Introduction

In the early spring of 2026, Guangzhou’s Nansha district faced a unique ‘final exam’.

Experts from the Guangdong Provincial Department of Transport and the China Academy of Transportation Sciences jointly conducted an on-site evaluation of the ‘Nansha Urban Mobility Service Autonomous Driving Pilot Project,’ which had been in operation for nearly two years. The results surpassed all expectations—every project goal was exceeded.

WeRide (Official Account: WeRide) believes this success is not merely a triumph for Guangzhou but signifies a distinctive path China has carved out in the global autonomous driving technology race: a path characterized by government leadership, vehicle-road coordination, full-chain integration, and contiguous demonstration.

(For further reading, click: ‘Xinhua News Reporter Experiences Driverless Cars in Guangzhou’s Nansha: ‘Smooth Ride’ Leaves Strongest Impression’)

I. Evaluation Site: ‘Hardcore’ Data Surpassing Targets

The experts’ first destination was the Nansha Mingzhu Bay Urban Operations Management Center. On a vast screen, real-time operational data of autonomous vehicles, traffic flow, and road conditions continuously flickered.

The crux of the evaluation lay in the data, and Nansha delivered ‘hardcore’ results:

1. Scalable Operational Data

During the pilot, over 300 autonomous passenger vehicles were deployed for mobility services.

What does this figure represent? It is equivalent to the entire fleet size of a mid-sized taxi company.

These vehicles collectively accumulated 22.85 million kilometers—enough to circle the Earth 570 times. More critically, they facilitated 3.01 million actual passenger trips.

This demonstrates that autonomous driving has seamlessly integrated into the urban public transport system, becoming a viable travel option for citizens.

2. Technical Reliability Data

In the Lingshan Island Tip area, the project established a new infrastructure system covering seven key sectors, including perceptual infrastructure, cloud-network infrastructure, and application support platforms.

This ‘vehicle-road-cloud integration’ system ensures the safe operation of autonomous vehicles in complex urban environments.

The L4 autonomous vehicles tested by the expert group smoothly completed trips from the operations center to Pony.ai’s base, navigating through complex scenarios such as pedestrian crossings, vehicle cut-ins, and construction zones.

3. Refined Regulatory Data

The project’s command, dispatch, and supervision platform incorporates over 390 functional points, enabling minute-level supervision of autonomous mobility services and real-time traffic situation updates.

The real-time visibility, controllability, and traceability of every autonomous vehicle’s location, status, and operational data provide technical safeguards for safety regulation in large-scale commercial operations.

Behind these figures lies a profound transformation: autonomous driving has officially transitioned from the ‘technology validation’ phase to the new stages of ‘service validation’ and ‘commercial validation.’

II. The Nansha Model: How Was the Full-Chain Closed Loop Achieved?

The success of Nansha’s pilot was no accident. It stems from a meticulously designed ‘full-chain closed-loop’ model, summarized as ‘Five Integrations.’

1. Integration of Technical Routes

The project created a full-link collaboration model combining ‘onboard perception + roadside coordination + remote support.’

Vehicles possess comprehensive perceptual decision-making capabilities, roadside devices provide beyond-line-of-sight and blind-spot information supplementation, while cloud platforms offer global scheduling and remote assistance.

This ‘triple-redundancy’ design significantly enhances system safety under extreme conditions.

2. Integration of Construction and Operation

The Mingzhu Bay Management Bureau assumed overall governance responsibilities, collaborating with 11 participating entities including OEMs, tech companies, and mobility platforms.

This ‘government-facilitated, enterprise-driven’ model ensures public attributes and regulatory uniformity while leveraging market players’ technological advantages and operational efficiency.

3. Integration of Data Applications

Autonomous vehicles in Nansha serve not just as mobility tools but also as front-end mobile sensing units. The massive real-time road traffic data they collect identifies hazards like road damage, missing signage, and traffic congestion, directly supporting urban traffic governance.

The project has established data interconnection mechanisms between autonomous vehicles and Nansha traffic police, exploring coordination with municipal intelligent connected vehicle management platforms.

4. Integration of Standards and Policies

The pilot not only validated technologies but also produced regulations. It has driven the release of five group standards and prompted over ten related policy documents.

These practice-derived standards provide valuable ‘Nansha Experience’ for formulating national L4 autonomous driving market access standards.

