CN-121982787-A - Road berth charging and control system for realizing multi-level fault tolerance and method thereof

CN121982787ACN 121982787 ACN121982787 ACN 121982787ACN-121982787-A

Abstract

The invention discloses a road berth charging and controlling system and a method thereof for realizing multi-level fault tolerance, belonging to the technical field of intelligent traffic systems and Internet of things. The system adopts a framework of cooperative edge calculation and distributed sensing, and consists of an Edge Controller (ECU) and a Sensing and Control Unit (SCU) deployed in a berth. The invention ensures high availability of a system through fault tolerance design of three core dimensions, namely firstly, a perception layer fault tolerance dynamically adjusts data fusion weights of geomagnetism, millimeter wave radar and vision AI according to real-time environment data such as rainfall, electromagnetic interference and the like through an integrated environment perception sub-module, secondly, a network layer fault tolerance utilizes an invariable transaction log and a Saga distributed transaction compensation mechanism, realizes double offline payment of local billing and digital RMB when cloud connection is interrupted and ensures consistency of data after network recovery, and finally, a hardware layer fault tolerance establishes a neighborhood cooperative protocol based on signature agent commands, and allows a healthy node to execute an unlocking instruction by safely checking proxy fault nodes. The invention effectively solves the pain points of environmental interference, network interruption, single-point hardware failure and the like in unattended parking management, and remarkably improves the robustness and financial security of the system.

Inventors

JI ZHONGYUAN
JI LEI
Tang Delang

Assignees

江苏若临物联科技有限公司

Dates

Publication Date: 20260505
Application Date: 20260212

Claims (10)

