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Integrated Systems And Specialized Vehicles
Integrated Systems And Specialized Vehicles
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Industrial Intelligence
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Intelligent Transportation
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Operation Management System
Overview
As the cloud-based "brain" of autonomous vehicle fleets, the Operation Management System serves as a important bridge between the business layer and autonomous fleets. Jingwei Hirain's Operation Management System comprises seven core functional modules: Business Integration, Vehicle Dispatch, Operation Management Engine, Traffic Coordination, Integrated Monitoring & Management, Operational Data Analytics, and Grayscale System. Driven by these modules, the system enables the practical deployment of autonomous fleets in scenarios such as container horizontal transportation at ports.
Solution Introduction
- Business Integration
Jingwei Hirain Operation Management System obtains the operation information to be executed by the unmanned fleet and the equipment information that cooperates with the unmanned vehicles through integration with business systems, providing necessary input for the vehicle dispatching and operation management engine. For the port container horizontal transportation scenario, the system has successfully integrated with multiple domestic and international terminal production and operation systems. It has also achieved system integration with several vertical transportation manufacturers for Quay Cranes (QCs) and Rail-Mounted Gantry Cranes (RMGs). Additionally, it has integrated with tally, gate, and intelligent yard equipment, building an information bridge for unmanned fleets to serve ports. Furthermore, at Jining Longgong Port, the system has expanded container horizontal transportation services to the railway yard for rail-water intermodal transportation scenarios.
- Vehicle Scheduling
As the core of Jingwei Hirain's fleet operation and scheduling management system, the vehicle scheduling system integrates information such as operational production plans, real-time fleet operation status, workload of port machinery and equipment, charging pile usage, and vehicle battery levels. It manages the switching of vehicle operational states (idle, on-duty, charging, and maintenance) and assigns operational instructions to on-duty vehicles, impacting the operational efficiency of unmanned fleets and the port as a whole. Aligned with production business scenarios and based on the core idea of operational optimization, Jingwei Hirain has developed a fleet scheduling system suitable for unmanned container horizontal transportation at port container terminals. This system has been validated in actual port production operations.
- Job Management Engine
The Job Management Engine is responsible for responding to operation instructions dispatched by the vehicle scheduling system. It plans the next tasks and navigation paths for unmanned vehicles based on business rules from the decision-making engine and sends them to the unmanned vehicles for execution. During task execution, it monitors the vehicle's operational status and manages business actions such as precise positioning, container loading/unloading, and twistlock assembly/disassembly. It responds to traffic scheduling results to intervene in the vehicle's driving process, monitors and diagnoses vehicle alarms and business process abnormalities, and establishes a closed loop among the cloud system, intelligent driving system, and remote driving system based on remote driving takeover decision rules. This integration enables better alignment between the remote driving system and fleet Operation Management System, facilitating rapid resolution of operational issues.
Built on the newly developed V4.0 system architecture, the Job Management Engine supports customized orchestration of business processes and decision rules based on user-specific business characteristics, enabling rapid project deployment and implementation.
- Traffic Dispatching System
The traffic dispatching system integrates functions such as traffic situation awareness, path planning, and traffic collaborative management. Based on vehicle operation status and task information, it builds a traffic situation model to quantify site congestion levels, and generates navigation path changes and lane-changing/overtaking intentions for unmanned vehicles. Leveraging high-precision map data and traffic situation information, the system plans suitable vehicle operation routes and selects reasonable dock access routes according to the distribution of quay cranes on the dock surface. It evaluates path conflict relationships between adjacent vehicles, and comprehensively decides vehicle passage sequences based on vehicle operation status, task priorities, and ultra-horizon perception information obtained via the intelligent field-side V2X system. Additionally, it enables linkage control of roadside traffic facilities such as gates and traffic lights, ensuring safe and efficient mixed operations of vehicle fleets and manually driven vehicles.
- Integrated Monitoring and Management
Register, manage, and configure all production elements involved in the fleet Operation Management System, including unmanned vehicles, on-vehicle terminal devices, port machinery equipment, geographic data, site terminal equipment (charging piles, traffic facilities, V2X, RSU), auxiliary positioning terminals, and human-machine interaction terminals. Monitor the operational status and health status of various production elements. Implement remote control operations for various devices, such as remote wake-up of vehicles, remote start/stop of vehicles, and remote configuration modification of intelligent terminals.
Additionally, supervise elements such as server resources, network resources, software applications, information security firewalls, databases, message middleware, and external business system gateways of the fleet Operation Management System, and provide real-time alarm reminders to ensure stable system operation.
- Operation Data
The Operation Management System records vehicle and equipment operation status, task instructions, key events, and other information to enable full-process operation traceability. By integrating business scenarios, it divides typical container horizontal transportation operation cycles into standard segments, presents operation energy consumption and efficiency data dashboards, marks abnormal data, and conducts multi-dimensional comparisons to identify efficiency bottlenecks, supporting system optimization and improvement. Additionally, it records and audits user operation behaviors, collects user usage preferences, and drives system iteration and upgrading.
- Gray Scale System
The fleet Operation Management System features a grayscale capability, supporting the configuration of multiple sets of dispatch decision rules and enabling zonal control over different vehicles. This facilitates A/B testing and reduces the associated impact of iterative upgrades to the system, achieving a certain level of operational transparency. Additionally, the system demonstrates stronger compatibility with iterative updates to the autonomous driving algorithms of unmanned vehicles, accommodating differences in vehicle architecture platforms, operational characteristics, and communication protocol versions.
Summary
The fleet Operation Management System developed by Jingwei Hirain can provide strong technical support for the implementation of unmanned driving fleets in specific scenarios such as ports. The integration of the fleet Operation Management System, remote driving system, and unmanned driving system helps realize the safe, efficient, and regular operation of unmanned driving fleets in fixed scenarios.
Key words:
Cloud Based Fleet Dispatching System
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