5. Integration of Industrial Ecosystems

The project established the world’s first high-grade autonomous vehicle model integration production line, achieving unified R&D, production, integration, and mass rollout.

This means Nansha is not just ‘using’ autonomous driving but ‘manufacturing’ it.

III. Industrial Upgrading: From ‘Demonstration Lines’ to ‘Industrial Chains’

Another significant achievement of Nansha’s pilot is successfully transforming autonomous driving from demonstration routes into complete industrial chains.

At Pony.ai’s operations center, experts witnessed the world’s first high-grade autonomous vehicle model integration production line.

Unlike traditional automotive production lines, this facility is specifically designed for batch retrofitting and system integration of autonomous vehicles. It integrates sensor installation, wiring harness layout, computing platform debugging, and system calibration, efficiently converting ordinary passenger vehicles into L4-capable smart vehicles.

The establishment of this production line resolves a critical bottleneck for autonomous driving commercialization: scalable mass production capacity.

More importantly, this line has attracted upstream and downstream enterprises.

Sensor suppliers, computing chip companies, wiring harness manufacturers, software algorithm firms—a self-driving-centric industrial cluster is taking shape in Nansha.

This ‘application-driven industrial development, industry-promoted application’ model represents China’s unique strength in cultivating strategic emerging industries.

IV. Urban Agglomeration Model: A ‘Contiguous Experiment’ in the Guangdong-Hong Kong-Macao Greater Bay Area

Nansha’s pilot ambitions extend beyond its borders.

One of its most forward-looking initiatives is actively promoting mutual recognition and open access agreements with major Guangdong-Hong Kong-Macao Greater Bay Area regions.

Currently, Nansha has collaborated with Qianhai, Bao’an, Hengqin, and other areas, covering major traffic nodes like airports, high-speed rail hubs, and metro stations.

This means an autonomous vehicle licensed for testing in Nansha could theoretically operate unrestricted in these regions.

(For further reading, click: ‘One Pass for Six Cities: Driverless Vehicles Finally Cross-City ‘Visit’! Guangzhou, Shenzhen, Foshan, Huizhou, Dongguan, Zhongshan Achieve Intelligent Connected Vehicle Mutual Recognition’)

This seemingly simple ‘mutual recognition’ represents a major breakthrough in dismantling administrative barriers and achieving regional coordination. It has created China’s first urban agglomeration-level contiguous application demonstration for autonomous mobility services.

The value of this ‘contiguous experiment’ is immense:

1. It better approximates real commercial scenarios. Passengers may need to travel from Nansha to Shenzhen Airport or from Hengqin to downtown Guangzhou. Contiguous demonstration makes such cross-city trips possible, validating technology reliability in more complex, longer-distance scenarios.

2. It amplifies network effects. When connected into a network, vehicles can be dispatched across wider areas to serve more diverse mobility needs, significantly boosting operational efficiency and economic benefits.

3. It provides replicable governance experience for the nation. How to coordinate traffic regulations, data standards, insurance policies, and accident liability across cities? Nansha’s exploration with Greater Bay Area partners seeks answers to these complex issues.

V. The Nansha Model: Breaking Open China’s Autonomous Driving Path

The evaluation of Nansha’s autonomous driving pilot project marks a ‘milestone’ for China’s autonomous driving industry.

It not only proves the feasibility of L4 autonomous driving technology but also demonstrates a new model of synergistic development among ‘technology + industry + urban governance.’

However, we must remain clear-eyed about the challenges ahead in autonomous driving commercialization:

• How to further reduce costs for wider vehicle adoption;

• How to address data security and privacy protection;

• How to develop more comprehensive laws and regulations to ensure orderly development.

These issues require joint efforts from government, enterprises, and society.

Nevertheless, Nansha’s success offers hope.

It proves through action that autonomous driving is not a ‘distant future’ but an ‘ongoing present.’

Perhaps in the near future, when we board autonomous vehicles, we’ll recall Nansha’s 300 vehicles, their 22.85 million kilometers, and all those who worked tirelessly for autonomous driving.

In conclusion, WeRide (Official Account: WeRide) believes:

Nansha’s ‘autonomous driving moment’ is just the beginning for China’s autonomous driving industry.

Looking ahead, we have reason to believe autonomous driving will transform our lives like smartphones, making cities better places.

What do you think?

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