The rapid proliferation of civilian drones, characterized by their low cost, compact size, and high degree of integration and intelligence, has transformed numerous sectors including aerial photography, surveying, agriculture, and logistics. This exponential growth presents significant challenges to existing air traffic management paradigms. The pressing need to integrate these vehicles safely and efficiently into national airspace has catalyzed the development of specialized Unmanned Aircraft System Traffic Management (UTM) frameworks globally. In China, this has evolved into the national Unmanned aircraft Operation Management (UOM) system, a structured approach that delegates substantial responsibility to provincial-level governments. This article analyzes the evolving landscape of provincial traffic management for civilian drones, examining established models and proposing a comprehensive framework for construction, drawing from domestic pilots and international best practices.
The foundational architecture for managing civilian drones in China is the national Unmanned aircraft Operation Management (UOM) system. This framework establishes a hierarchical, coordinated structure involving national authorities, provincial governments, service providers, and end-users. Its core principle is layered responsibility: national agencies set overarching policies, technical standards, and coordinate critical resources (e.g., access to core airspace data). Provincial governments, as the pivotal management entities, assume属地 safety management responsibilities. They are tasked with implementing the national framework locally, promoting the establishment of service providers, and ensuring users operate within the defined rules. This structure is visualized as follows:
The operationalization of this UOM framework at the provincial level has led to the emergence of distinct management models, shaped by local conditions, reform priorities, and institutional arrangements. Among these, two models stand out as particularly mature and instructive: the Low-altitude Collaborative Management “Sichuan Model” and the Province-wide Low-altitude Opening “Hunan Model.”
Analysis of Established Provincial Models
These two pioneering models offer valuable insights into the practical implementation of traffic management for civilian drones. Their approaches, while sharing common goals, differ in scope, institutional design, and operational focus.
The Low-altitude Collaborative Management “Sichuan Model”
This model emerged from early pilots focused on low-altitude airspace reform. Its cornerstone is the establishment of a streamlined civil-military-civilian coordination mechanism. A provincial-level coordination office, typically housed within an organization familiar with military liaison (e.g., Civil-Military Integration Office), acts as the lead entity. This office oversees a dedicated public institution responsible for daily operations, such as a Low-altitude Collaborative Operations Center.
The key innovations of this model are profound. First, it successfully transitioned from a strict “control” philosophy to a “managed” one. Instead of relying on air traffic controllers to隔离 all flight activities, it implements a “managed low-altity Visual Flight Rules (VFR) autonomous flight” paradigm. The operations center provides information services and necessary coordination, empowering users and significantly enhancing airspace utilization. This can be conceptually represented by a shift in the management function:
$$ \text{Old: Control}(C) = \text{Isolate}(Flight_i, Flight_j) \quad \forall i,j $$
$$ \text{New: Manage}(M) = \text{Inform} + \text{Coordinate} + \text{Deconflict}(Flight_k) $$
Second, it achieved a breakthrough in flight approval processes. It replaced the cumbersome multi-day “approval system” with a simplified “filing system.” Within designated pilot zones, operators of civilian drones can now file flight plans merely one hour in advance via multiple channels, enabling near real-time, flexible operations. The efficiency gain is dramatic:
$$ t_{\text{process-old}} = t_{\text{airspace-request}} (\geq 7 \text{days}) + t_{\text{plan-request}} (1 \text{day}) + t_{\text{clearance}} $$
$$ t_{\text{process-new}} = t_{\text{filing}} (\approx 1 \text{hour}) $$
where $t_{\text{process}}$ represents the total lead time required before flight.
The Province-wide Low-altitude Opening “Hunan Model”
This model takes a comprehensive, province-scale approach from the outset. It begins with a systematic planning and classification of the entire provincial low-altitude airspace (below 3,000 meters), categorizing it into Controlled, Surveillance, and Advisory airspace, and publishing a network of Visual Flight Routes (VFR). A cornerstone of this model is the establishment of a provincial A-type Flight Service Station (FSS) as the central operational node, providing “one-stop” services for flight applications and information.