1. Road berth billing and control system for implementing multi-level fault tolerance, comprising one or more road Edge Controllers (ECU) and several Sensing and Control Units (SCU), characterized in that each SCU is associated with a road berth and that the SCU comprises a local sensor group comprising geomagnetic sensors and millimeter wave radars, an environment awareness submodule configured to detect real-time weather environmental conditions and physical field interference conditions around the berth, a physical Security Element (SE) configured to securely store at least one device-specific encryption key and to perform hardware-level asymmetric encryption operations, a non-volatile memory configured to store a hash-chain structure based immutable transaction log, an inter-device control network interface for low-delay peer-to-peer or ad hoc mesh communication with an adjacent SCU or ECU, a user local communication interface configured to interact with user terminals in near-field wireless data, an intelligent parking lock associated with the berth comprising mechanical execution mechanisms, The system comprises a motor driving circuit, a standby unlocking circuit controlled by a control network interface between devices, and a low-power consumption Microprocessor (MCU), wherein the ECU comprises a high-power processor, a control unit and a control unit, the high-power processor is configured to execute video AI analysis based on deep learning and send a structural identification result aiming at a berth occupation state to a corresponding SCU through a network, the MCU of the SCU is configured to execute specific instructions to realize multi-level fault-tolerant processing logic, wherein the multi-level fault-tolerant processing logic is used for (perception layer fault tolerance) receiving original sampling data of a local sensor group, the structural identification result sent by the ECU, and the control unit is used for receiving the original sampling data of the local sensor group in real time, The system comprises a local security module, an environment sensing submodule, an environment characteristic parameter feedback by the environment sensing submodule, a data fusion weight of each sensor in an occupied state judging algorithm based on the confidence degree of the environment characteristic parameter characterization, a network layer fault tolerance) and a physical security element, wherein the data fusion weight of each sensor in the local sensor group in the occupied state judging algorithm is dynamically adjusted to generate a final berth occupied state signal, the network layer fault tolerance is automatically switched to a local autonomous mode when a communication link interruption with a cloud platform or an ECU is detected, after a verified local support certificate is received through a local user communication interface, a local support record entry carrying a digital signature of the physical security element is created and added in the non-variable transaction log in the non-volatile memory, the intelligent parking stall lock is controlled to execute unlocking action according to the entry, the hardware layer fault tolerance) continuously monitors a control network interface between devices during normal operation, and when a signature proxy command pointing to an adjacent fault SCU is received, the multiple security verification is carried out by calling the physical security element, and at least comprises (a) using a pre-stored root certificate to public verify the digital signature carried in the signature proxy command or an authorized entity, and whether the random signature of the SCU is triggered by the MCU through the local security proxy command after the random verification has been carried out in the local security proxy command.
2. The road berth billing and control system for implementing multi-level fault tolerance of claim 1 wherein the environmental awareness submodule comprises at least one piezoelectric rainfall sensor and one Hall magnetic field monitor, wherein the MCU is configured to automatically reduce the weight coefficient of the millimeter wave radar in the decision algorithm if the sampled value of the piezoelectric rainfall sensor exceeds a preset rainfall intensity threshold value when the awareness layer fault tolerance logic is executed, and the MCU is configured to automatically reduce the weight coefficient of the geomagnetic sensor in the decision algorithm if the Hall magnetic field monitor detects that the background magnetic field fluctuation frequency is in a non-vehicle induction frequency band and the amplitude exceeds an interference threshold value.
3. The road berth charging and controlling system for realizing multi-level fault tolerance according to claim 1, wherein the high-computation-power processor of the ECU adopts a heterogeneous computing architecture and comprises a multi-core CPU and a special GPU accelerating unit, and the low-power microprocessor of the SCU adopts a Harvard architecture and is provided with an independent data bus and an independent instruction bus.
4. The system of claim 1, wherein the SCU is configured to start a data synchronization flow based on a Saga distributed transaction mode after detecting that a communication link is recovered, wherein the SCU actively pushes a local pay record entry which is not yet reported in the invariable transaction log to a cloud platform through an uplink, and the cloud platform forcedly executes a compensation transaction if a cloud order state is found to collide with the record entry after receiving and verifying the validity of the record entry and a digital signature thereof, rolls back and rewrites the cloud order state as "paid (offline)", thereby giving a local physical transaction fact the highest priority, and explicitly excluding a time stamp-based "last write-in" conflict resolution logic.
5. The road berth billing and control system for achieving multi-level fault tolerance of claim 1 wherein the MCU of the SCU maintains a circularly overlaid list of executed nonces in the non-volatile memory and, when processing the signed proxy command, if the Nonce is present in the list, the MCU determines the command as a replay attack attempt and reports a security alert message to the ECU.
6. The system for road berth billing and control for achieving multi-level fault tolerance of claim 1 wherein the user local communication interface supports digital Renminbi (e-CNY) dual offline payment protocol allowing the SCU to complete Trusted Execution Environment (TEE) based value transfer and unlock instruction validation with a terminal holding a hardware wallet by a user without both public network signaling and local area network connectivity.
7. The road berth charging and control system for achieving multi-level fault tolerance of claim 1, wherein the inter-device control network interface employs a low latency wireless sensor network protocol based on the IEEE802.15.4 standard, and each of the SCUs is logically configured as a routing node in a Mesh network (Mesh).
8. A multi-level fault tolerance method for road berth billing and control is carried out by a collaborative system comprising an Edge Controller (ECU) and Sensing and Control Units (SCU) distributed at each berth, and is characterized by comprising the steps of dynamically sensing fusion steps of collecting local geomagnetic data, radar data and external environment parameters in real time by the SCU and receiving berth state reference values generated by the ECU through a computer vision technology, reconstructing a weighted matrix with multiple source data fusion in real time based on the influence of the external environment parameters on signal-to-noise ratio of different sensing modes, thereby outputting a berth occupancy state judgment result with environment self-adaption capability, starting a local offline billing clock when the SCU detects network access layer failure, executing payment credential verification under the protection of a security element inside the SCU when a settlement request initiated by local near field communication is received, writing transaction metadata and equipment end signatures into an invariable transaction log with anti-physical tampering characteristics, subsequently opening a lock of the berth, responding to a cloud-state synchronous response platform by the cloud-state error-proof synchronous response platform when the SCU is in response to a global-state-error-proof command, and the cloud-state-synchronous-response platform is carried out, and the healthy adjacent SCU confirms the validity and timeliness of the instruction by verifying the asymmetric signature and the Nonce value of the instruction, and forcedly triggers a lockset mechanism associated with the fault SCU through a physical hard-wired link after the verification is passed.
9. The multi-level fault tolerance method for road berth billing and control of claim 8 wherein in the dynamic sense fusion step, when it is detected that the rainfall exceeds 5mm/h or the magnetic field fluctuation rate exceeds 200mG/s, the system down-regulates millimeter wave radar weight or geomagnetic sensor weight, respectively, and compensates the missing weight to the video AI analysis result weight proportionally.
10. The multi-level fault tolerance method for road berth billing and control of claim 8 wherein in the collaborative proxy unlocking step, the healthy neighbor SCU automatically enters a lock mode and cuts off its specific control command receiving channel with the external network when it detects that the number of signature verification failures exceeds a preset attack defense threshold.

