset proportion range, and the capacity proportion of the manual driving vehicle charging pile special pool is correspondingly adjusted within a second preset proportion range;

[0025] Charging demand prediction unit: a time series prediction model is used to process historical charging data, peak parking flow data and environmental data to generate a periodic charging demand prediction value;

[0026] Elastic adjustment unit: dynamically adjust the total reserved proportion according to the periodic charging demand prediction value;

[0027] Cross-pool borrowing unit: when the automatic driving vehicle charging pile special pool or the manual driving vehicle charging pile special pool is lower than a third preset threshold, start the cross-pool resource allocation mechanism, and when the cross-pool resources are full, the allocated resources can be adjusted, and the borrowing and returning operations are recorded to the distributed storage node.

[0028] Preferably, the cooperative control decision module comprises:

[0029] A two-layer game modeling unit: a two-layer decision-making model based on a leader-follower game framework is established

[0030] Among them, the charging pile resource allocation layer is the leader, and the joint optimization objectives are to minimize the weighted sum of the reciprocal of the remaining power of the vehicle and to maximize the power utilization rate of the charging pile, and a charging pile scheduling function is constructed, and the calculation formula of the charging pile scheduling function is shown as formula (1):

[0031] (1)

[0032] Among them, SOC i represents the percentage of the remaining power of the vehicle i;

[0033] P(e) represents the output power of the parking lot charging pile e;

[0034] represents the power balance coefficient of the dynamic adjustment of the charging pile;

[0035] That is, for each vehicle, the charging pile with the minimum F(i, e) is allocated and used, that is, e*(i) represents the charging pile allocated for the i-th vehicle, and the calculation formula of e*(i) is shown as formula (2):

[0036] (2)

[0037] Among them, S represents the set of all charging piles;

[0038] argmin represents a general numerical function, that is, the value of e when F(i, e) takes the minimum value;

[0039] The barrier passage control layer as a follower generates a vehicle passage priority score according to the vehicle type weight coefficient, the preset vehicle type weight factor, the inter-vehicle path conflict degree index and the preset inter-vehicle path conflict degree index weight factor:

[0040] Among them, the preset vehicle type weight factor and the preset inter-vehicle path conflict degree index weight factor add up to 1;

[0041] Emergency response execution unit: when it is detected that the SOC i of the vehicle i is lower than the first preset threshold, a barrier lifting rod instruction with a response delay less than the second preset threshold is generated;

[0042] Conflict resolution unit: an inter-vehicle path conflict degree index is generated according to the number of overlapping grids of the paths of the vehicles and the estimated time difference of the vehicles to the conflict point;

[0043] When the inter-vehicle path conflict degree index exceeds the third preset threshold, the spatio-temporal window redistribution algorithm of the passage sequence is activated.

[0044] Preferably, the emergency passage management module comprises:

[0045] Identity authentication triggering unit: match the vehicle identity code with the preset high-priority vehicle database, and generate a preset path clearing instruction set when the verification is passed;

[0046] Resource preemption control unit: send state reset instructions to the target charging pile, interrupt the current charging process and release the charging gun lock, and through dynamic path topology analysis, broadcast path re-planning request to the conflict area vehicle;

[0047] Emergency passage execution unit: after receiving the identity authentication trigger signal, set the associated parking lot barrier system to the normally open state until one of the following conditions is met:

[0048] The emergency vehicle completely passes through the preset monitoring area;

[0049] The parking lot barrier system receives a manual release instruction;

[0050] The emergency state duration exceeds the first response duration threshold.

[0051] Preferably, the multi-modal communication module comprises:

[0052] Edge communication relay unit: deployed in the parking lot area edge computing node, build a heterogeneous communication channel cluster containing V2X short-range communication link, charging pile control bus, parking lot barrier system RS485 interface;

[0053] Strategy data synchronization unit: real-time execute the following data interaction operations:

[0054] Receive the vehicle remaining power and estimated stay duration data set from the vehicle terminal;

[0055] Issue the power adjustment coefficient matrix [λ1, λ2,..., λn] to the charging pile;

[0056] Extract the passage sequence space-time coding from the parking lot barrier system controller;

[0057] Dynamic visualization unit: generate an interactive interface containing the following layers:

[0058] Strategy parameter atlas: map the real-time weight ratio of the reciprocal of the vehicle remaining power and the power balance item in the charging pile allocation strategy;

[0059] Running state topology map: display the load intensity color temperature coding of each charging pile and the opening and closing state pulse signal of the parking lot barrier system.