A significant contribution of this model is the publication of official Visual Flight Charts for low-altitude operations, a critical tool long missing for pilots of civilian drones. Furthermore, it emphasizes building a robust technical and legal guarantee system. This includes a province-wide surveillance and communication network, a coordinated military-civilian operation management information system, and the enactment of provincial-level regulations (e.g., “General Aviation Regulations”) to institutionalize the reform outcomes. The model’s comprehensiveness aims to create a predictable, rules-based environment:
$$ \text{System Stability} \propto \frac{\text{(Technical Infrastructure + Regulatory Clarity)}}{\text{Operational Uncertainty}} $$
The comparative analysis of these two primary models can be summarized in the following table, highlighting their key characteristics and components essential for managing civilian drones:
| Core Element | “Sichuan Model” (Collaborative Management) | “Hunan Model” (Province-wide Opening) |
|---|---|---|
| Pilot Airspace Scope | Phased expansion within specific regions (e.g., 6,700+ km²). | Comprehensive planning for the entire province (240,000+ km² planned). |
| Lead Government Unit | Provincial Low-altitude Coordination Committee/Office (often under Civil-Military Integration structures). | Led by provincial government, with strong involvement of transportation and aviation authorities. |
| Primary Operational Unit | Dedicated Low-altitude Collaborative Operations Center (Public Institution). | Provincial A-type Flight Service Station (e.g., Changsha FSS). |
| Core Information Systems | Low-altitude Collaborative Operation System. | Integrated Provincial General Aviation Service Platform; Military-Civilian Coordinated Operation Management System. |
| Key Regulatory Support | Low-altitude Airspace Coordination Management and Use Provisions. | Provincial General Aviation Regulations; Published VFR Charts and Routes. |
| Operational Philosophy | Managed autonomous flight within defined zones; Simplified filing. | Rules-based, integrated low-altitude flight across the province; One-window service. |
A Proposed Framework for Constructing Provincial Management Models
Based on the analysis of existing models and the impending nationwide implementation of regulations like the “Interim Regulations on Flight Management of Unmanned Aircraft,” a generalized framework for constructing provincial traffic management systems for civilian drones can be proposed. This framework rests on three interdependent pillars.
1. Defining the Management Entity and Streamlining Coordination Mechanisms
The first and most critical step is to clearly designate a leading provincial government department with the authority and capability to interface effectively with military airspace management authorities. Success, as observed in the models, often hinges on smooth civil-military coordination. The lead department, potentially the Transportation Department, Civil-Military Integration Office, or a specially formed committee, must establish a permanent coordination mechanism that brings together all relevant stakeholders: public security, aviation regulators, air traffic control, and local governments. This mechanism is vital for unifying objectives, resolving conflicts, and developing a shared operational protocol for civilian drones. The effectiveness of this coordination (Ecoord) can be seen as a function of institutional mandate (M), communication frequency (C), and decision-making authority (A):
$$ E_{coord} = f(M, C, A) \approx k \cdot \frac{M \cdot A}{1/C} = k \cdot M \cdot C \cdot A $$
where $k$ is a system constant.
2. Establishing Operational Institutions and Building the Support System
To ensure day-to-day, reliable management, a dedicated operational institution is necessary. This is typically a public service unit or a government-trusted entity that operates 24/7, handling flight plan filings, dynamic monitoring, user communication, and紧急 coordination with air traffic control. This institution serves as the visible “nerve center” for all civilian drones activities in the province.
Concurrently, a robust technological support system must be deployed. This includes:
- Provincial UOM Platform: The software platform that interfaces with the national UOM, manages user registration, flight filings, and provides services.
- Surveillance and Communication Network: A network of ground-based radar, ADS-B receivers, and cellular-based tracking to monitor the real-time位置 of civilian drones in low-altitude airspace.
- Military-Civilian Information Exchange System: A secure system for sharing airspace status, flight plans, and alerts between the provincial operations center and military ATC.
