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CN-122022406-A - Intelligent scheduling decision and monitoring management system and method for motorcade combined with roof cradle head

CN122022406ACN 122022406 ACN122022406 ACN 122022406ACN-122022406-A

Abstract

The invention relates to the technical field of a vehicle team management system, and discloses a vehicle team intelligent scheduling decision and monitoring management system and method combining a vehicle roof cradle head, wherein the vehicle team intelligent scheduling decision and monitoring management system comprises a management server and a vehicle-mounted terminal, and the vehicle-mounted terminal collects space monitoring abnormal values; the management server acquires a vehicle team business value base number, a business performance path and real-time position coordinates, determines a corresponding vehicle business performance rigidity coefficient, calculates a business performance deviation degree, constructs a correlation suppression model according to the business performance rigidity coefficient and the business performance deviation degree, and generates a weight correction parameter for a roof cradle head.

Inventors

  • WU XIANGFENG

Assignees

  • 福建仙兴汽车配件有限公司
  • 福建榕泰唯星汽车产业有限公司

Dates

Publication Date
20260512
Application Date
20260414

Claims (10)

  1. 1. The intelligent scheduling decision and monitoring management system for the motorcade combining the vehicle roof cradle head is characterized by comprising a management server and a vehicle-mounted terminal: The vehicle-mounted terminal comprises an anomaly acquisition module and is used for extracting a space monitoring anomaly value; The management server comprises a performance evaluation module, a weight suppression module and a scheduling decision module; The performance evaluation module is used for acquiring a business value base number, a business performance path and real-time position coordinates of the vehicle team, determining a business performance rigidity coefficient of the vehicle corresponding to the vehicle by the vehicle-mounted terminal according to the business value base number, and calculating business performance deviation degree according to the business performance path and the real-time position coordinates; the weight suppression module is used for generating weight correction parameters for the vehicle roof cradle head through the association suppression model according to the commercial performance rigidity coefficient and the business performance deviation degree, wherein the business performance deviation degree approaches to When the commercial performance rigidity coefficient is higher than a preset threshold, the weight correction parameter decays exponentially along with the reduction of the business performance deviation degree so as to shield interference signals generated by physical environment fluctuation; and the scheduling decision module is used for carrying out numerical correction on the space monitoring abnormal value according to the weight correction parameter and outputting a monitoring scheduling instruction aiming at the vehicle-mounted terminal.
  2. 2. The intelligent scheduling decision and monitoring management system for a motorcade combined with a roof cradle head according to claim 1 is characterized in that the performance evaluation module performs the following sub-logic when calculating a business performance deviation degree, wherein the step 1011 is to acquire a space-time constraint matrix defined by a business contract as a business performance path and extract projection characteristics of real-time position coordinates in the space-time constraint matrix, and the step 1012 is to calculate euclidean distance deviation and time lag parameters of the real-time position coordinates relative to the business performance path and perform normalized weighted fusion on the euclidean distance deviation and the time lag parameters to generate the business performance deviation degree.
  3. 3. The intelligent scheduling decision and monitoring management system for a fleet of vehicles with integrated roof head as set forth in claim 1, wherein the management server is further configured to calculate a time compensation correction term according to a cutoff duration of the communication heartbeat signal to correct the weight correction parameter, wherein the management server calculates the corrected weight correction parameter : Wherein W is the corrected weight correction parameter, And (3) correcting parameters for initial weights, wherein alpha is a preset risk growth coefficient, and delta t is the interruption duration of communication heartbeat signals.
  4. 4. The intelligent scheduling decision and monitoring management system for the motorcade combined with the vehicle roof cloud deck according to claim 1 is characterized by further comprising a utility audit module, wherein the utility audit module is used for calculating a supervision necessity index representing the scheduling necessity degree according to the risk confirmation rate of a bicycle historical scheduling period, and the utility audit module is used for identifying and suppressing frequent false alarms of space monitoring abnormal values caused by sensor faults or environmental noise and reducing the occupation priority of corresponding vehicle-mounted terminals in a global supervision bandwidth according to the negative feedback result of the risk confirmation rate.