[0060] A resource elastic allocation and barrier linkage control method for mixed traffic in a parking lot, applied to a resource elastic allocation and barrier linkage control system for mixed traffic in a parking lot, comprising the following steps:

[0061] A, vehicle type identification:

[0062] Obtain vehicle control mode information through a vehicle terminal, combine driving behavior feature data collected by an array camera, and generate a vehicle type label with automatic driving vehicle or manual driving vehicle classification identification;

[0063] B, dynamic resource allocation:

[0064] Based on the vehicle type label, divide an automatic driving vehicle charging pile special pool and a manual driving vehicle charging pile special pool, establish a quota adjustment mechanism for automatic driving vehicle quota and manual driving vehicle quota, and dynamically adjust the total reserved proportion of charging piles according to the real-time charging demand prediction value of each partition of the parking lot;

[0065] C, collaborative control decision:

[0066] Build a double-layer decision model for charging pile resource allocation and parking lot barrier system access control;

[0067] The charging pile resource allocation layer generates a charging pile scheduling instruction based on the remaining battery level, estimated charging time, and charging pile output power;

[0068] The barrier access control layer calculates the release sequence and time interval of the parking lot barrier system according to the vehicle type priority weight and path conflict detection result;

[0069] D, emergency passage management:

[0070] When the identity features of emergency vehicles are identified, activate the preset charging pile occupation resource forced release program on the empty path, and send an emergency access mode activation instruction to the associated parking lot barrier system;

[0071] E, multi-modal communication control:

[0072] Through an edge computing node, realize real-time data interaction between the vehicle terminal, parking lot charging pile and parking lot barrier system, dynamically update the weight parameter matrix of the charging pile allocation strategy, and visually present the system operation state.

[0073] A computer readable storage medium, the computer readable storage medium stores at least one computer program instruction, the at least one computer program instruction is loaded and executed by the processor to realize the operation performed by the resource elastic allocation and barrier linkage control method for mixed traffic in a parking lot.

[0074] An electronic device comprising one or more processors and one or more memories having at least one program code stored therein, the at least one program code being loaded and executed by the one or more processors to implement the operations performed by the resource elasticity allocation and barrier linkage control method for mixed traffic in a parking lot.

[0075] Compared with the prior art, the beneficial effects of the present application are:

[0076] 1. Solving resource competition conflict and improving charging pile utilization rate:

[0077] By establishing independent resource pools for autonomous driving vehicles and manually driven vehicles and adopting a dynamic quota adjustment mechanism, optimal allocation of charging pile resources is achieved, and the system intelligently matches charging piles according to vehicle SOC (remaining power), charging demand and parking time, effectively reduces resource preemption conflict, and improves charging pile power utilization rate;

[0078] 2. Realizing cooperative control of barrier and resource allocation, and optimizing traffic efficiency:

[0079] The traditional parking lot barrier control and resource allocation are disconnected, resulting in low traffic efficiency, and the present application introduces a charging pile-barrier cooperative optimization unit to incorporate vehicle traffic priority score into barrier release decision, dynamically adjusts release interval and lane function based on real-time traffic density, improves vehicle traffic efficiency and reduces path conflict in mixed traffic environment.

[0080] 3. Improving the intelligent level of emergency response and ensuring the passage of special vehicles:

[0081] The existing system relies on manual intervention for emergency response, which has a reaction lag problem, and the present application introduces a multi-level emergency response protocol to automatically identify high-priority vehicles (such as fire trucks and ambulances) through an identity authentication triggering unit, and generates a path clearing instruction, while combining a resource preemption control unit to quickly release charging piles and optimize traffic paths to ensure the priority passage of special vehicles.

[0082] 4. Strengthening multi-modal communication capability, realizing low-latency control and visual management:

[0083] By adopting edge computing + V2X (vehicle-road cooperative communication) technology, the low-latency communication capability in the parking lot is optimized to ensure millisecond-level barrier release control instruction synchronization, while providing a resource allocation visualization interface to monitor key optimization parameters such as charging demand satisfaction rate and traffic fairness in real time, facilitating the management party to adjust operation strategies. BRIEF DESCRIPTION OF DRAWINGS

[0084] Figure 1 The system structure diagram of the present application;

[0085] Figure 2A flowchart of the method of the present application. DETAILED DESCRIPTION

[0086] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0087] Please refer to Figure 1 The resource elasticity allocation and barrier linkage control system for mixed traffic in a parking lot provided by the present application comprises:

[0088] A vehicle type identification module is configured to obtain vehicle control mode information and driving behavior characteristic data, and generate a vehicle type label with automatic driving or manual driving classification attributes;

[0089] The vehicle type identification module comprises:

[0090] An OBU interface analysis unit is disposed in an RSU device at an entrance and exit of a parking lot, receives OBU diagnostic interface information of a vehicle terminal through the RSU device disposed in a barrier system of the parking lot, obtains a vehicle control mode identification code in real time, and analyzes and generates an initial classification identification of automatic driving or manual driving;

[0091] A visual feature analysis unit is disposed in an edge computing node arranged near an entrance and exit of a parking lot, collects vehicle trajectory video stream data through array cameras arranged at an entrance of the parking lot, extracts turning angle fluctuation rate and acceleration variance data, and constitutes a driving behavior characteristic vector;

[0092] A double-check decision unit is integrally arranged in an edge computing node arranged near an entrance and exit of a parking lot, performs time sequence matching and verification on an initial classification identification result analyzed by the OBU interface analysis unit and a driving behavior characteristic vector result analyzed by the visual feature analysis unit, and generates a vehicle type label with a time stamp;