Description

Road berth charging and control system for realizing multi-level fault tolerance and method thereof Technical Field The invention relates to the field of intelligent traffic management systems and safety control of the Internet of things, in particular to a road berth charging and control system and a method for realizing multi-level fault tolerance. Background In the construction process of modern smart cities, intelligent management of road side parking spaces is a key link for relieving the problem of difficult parking in the cities. With the wide application of geomagnetic sensors, millimeter wave radars and video recognition technologies, an automatic berth occupancy detection and automatic charging system gradually replaces the traditional manual inspection. However, since the road berthing system is deployed in a severe and complex outdoor street environment, the prior art solutions face serious robustness challenges in practical operation. First, the lack of reliability at the perception level is one of the core pain points of existing systems. A single sensor is extremely prone to false alarms in a particular environment. For example, although geomagnetic sensors have low power consumption and long service life, magnetic field measurement values of the geomagnetic sensors fluctuate drastically when they encounter underground power line switching, subway passing, or proximity stop amplification type metal vehicles. Millimeter wave radar has excellent detection precision in normal weather, but in heavy rain or road surface water accumulation environment, the absorption of electromagnetic waves by a water film and clutter reflection can lead to obvious reduction of signal to noise ratio and cause false detection results. Even if the video recognition technology is introduced, the recognition accuracy of the AI model is greatly reduced under the conditions of strong backlight, dense fog, night low illumination or lens shielding. The existing simple fusion algorithm often adopts fixed weight distribution, and can not dynamically avoid 'weak' sensing sources when the perceived environment is deteriorated. Second, the vulnerability of the network connection limits the service continuity of the system. Current parking management systems rely heavily on wide area wireless networks such as 4G/NB-IoT to transmit data to cloud platforms in real time. However, in the case of urban building obstruction, base station failure or the presence of malicious disruptors, network disruption is an inevitable normalcy. Once the network is disconnected, the existing system cannot complete the payment process, even the parking lock cannot be unlocked, so that a user vehicle is trapped in place, serious economic loss is caused, and legal disputes are extremely easy to cause. Meanwhile, how to ensure the final consistency between the locally generated payment data and the cloud billing system after the network is restored and prevent the charging logic conflict caused by concurrent writing is also a technical problem to be solved. Finally, single-point hardware failure is an unavoidable problem for outdoor internet of things equipment. Unpredictable physical damage to the communication modules, processors or sensors of individual berth control devices may occur due to prolonged exposure to sun and rain, rolling vehicles, and possibly malicious vandalism. When the equipment is changed into brick, the associated parking space lock loses response. The prior art generally only can carry special tools to the site for treatment by means of manual maintenance personnel, and has extremely long response time, thereby seriously affecting the service image of public infrastructure. Therefore, there is a strong need in the art for a parking charging and control system that is capable of adapting to environmental changes, is still capable of charging safely in a broken network state, and has a single point failure self-healing capability. Disclosure of Invention The invention aims to overcome the defects of the prior art, provide a system architecture and a protocol with three layers of fault tolerance capability of perception, network and hardware, and aims to ensure that a road berth management system still has extremely high availability and data integrity under extreme conditions. In order to achieve the above purpose, the present invention provides the following technical solutions: A road berth billing and control system for achieving multi-level fault tolerance, the system comprising one or more road Edge Controllers (ECU) and a number of Sensing and Control Units (SCU), each SCU being associated with a road parking berth and the SCU comprising a local sensor group comprising geomagnetic sensors and millimeter wave radars; an environment awareness submodule configured to detect real-time weather environmental conditions and physical field disturbance conditions around the berth, a physical Security Element (SE) configured to secure