  5. 5. The intelligent scheduling decision and monitoring management system for a fleet of vehicles combined with a roof cradle head according to claim 1, wherein the management server is used for establishing an image relation model of service contract constraint force and default cost to generate a commercial performance rigidity coefficient, the commercial performance rigidity coefficient is used for representing performance constraint intensity of the vehicles when the vehicles implement specific commercial tasks, and the service performance deviation degree is kept monotonically decreasing in an electronic fence boundary defined by a commercial performance path.
  6. 6. The intelligent scheduling decision and monitoring management system for the vehicle fleet in combination with the vehicle roof cradle head according to claim 1 is characterized in that the monitoring scheduling instruction comprises a monitoring gesture allocation parameter and a data sampling configuration parameter, and the vehicle-mounted terminal further comprises a gesture configuration module for logically mapping the rotation step length, the overlooking angle and the zoom ratio of the vehicle roof cradle head according to the monitoring gesture allocation parameter and synchronously adjusting the sampling frequency of a vehicle-mounted monitoring component according to the data sampling configuration parameter.
  7. 7. The intelligent scheduling decision and monitoring management system for the motorcade combined with the roof cradle head, as set forth in claim 1, is characterized in that the management server is further configured to configure the triggering sensitivity of the anomaly acquisition module according to the weight correction parameter, and the management server is configured to send a silencing instruction to the vehicle-mounted terminal when the weight correction parameter is lower than a preset threshold, so as to cut off a communication link for the vehicle-mounted terminal to upload non-anomaly monitoring data to the management server.
  8. 8. The intelligent scheduling decision and monitoring management system for the motorcade combined with the roof cradle head according to claim 3 is characterized in that the management server is used for dynamically distributing motorcade supervision resources according to weight correction parameters, and the management server is used for placing vehicles with weight correction parameters higher than a preset safety level at the tail of a scheduling queue and preferentially pushing the vehicles which are in a communication blind area and have time compensation correction items reaching an early warning threshold to the head of the scheduling queue.
  9. 9. The intelligent scheduling decision and monitoring management system for the vehicle fleet combined with the vehicle roof cradle head is characterized by comprising an anomaly acquisition module, a management server and a management server, wherein the anomaly acquisition module is used for carrying out time domain filtering and frequency domain component extraction on a physical sensing signal to generate a space monitoring anomaly value, the anomaly acquisition module is used for extracting feature vectors representing space deformation, vibration frequency and brightness mutation in the physical sensing signal, converting the feature vectors into the space monitoring anomaly value by utilizing nonlinear mapping logic, and superposing historical risk gain coefficients in an association suppression model, and the management server is used for carrying out dynamic fine adjustment on commercial performance rigidity coefficients according to historical default frequencies and scheduled risk confirmation rates so as to implement differential supervision strategies for different driving subjects and different transportation lines.
  10. 10. The intelligent scheduling decision and monitoring management method for the motorcade combined with the roof tripod head is used for realizing the intelligent scheduling decision and monitoring management system for the motorcade combined with the roof tripod head, and is characterized by comprising the following steps of: Step 1101, acquiring service state data of a vehicle team and a space monitoring abnormal value extracted by an abnormal acquisition module, wherein the service state data comprises a service value base, a commercial performance path and real-time position coordinates; Step 1102, determining a commercial performance rigidity coefficient of a vehicle corresponding to the vehicle by a performance evaluation module according to the service value base, and calculating a service performance deviation degree according to a commercial performance path and real-time position coordinates; Step 1103, generating a weight correction parameter for the vehicle roof cradle head by a weight suppression module according to the business performance rigidity coefficient and the business performance deviation degree through a correlation suppression model, wherein when the business performance deviation degree approaches to 0 and the business performance rigidity coefficient is higher than a preset threshold value, the weight correction parameter is driven to exponentially attenuate along with the reduction of the business performance deviation degree so as to shield an interference signal generated by physical environment fluctuation; And 1104, carrying out numerical correction on the space monitoring abnormal value by a scheduling decision module according to the weight correction parameter, and outputting a monitoring scheduling instruction aiming at the vehicle-mounted terminal so as to implement monitoring gesture allocation on the vehicle roof cradle head by a gesture allocation module.