[0093] A dynamic resource allocation module is arranged in a host server of the parking lot, divides a charging pile resource pool according to the vehicle type label, establishes a dynamic quota adjustment mechanism for automatic driving vehicles and manual driving vehicles, and dynamically predicts and adjusts a total reserved proportion of resources of the parking lot according to real-time charging demands of the parking lot;

[0094] The dynamic resource allocation module comprises:

[0095] The resource pool division unit divides the charging pile resources into an autonomous vehicle charging pile special pool and a manually driven vehicle charging pile special pool, wherein the capacity proportion of the autonomous vehicle charging pile special pool is dynamically adjusted within a first preset proportion range, and the capacity proportion of the manually driven vehicle charging pile special pool is correspondingly adjusted within a second preset proportion range.

[0096] The charging demand prediction unit adopts a time series prediction model to process historical charging data, peak parking flow data and environmental data to generate periodic charging demand prediction values.

[0097] The elastic adjustment unit dynamically adjusts the total reserved proportion according to the periodic charging demand prediction values.

[0098] The cross-pool borrowing unit starts a cross-pool resource allocation mechanism when the autonomous vehicle charging pile special pool or the manually driven vehicle charging pile special pool is below a third preset threshold, and can allocate resources when the cross-pool resources are full, and records the borrowing and returning operations to a distributed storage node.

[0099] The cooperative control decision module is arranged in an edge computing node arranged near the entrance and exit of the parking lot, and a double-layer decision model of a charging pile resource allocation layer and a gate passage control layer is established, the charging pile resource allocation layer performs charging pile resource scheduling based on vehicle residual capacity and charging pile power, and the gate passage control layer generates a gate release instruction based on vehicle type priority and path conflict degree.

[0100] The cooperative control decision module includes:

[0101] The double-layer game modeling unit establishes a double-layer decision model based on a leader-follower game framework.

[0102] The charging pile resource allocation layer is the leader, and the joint optimization objectives are to minimize the weighted sum of the reciprocals of the vehicle residual capacities and to maximize the charging pile power utilization rate, and a charging pile scheduling function is constructed, and the calculation formula of the charging pile scheduling function is shown in formula (1):

[0103] (1)

[0104] wherein, SOC i represents the percentage of the residual capacity of the vehicle i;

[0105] P(e) represents the output power of the charging pile e in the parking lot;

[0106] represents the power balance coefficient of the dynamically adjusted charging pile;

[0107] That is, for each vehicle, the charging pile with the minimum F(i, e) is allocated, that is, the charging pile allocated to the i-th vehicle is denoted as e*(i), and the calculation formula of e*(i) is shown in formula (2):

[0108] (2)

[0109] Wherein, S represents the set of all charging piles;

[0110] argmin represents a general numerical function, that is, the value of e when F(i, e) takes the minimum value;

[0111] The barrier passage control layer is a follower, and generates a vehicle passage priority score according to the vehicle type weight coefficient, the preset vehicle type judgment weight factor, the inter-vehicle path conflict degree index, and the preset inter-vehicle path conflict degree index weight factor:

[0112] Wherein, the preset vehicle type judgment weight factor and the preset inter-vehicle path conflict degree index weight factor are added to equal 1;

[0113] Emergency response execution unit: when it is detected that the SOC of vehicle i i is lower than the first preset threshold, a barrier lifting rod instruction with a response delay less than the second preset threshold is generated;

[0114] Conflict resolution strategy unit: generate an inter-vehicle path conflict degree index according to the number of overlapping grids of the paths of the vehicles and the estimated time difference of the vehicles to the conflict point;

[0115] When the inter-vehicle path conflict degree index exceeds the third preset threshold, the spatio-temporal window redistribution algorithm of the passage sequence is activated;

[0116] Emergency passage management module: the emergency passage management module is deployed in the edge computing nodes arranged near the entrances and exits of the parking lot, triggers a preset path emptying mechanism by identifying the vehicle identity, performs a charging pile occupied resource forced release operation, and controls the parking lot barrier system to enter an emergency passage mode;

[0117] The emergency passage management module comprises:

[0118] Identity authentication triggering unit: match the preset high-priority vehicle database through the vehicle identity code, and generate a preset path emptying instruction set when the verification is passed;

[0119] Resource preemption control unit: sends a state reset instruction to the target charging pile, interrupts the current charging process and releases the charging gun lock, and broadcasts a path re-planning request to the vehicles in the conflict area through dynamic path topology analysis;

[0120] Emergency passage execution unit: after receiving the identity authentication trigger signal, set the associated parking lot barrier system to the normally open state until one of the following conditions is met:

[0121] The emergency vehicle completely passes through the preset monitoring area;

[0122] The parking lot barrier system receives a manual release instruction;

[0123] The duration of the emergency state exceeds the first response duration threshold;