The overall system capacity (SC) can be modeled as a product of its coverage, data integrity, and processing speed:
$$ SC = \text{Coverage}_{geo} \cdot \text{Data}_{integrity} \cdot \text{Speed}_{process} $$
3. Formulating Regulations and Legal Safeguards to Foster Industry Growth
Sustainable management requires a clear, accessible, and enforceable legal environment. Provincial authorities must develop detailed implementation rules that complement national regulations, addressing local specifics for civilian drones operations. This includes ordinances on no-fly zones, insurance requirements, liability, and privacy. Furthermore, user-friendly channels—such as dedicated websites and mobile applications—must be established for information dissemination, online training, and seamless flight filing. The goal is to reduce regulatory ambiguity, which is a major barrier to compliance and industry growth for civilian drones. The relationship between regulatory clarity (R), public accessibility (P), and industry growth (G) can be expressed as:
$$ G \propto \frac{R}{P^{-1}} = R \cdot P $$
Higher clarity and accessibility jointly promote growth.
The integrated framework, showing the interconnection of these three pillars, is summarized below:
| Framework Pillar | Core Components | Primary Output/Deliverable | Impact on Civilian Drones Ecosystem |
|---|---|---|---|
| Pillar 1: Governance & Coordination | Lead Department; Inter-agency Coordination Committee; Liaison Protocols with Military. | Clear authority; Streamlined decision-making process; Unified operational rules. | Reduces institutional friction; Enables predictable airspace access. |
| Pillar 2: Operations & Technology | Operational Center (FSS/Ops Center); UTM/UOM Platform; Surveillance Network; Communication Links. | 24/7 service capability; Real-time situational awareness; Efficient flight plan processing. | Ensures safety and efficiency; Provides reliable service to users; Enables high-density operations. |
| Pillar 3: Regulation & Engagement | Provincial Implementation Rules; Public Service Portals (Web/App); Industry Promotion Policies. | Legal certainty; Easy-to-use public interfaces; Stimulated market demand. | Encourages compliance; Lowers barrier to entry; Drives innovation and commercial adoption. |
Synthesis and Key Performance Considerations
The ultimate measure of a successful provincial traffic management system for civilian drones lies in its ability to balance safety, efficiency, and scalability. From the analyzed models and proposed framework, several performance metrics and principles emerge.
A critical metric is Airspace Utilization Rate (U). Moving from a restrictive control model to a managed or rules-based model aims to maximize this rate for civilian drones. It can be conceptually defined as the ratio of actual, safely conducted flight time to the total available flight time in a given airspace volume:
$$ U = \frac{\sum_{i=1}^{n} t_i}{T \cdot A} $$
where $t_i$ is the duration of the i-th flight, $n$ is the total number of flights, $T$ is the total time period observed, and $A$ is a normalization factor for airspace volume accessibility. Models that simplify filing (like Sichuan) and expand accessible routes (like Hunan) directly increase $n$ and $A$, thereby boosting $U$.
Another key principle is Management Scalability. The system must handle growth in the number of civilian drones and flight frequency. This requires automation in flight plan processing, conflict detection, and user communication. The management workload ($W$) should scale sub-linearly with the number of operations ($N_{ops}$):
$$ W \propto N_{ops}^{\alpha}, \quad \text{where } 0 < \alpha < 1 \text{ is desirable}. $$
A value of $\alpha$ close to 1 indicates manual, non-scalable processes, while a lower $\alpha$ indicates effective automation, a hallmark of a mature UTM system for civilian drones.
Finally, User Compliance Rate (C) is fundamental. Compliance is driven by the perceived ease of legal operation versus the risk and effort of “rogue” flights. A well-constructed provincial system increases compliance by minimizing the “friction coefficient” ($f$) for legal operations through easy filing, clear rules, and useful services:
$$ C \propto \frac{1}{f_{\text{legal}}} \quad \text{and} \quad f_{\text{legal}} = g(\text{Complexity}, \text{Time}, \text{Cost}) $$
The models studied actively work to reduce $f_{\text{legal}}$ by cutting complexity and time, thereby increasing $C$ and overall safety for all civilian drones operations.
In conclusion, the management of civilian drones at the provincial level is evolving from isolated experiments into a structured discipline. The national UOM framework provides the overarching architecture, while provincial models like the collaborative and province-wide opening approaches demonstrate viable implementation paths. The future lies in synthesizing these experiences into a robust, three-pillar construction framework centered on clear governance, capable operational institutions supported by technology, and a nurturing legal-regulatory environment. As regulations solidify and technology advances, the provincial role will become increasingly central in unlocking the immense economic and social potential of civilian drones, ensuring their safe and harmonious integration into our shared skies.