Description

Intelligent scheduling decision and monitoring management system and method for motorcade combined with roof cradle head Technical Field The invention belongs to the technical field of fleet management systems, and particularly relates to a fleet intelligent scheduling decision and monitoring management system and method combined with a roof cradle head. Background However, in a wide-area distributed scheduling scene, resource mismatch exists between a central end downlink supervision bandwidth and a front end massive visual data stream, the existing scheduling decision logic depends on random spot check or data return triggered by physical sensors such as bottom collision and vibration, the mode generates response delay and resource allocation blindness when facing concurrent service conflict, the scheduling inertia which enables physical environment fluctuation to be equal to service risk early warning exists in the industry, and in actual operation, when a vehicle with commercial performance rigidity passes complex working conditions, the vehicle-mounted end sensor triggers a space abnormal scalar due to environmental noise, if the downlink bandwidth is simply increased or edge computing force reinforcement is introduced, the bandwidth is not only increased but also true to be submerged in the data flood due to increase of supervision redundancy caused by invalid physical noise. Not only the limitation of the physical perception hardware equipment is difficult to overcome, but also the limitation of a emphasis algorithm optimizing software control method is insufficient, for example, the Chinese patent application with publication number of CN121616173A discloses an artificial intelligent vehicle-mounted logistics intelligent control system, the follow-up matching and path planning are corrected by updating credit account book through calculating causal contribution, the hidden premise that a dependence post-data accumulation feedback mechanism is established is that a traffic environment has long-period steady-state repeatability, in a real complex working condition, physical environment sudden disturbance such as instantaneous bump and local electromagnetic interference belongs to a high-frequency disordered random event, unpredictable bottom layer dynamic change is forcedly brought into a historical experience account book to carry out causal attribution, and the fundamental mismatch of a core preset premise and an actual boundary condition is caused, so that dynamic authentication cannot be implemented at the moment of abnormal signal generation, but also supervision response is seriously lagged due to long post-evaluation, the absolute performance constraint strength is anchored when a vehicle implements a commercial task, the physical disturbance is restrained by using business logic, and the problem that the dependence probability cannot cope with the transient principle is solved. Therefore, according to the service performance rigidity, a dynamic authentication and suppression mechanism aiming at the physical abnormal scalar is constructed, and under the condition of limited resources, the focusing of the supervision bandwidth to the real service default risk node is ensured, so that the technical problem to be solved by the invention is solved. Disclosure of Invention The invention provides a motorcade intelligent scheduling decision and monitoring management system combined with a vehicle roof cradle head, which comprises a management server and a vehicle-mounted terminal: The vehicle-mounted terminal comprises an anomaly acquisition module and is used for extracting a space monitoring anomaly value; The management server comprises a performance evaluation module, a weight suppression module and a scheduling decision module; The performance evaluation module is used for acquiring a business value base number, a business performance path and real-time position coordinates of the vehicle team, determining a business performance rigidity coefficient of the vehicle corresponding to the vehicle by the vehicle-mounted terminal according to the business value base number, and calculating business performance deviation degree according to the business performance path and the real-time position coordinates; the weight suppression module is used for generating weight correction parameters for the vehicle roof cradle head through the association suppression model according to the commercial performance rigidity coefficient and the business performance deviation degree, wherein the business performance deviation degree approaches to When the commercial performance rigidity coefficient is higher than a preset threshold, the weight correction parameter decays exponentially along with the reduction of the business performance deviation degree so as to shield interference signals generated by physical environment fluctuation; and the scheduling decision module is used for carrying out numerical correction on