[0124] Multi-modal communication module: through the deployment of edge computing nodes, realize real-time data interaction between vehicle terminal, parking lot charging pile and parking lot barrier system, and synchronize the weight parameters and running state of the parking lot charging pile allocation strategy;

[0125] The multi-modal communication module comprises:

[0126] Edge communication relay unit: deployed in the edge computing node of the parking lot area, build a heterogeneous communication channel cluster containing V2X short-range communication link, charging pile control bus and parking lot barrier system RS485 interface;

[0127] Strategy data synchronization unit: real-time data interaction operations include:

[0128] Receive vehicle remaining power and estimated stay duration data set from vehicle terminal;

[0129] Issue power adjustment coefficient matrix [λ1, λ2,..., λn] to the charging pile;

[0130] Extract the passage sequence space-time code from the parking lot barrier system controller;

[0131] Dynamic visualization unit: generate an interactive interface containing the following layers:

[0132] Strategy parameter graph: map the real-time weight ratio of the reciprocal of vehicle remaining power and power balance in the charging pile allocation strategy;

[0133] Running state topology map: display the load intensity color temperature coding of each charging pile and the opening and closing state pulse signal of the parking lot barrier system.

[0134] Please refer to Figure 2 The resource elasticity allocation and barrier linkage control method for parking lot mixed traffic provided by the embodiment is applied to a resource elasticity allocation and barrier linkage control system for parking lot mixed traffic, and includes the following steps:

[0135] A, Vehicle type identification: Obtain vehicle control mode information through the vehicle terminal, combine the driving behavior characteristic data collected by the array camera, and generate a vehicle type label with automatic driving vehicle or manual driving vehicle classification identification. The specific process is as follows:

[0136] A1: When the vehicle drives to the parking lot gate system, the OBU diagnostic interface information of the vehicle terminal is obtained through the RSU device placed at the parking lot gate system, and the vehicle control mode identification code is obtained in real time. The control mode identification code sent by the vehicle-mounted OBU is received, for example, 0x01 identification code represents an automatic driving vehicle, and 0x02 identification code represents a manual driving;

[0137] A2: Use the array camera (for example, the camera has a 4K resolution and 30fps) deployed at the entrance of the parking lot to collect vehicle trajectory video stream data, extract the steering angle fluctuation rate and acceleration variance of the vehicle, and form a driving behavior feature vector;

[0138] Wherein the steering angle fluctuation rate is the standard deviation of the steering angle per second (threshold set to ≤1.5°), and the acceleration variance is the dispersion degree of acceleration change (threshold set to ≤0.5m / s³);

[0139] A3: Enable double-check decision, that is, time sequence matching of OBU interface analysis result and visual feature analysis result, when OBU result is automatic driving, but steering angle fluctuation rate and acceleration variance index all exceed threshold, start manual review mechanism (for example, OBU obtains vehicle as identification code 0x01 automatic driving vehicle, but according to visual calculation, its steering angle fluctuation rate is 5° and acceleration variance is 1m / s³, trigger manual review), finally generate vehicle type label with timestamp, label example is 0x01_202504051430;

[0140] B, Dynamic resource allocation: Based on the vehicle type label, divide the automatic driving vehicle charging pile special pool and the manual driving vehicle charging pile special pool, establish the quota adjustment mechanism of automatic driving vehicle quota and manual driving vehicle quota, dynamically adjust the total reserved proportion of charging piles according to the real-time charging demand prediction value of each partition of the parking lot. The specific process is as follows:

[0141] B1: Preliminary division of charging pile resource pool proportion, that is, all charging pile resources in the parking lot are divided into automatic driving vehicle charging pile special pool (first resource pool) and manual driving vehicle charging pile special pool (second resource pool), wherein the capacity proportion of the first resource pool is dynamically adjusted in the first preset proportion range (set to 60%-80%), and the proportion of the second resource pool is adjusted in the second preset proportion range (set to 20%-40%);

[0142] B2: input the parking lot historical charging data, historical peak parking flow data, weather temperature data, holiday data into the time series prediction model (LSTM neural network), generate the predicted periodic charging demand prediction value, and dynamically adjust the total reservation ratio according to the prediction value;

[0143] For example, the time series model predicts that at 8-10 am on Monday, the weather temperature is -1 degree, and the autonomous vehicle charging accounts for 60% of all charging piles. Then, the first resource pool accounts for 60%, and the second resource pool accounts for 40%.

[0144] B3: When the utilization rate of a single charging pile resource pool is lower than the third preset threshold (set to 30%), the cross-pool resource allocation mechanism is started, and when the other resource pool is full, the allocated resources can be adjusted, and the borrowing and returning operations are recorded to the blockchain network node storage;

[0145] For example, at a certain moment, the utilization rate of the second resource pool is only 20%, which is marked as a borrowable state. At this time, if the first resource pool is full, the charging piles of the second resource pool can be allocated to the first resource pool, and the storage record is made by using the blockchain network node;

[0146] C, cooperative control decision: a double-layer decision model of charging pile resource allocation and parking lot gate system access control is constructed. The charging pile resource allocation layer generates charging pile scheduling instructions based on the vehicle remaining power, estimated charging time, and charging pile output power. The gate access control layer calculates the parking lot gate system release sequence and time interval according to the vehicle type priority weight and path conflict detection result. The specific process is as follows:

[0147] C1: a double-layer decision model based on a leader-follower game framework is established:

[0148] Among them, the charging pile resource allocation layer is the leader, and the joint optimization objectives are to minimize the weighted sum of the reciprocal of the vehicle remaining power and maximize the charging pile power utilization rate. The charging pile scheduling function is constructed, and the calculation formula of the charging pile scheduling function is shown in formula (1):

[0149] (1)

[0150] Among them, SOC i represents the percentage of the remaining power of vehicle i;

[0151] P(e) represents the output power of the charging pile e in the parking lot;

[0152] represents the power balance coefficient of the charging pile dynamic adjustment;

[0153] That is, for each vehicle, the charging pile with the minimum F(i, e) is allocated, that is, the charging pile allocated to the i-th vehicle is denoted as e*(i), and the calculation formula of e*(i) is shown in formula (2):

[0154] (2)

[0155] Wherein, S represents the set of all charging piles;

[0156] argmin represents a general numerical function, that is, the value of e when F(i, e) takes the minimum value;

[0157] For example, the adjustment rule of the said λ can be set as:

[0158] λ=0.5•(1-SOCavg),

[0159] SOCavg represents the average remaining power of the vehicles in the parking lot;

[0160] When SOCavg=40%, vehicle A with 15% remaining power enters, and a charging pile with a power of 22KW is preferentially allocated to vehicle A, and vehicle B with 50% remaining power enters, and a charging pile with a power of 7KW is preferentially allocated to vehicle B;

[0161] The barrier passage control layer serves as a follower, and generates a vehicle passage priority score according to the vehicle type weight coefficient, the preset vehicle type weight factor, the inter-vehicle path conflict degree index, and the preset inter-vehicle path conflict degree index weight factor:

[0162] Wherein, the preset vehicle type weight factor and the preset inter-vehicle path conflict degree index weight factor add up to 1;

[0163] For example, the vehicle type weight coefficient adopts hierarchical assignment, and in a regional parking lot where automatic driving is vigorously promoted, the vehicle type weight coefficient of an automatic driving vehicle can be set to 1.0, and the vehicle type weight coefficient of a manual driving vehicle can be set to 0.6, so as to ensure the priority of the automatic driving vehicle;

[0164] C2: when it is detected that the SOC of vehicle i is lower than a first preset threshold value, a barrier lifting rod instruction with a response delay less than a second preset threshold value is generated; i

[0165] For example, the first preset value can be set to 5%, and the second preset value can be set to 500ms, that is, when the system detects that the SOC of the vehicle is lower than 5%, a barrier lifting rod with a delay less than 500ms is generated, so as to ensure that the power of the vehicle can smoothly reach the parking space, and to reduce the waiting and power consumption time in front of the barrier;

[0166] ​C3: generating an inter-vehicle path conflict degree index according to the number of overlapped grids of the inter-vehicle paths and the estimated time difference of the two vehicles reaching the conflict point;

[0167] when the inter-vehicle path conflict degree index exceeds a third preset threshold, activating a spatiotemporal window redistribution algorithm of the passing sequence;

[0168] For example, the third preset threshold is set to 2, then

[0169] the inter-vehicle path conflict degree index < 2.0 (low conflict, keeping the original sequence);

[0170] 2.0 ≤ the inter-vehicle path conflict degree index < 4.0 (medium conflict, local adjustment);

[0171] the inter-vehicle path conflict degree index ≥ 4.0 (high conflict, global reorganization);

[0172] Suppose the number of overlapped grids of the inter-vehicle paths is 10 and the estimated time difference of the two vehicles reaching the conflict point is 10 seconds, then the inter-vehicle path conflict degree index is 1, keeping the original sequence passing;

[0173] D, emergency passage management: when the identity features of emergency vehicles are identified, a preset charging pile occupation resource forced release program on the empty path is activated, and an emergency passing mode activation instruction is sent to the associated parking lot barrier system, and the specific process is as follows:

[0174] D1: matching the preset high-priority vehicle database through the vehicle identity code, generating a path emptying instruction set when the verification is passed;

[0175] The high-priority vehicle database includes: encrypted digital certificates of emergency rescue vehicles and special operation vehicles;

[0176] For example, when it is identified that the vehicle is about to enter the parking lot, the current vehicle is matched in the high-priority vehicle database as a fire truck (such as VIN code: LSKGJ4CLXHA******), and a path emptying instruction is generated;

[0177] D2: resource preemption control unit, configured to perform hierarchical response operation:

[0178] First, send a state reset instruction to the target charging pile, interrupt the current charging process and release the charging gun lock, and through dynamic path topology analysis, broadcast a path re-planning request to the vehicles in the conflict area;

[0179] The state reset instruction includes a charging pile power-off sequence:

[0180] ① stop power output, ② release the charging gun mechanical lock, ③ turn on the emergency indicator light;

[0181] D3: emergency passing execution unit, configured to:

[0182] Upon receiving the identity authentication trigger signal, set the associated barrier gate to an open state until one of the following conditions is met:

[0183] (1) The emergency vehicle completely passes through the preset monitoring area;

[0184] (2) The system receives a manual release instruction;

[0185] (3) The duration of the emergency state exceeds the first response duration threshold;

[0186] The default setting of the first response duration threshold is 120 seconds, which can be dynamically adjusted based on the size of the parking lot;

[0187] E, multi-modal communication control: through the edge computing node to realize the real-time data interaction between the vehicle terminal, the parking lot charging pile and the parking lot barrier system, dynamically update the weight parameter matrix of the charging pile allocation strategy, and visually present the system running state, the specific process is as follows:

[0188] E1: Build an edge communication relay unit, deployed in the edge computing node of the parking lot area, build a heterogeneous communication channel cluster containing V2X short-range communication link, charging pile control bus, barrier RS485 interface, V2X communication link uses IEEE802.11p protocol, data update period ≤200ms;

[0189] E2: Strategy data synchronization unit, real-time performs the following data interaction operations:

[0190] (1) Receive the vehicle remaining power (SOC) and estimated stay duration data set from the vehicle terminal;

[0191] (2) Issue the power adjustment coefficient matrix [λ1, λ2,..., λn] to the charging pile;

[0192] The power adjustment coefficient matrix is calculated by the following formula:

[0193] λj=(Prated,j-Pcurrent,j) / Prated,j

[0194] Where Prated,j is the rated power of charging pile j, and Pcurrent,j is the real-time output power of charging pile j.

[0195] (3) Extract the passing sequence space-time code from the barrier controller;

[0196] E3: Dynamic visualization unit, generate an interactive interface containing the following layers:

[0197] (1) Strategy parameter atlas: map the real-time weight ratio of the SOC reciprocal term and the power balance term in the charging pile allocation strategy;

[0198] (2) Running state topology diagram: display the load intensity color temperature coding of each charging pile and the opening and closing state pulse signal of the barrier gate;

[0199] The load intensity color temperature coding rule is:

[0200] Low load: blue system (λj>0.7);

[0201] Medium load: green system (0.3≤λj≤0.7);

[0202] High load: red system (λj<0.3);

[0203] In the actual operation process, the edge communication relay unit receives the SOC data and the stay duration prediction of multiple vehicles at the same time, and the latest strategy parameters (for example, [λ1=0.22, λ2=0.18,…]) are issued to each charging pile through the charging pile control bus; at the same time, the barrier gate controller feeds back the current passing sequence code "TS-20250319-15:10", and these data are displayed in the form of charts on the monitoring platform in real time through the dynamic visualization unit, so as to facilitate the management personnel to timely adjust the strategy and monitor the system operation state.

[0204] The computer readable storage medium provided in the embodiment stores at least one computer program instruction, and the at least one computer program instruction is loaded and executed by the processor to realize the operations performed by the resource elastic allocation and barrier linkage control method for mixed traffic in a parking lot.

[0205] The electronic device provided in the embodiment includes one or more processors and one or more memories, and the one or more memories store at least one program code, and the at least one program code is loaded and executed by the one or more processors to realize the operations performed by the resource elastic allocation and barrier linkage control method for mixed traffic in a parking lot.

[0206] The present application significantly improves the intelligent level of mixed traffic management in a parking lot by introducing car-road cooperation communication, double-layer game optimization and elastic resource pool division, and has the following beneficial effects compared with the prior art:

[0207] (1) Solving resource competition conflict and improving charging pile utilization rate:

[0208] By establishing independent resource pools for autonomous driving vehicles and manually driving vehicles and adopting a dynamic quota adjustment mechanism, optimal allocation of charging pile resources is realized, the system intelligently matches charging piles according to the SOC (remaining power), charging demand and parking duration of the vehicle, effectively reduces resource preemption conflict, and improves charging pile power utilization rate;

[0209] (2) Realize the coordinated control of gate and resource allocation, optimize the passing efficiency:

[0210] The traditional parking lot gate control is disconnected with resource allocation, resulting in low passing efficiency, the present application realizes the coordinated optimization of charging pile-gate unit, the vehicle passing priority score is included in the gate release decision, the release interval and lane function are dynamically adjusted based on real-time traffic density, the vehicle passing efficiency is improved, and the path conflict under mixed traffic environment is reduced;

[0211] (3) Improve the intelligent level of emergency response, and protect the passing of special vehicles:

[0212] The existing system depends on manual intervention for emergency response, and there is a problem of reaction lag, the present application introduces a multi-level emergency response protocol, automatically identifies high-priority vehicles (such as fire trucks and ambulances) through an identity authentication triggering unit, and generates a path clearing instruction, while combining a resource preemption control unit to quickly release charging piles and optimize the passing path, to ensure the priority passing of special vehicles;

[0213] (4) Strengthen the multi-modal communication capability, realize low-delay control and visual management:

[0214] The edge computing+V2X (vehicle-road cooperative communication) technology is adopted to optimize the low-delay communication capability in the parking lot, to ensure the synchronization of millisecond-level gate release control instructions, and to provide a resource allocation visual interface to monitor key optimization parameters such as charging demand satisfaction rate and traffic fairness in real time, to facilitate the management party to adjust the operation strategy.

[0215] Although the embodiments of the present application have been shown and described, it can be understood by those skilled in the art that various changes, modifications, replacements and variations can be made to the embodiments without departing from the principles and spirits of the present application, the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A resource elasticity allocation and barrier linkage control system for mixed traffic in a parking lot, characterized in that, The application relates to a parking lot charging pile resource allocation method based on vehicle type identification and dynamic resource allocation, which comprises the following steps: a vehicle type identification module: used for acquiring vehicle control mode information and driving behavior characteristic data, and generating a vehicle type label with automatic driving or manual driving classification attributes; a dynamic resource allocation module: used for dividing charging pile resource pools according to the vehicle type label, establishing a dynamic quota adjustment mechanism for automatic driving vehicles and manual driving vehicles, and dynamically predicting and adjusting the total reservation proportion of parking lot resources according to real-time charging demands of the parking lot; a collaborative control decision module: used for establishing a double-layer decision model of a charging pile resource allocation layer and a gate passing control layer, the charging pile resource allocation layer is used for performing charging pile resource scheduling based on vehicle residual power and charging pile power, and the gate passing control layer is used for generating gate release instructions based on vehicle type priority and path conflict degree; the collaborative control decision module comprises: a double-layer game modeling unit: used for establishing a double-layer decision model based on a leader-follower game framework; wherein the charging pile resource allocation layer is used as a leader, a charging pile scheduling function is constructed by taking the weighted sum of the reciprocal of vehicle residual power and the maximum charging pile power utilization rate as the joint optimization target, and the calculation formula of the charging pile scheduling function is shown in formula (1): （1） where SOCi i represents the percentage of the remaining power of the vehicle i; P (e) represents the output power of a parking lot charging pile e; a power balance coefficient representing a dynamic adjustment of the charging pile; that is, for each vehicle, a charging pile with the minimum F (i, e) is allocated, that is, e* (i) represents the charging pile allocated for the ith vehicle, and the calculation formula of e* (i) is shown in formula (2): （2） wherein S represents the set of all charging piles; argmin represents a general numerical function, that is, the value of e when F (i, e) takes the minimum value; an emergency channel management module: used for triggering a preset path emptying mechanism by identifying the vehicle identity, performing a charging pile occupied resource forced release operation, and controlling the parking lot gate system to enter an emergency passing mode; a multi-modal communication module: used for realizing real-time data interaction of vehicle terminals, parking lot charging piles and parking lot gate systems by deploying edge computing nodes, and synchronously displaying the weight parameters and running states of the parking lot charging pile allocation strategy.

2. The resource elasticity allocation and barrier linkage control system for mixed traffic in parking lots according to claim 1, characterized in that: The vehicle type identification module comprises: an OBU interface analysis unit: used for receiving OBU diagnostic interface information of vehicle terminals through RSU equipment arranged in the parking lot gate system, acquiring vehicle control mode identification codes in real time, and analyzing and generating initial classification identification of automatic driving or manual driving; a visual feature analysis unit: used for collecting vehicle driving track video stream data through array cameras arranged at the parking lot entrance, extracting turning angle fluctuation rate and acceleration variance data, and constituting a driving behavior feature vector; a double-check decision unit: used for performing time sequence matching and verification on the initial classification identification result analyzed by the OBU interface analysis unit and the driving behavior feature vector result analyzed by the visual feature analysis unit, and generating a vehicle type label with a time stamp.

3. The resource elasticity allocation and barrier linkage control system for mixed traffic in parking lots according to claim 2, characterized in that: The dynamic resource allocation module comprises: a resource pool division unit: used for dividing charging pile resources into an automatic driving vehicle charging pile special pool and a manual driving vehicle charging pile special pool, wherein the capacity proportion of the automatic driving vehicle charging pile special pool is dynamically adjusted in a first preset proportion range, and the capacity proportion of the manual driving vehicle charging pile special pool is correspondingly adjusted in a second preset proportion range; The charging demand prediction unit: uses a time series prediction model to process historical charging data, peak parking flow data, and environmental data to generate periodic charging demand prediction values; The elastic adjustment unit: dynamically adjusts the total reservation ratio based on the periodic charging demand prediction values; The cross-pool borrowing unit: activates the cross-pool resource allocation mechanism when the autonomous vehicle charging pile dedicated pool or the manually driven vehicle charging pile dedicated pool falls below the third preset threshold, and records the borrowing and returning operations to the distributed storage node when the cross-pool resources are full.

4. The resource elasticity allocation and barrier linkage control system for mixed traffic in parking lots according to claim 3, characterized in that: The barrier passage control layer as a follower generates a vehicle passage priority score based on the vehicle type weight coefficient, the preset vehicle type weight factor, the inter-vehicle path conflict degree index, and the preset inter-vehicle path conflict degree index weight factor: Wherein, the preset inter-vehicle path conflict degree index weight factor and the preset inter-vehicle path conflict degree index weight factor add up to 1; The cooperative control decision module further comprises an emergency response execution unit: when it is detected that the SOC of the vehicle i is lower than a first preset threshold value i a barrier lifting rod instruction is generated, and a response delay is less than a second preset threshold value. The conflict resolution strategy unit: generates an inter-vehicle path conflict degree index based on the number of overlapping grids and the estimated time difference between the arrival of the conflict point; When the inter-vehicle path conflict degree index exceeds the third preset threshold, the time and space window redistribution algorithm of the passage sequence is activated.

5. The resource elasticity allocation and barrier linkage control system for mixed traffic in parking lots according to claim 4, characterized in that: The emergency passage management module includes: The identity authentication triggering unit: matches the vehicle identity code with the preset high-priority vehicle database, and generates a preset path clearing instruction set when the verification is passed; The resource preemption control unit: sends a state reset instruction to the target charging pile, interrupts the current charging process, and releases the charging gun lock, and through dynamic path topology analysis, broadcasts a path re-planning request to the vehicles in the conflict area; The emergency passage execution unit: after receiving the identity authentication trigger signal, sets the associated parking lot barrier system to the normally open state until one of the following conditions is met: The emergency vehicle has completely passed through the preset monitoring area; The parking lot barrier system receives a manual release instruction; The duration of the emergency state exceeds the first response time threshold.

6. The resource elasticity allocation and barrier linkage control system for mixed traffic in parking lots according to claim 5, characterized in that: The multi-modal communication module includes: The edge communication relay unit: deployed at the edge computing nodes of the parking lot area, constructs a heterogeneous communication channel cluster including V2X short-range communication links, charging pile control buses, and parking lot barrier system RS485 interfaces; The strategy data synchronization unit: performs the following data interaction operations in real time: Receives vehicle remaining power and estimated stay duration data sets from vehicle terminals; Issues a power adjustment coefficient matrix [λ1, λ2,..., λn] to the charging pile; Extracts the passage sequence space-time code from the parking lot barrier system controller; The dynamic visualization unit: generates an interactive interface including the following layers: Strategy parameter map: maps the real-time weight ratio of the reciprocal of the vehicle remaining power and the power balance term in the charging pile allocation strategy; Running state topology map: displays the load intensity color temperature coding of each charging pile and the opening and closing state pulse signal of the parking lot barrier system.

7. A resource elasticity allocation and barrier linkage control method for mixed traffic in a parking lot, applied to the resource elasticity allocation and barrier linkage control system for mixed traffic in a parking lot in any one of claims 1-6, characterized in that, The method includes the following steps: A. Vehicle type identification: Obtain vehicle control mode information through the vehicle terminal, combine the driving behavior feature data collected by the array camera, and generate a vehicle type label with automatic driving vehicle or manually driven vehicle classification identification; B. Dynamic resource allocation: Based on the vehicle type label, the automatic driving vehicle charging pile special pool and the artificial driving vehicle charging pile special pool are divided, the quota adjustment mechanism of automatic driving vehicle quota and artificial driving vehicle quota is established, and the total reserved proportion of charging piles is dynamically adjusted according to the real-time charging demand prediction value of each partition of the parking lot; C. Collaborative control decision: A double-layer decision model of charging pile resource allocation and parking lot barrier system access control is constructed; The charging pile resource allocation layer generates charging pile scheduling instructions based on the remaining electric quantity of the vehicle, the estimated charging time and the output power of the charging pile; The barrier access control layer calculates the release sequence and time interval of the parking lot barrier system according to the vehicle type priority weight and the path conflict detection result; D. Emergency passage management: When the identity characteristics of the emergency vehicle are identified, the preset empty path charging pile occupation resource forced release program is activated, and the emergency access mode activation instruction is sent to the associated parking lot barrier system; E. Multi-modal communication control: Through the edge computing node, real-time data interaction is realized between the vehicle terminal, the parking lot charging pile and the parking lot barrier system, the weight parameter matrix of the charging pile allocation strategy is dynamically updated, and the system operation state is visualized.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores at least one computer program instruction, and the at least one computer program instruction is loaded and executed by the processor to realize the operations performed by the resource elastic allocation and barrier linkage control method for mixed traffic in the parking lot as claimed in claim 7.

9. An electronic device, comprising: The one or more processors and the one or more memories are included, and the one or more memories store at least one program code, and the at least one program code is loaded and executed by the one or more processors to realize the operations performed by the resource elastic allocation and barrier linkage control method for mixed traffic in the parking lot as claimed in claim 7.

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