China set to advance intelligent, integrated, multi-dimensional transport network by 2030

An autonomous monorail train runs in Wuhu, east China's Anhui province. (Photo/Tao Haijin)

China is accelerating the integration of artificial intelligence (AI) into its transportation sector, aiming to establish an intelligent, integrated, and multi-dimensional national transport network by 2030. A recently issued government guideline outlines 16 targeted tasks across four strategic areas, including technological innovation and scenario-based application, in a bid to enhance mobility, improve safety, and reduce environmental impact.

The guideline emphasizes self-reliance in core technologies and sets out a roadmap to ensure China's transport infrastructure ranks among the world's most advanced by the end of the decade. The strategy centers on breakthroughs in applied AI technologies, innovation in intelligent transport products, and the development of large AI models tailored to comprehensive transport systems.

"Strengthening the supply of key technologies is essential to build a full innovation chain from research and development to practical application," said Wang Yunpeng, an academician of the Chinese Academy of Engineering and president of Beihang University. Wang added that developing large-scale AI models would enable the creation of a "transport brain," equipped with high-quality datasets, algorithm libraries, and digital toolchains to support intelligent transformation across the sector.

Progress in large transport models is already well underway. The Transport Foundation Model Innovation and Industrial Alliance -- launched under the guidance of China's Ministry of Transport -- has brought together more than 50 leading enterprises, AI companies, and universities and research institutes, identifying 860 typical AI application scenarios.

A model of a smart transport system is exhibited by China Communications Construction Company Limited at the Seventeenth International Exhibition on Transport Technology and Equipment, July 3, 2025. (Photo/Guo Junfeng)

At the enterprise level, China Logistics Group introduced a large model serving over 40 specific scenarios, including multimodal transport and warehouse scheduling. A "smart hub" built upon a transport large model developed by Chinese tech firm Baidu has been deployed in over 10 cities, serving over 1 million vehicles equipped with L2 driver-assistance driving systems.

"Demonstration regions across the country are applying large-model-based solutions in areas such as road network monitoring and early warning, active management of high-traffic corridors, and integrated mobility services," said an official from China's Ministry of Transport. By enhancing capacity along major transport routes and implementing multi-tiered, refined traffic management models, these demonstration corridors have achieved approximately a 20 percent increase in traffic efficiency and a 30 percent improvement in emergency response efficiency during unforeseen events.

Enabled by big data analytics and high-precision modeling, AI is establishing a robust digital foundation for China's transport infrastructure. Statistics show that the 20 designated demonstration regions for digital transformation of highway and waterway infrastructure now encompass more than 60,000 kilometers of upgraded corridors, comprising approximately 54,000 kilometers of highways and 7,500 kilometers of waterways. These improved sections form a critical backbone of the national integrated, multi-dimensional transport network.

Diverse application scenarios are essential for driving the deep integration of AI into the transportation sector. The newly issued guideline identifies intelligent application scenarios across seven major areas, including assisted driving, smart railways, and smart shipping, designed to accelerate innovation through real-world implementation. "These scenarios span almost all segments of the transport system, offering broader opportunities for testing and deploying new technologies and products," Wang said.

An autonomous bus runs in Guiyang, southwest China's Guizhou province. (Photo/Jia Zhi)

On the waterways front, China now has 52 automated terminals. Domestically developed intelligent operating systems for fully automated container terminals have been implemented at more than a dozen terminals both domestically and internationally. Electronic navigation charts for waterways have been successfully deployed along the Yangtze River's main and branch routes. The accelerated adoption of intelligent technologies across ports, waterways, and vessels is significantly enhancing the efficiency of waterborne transport.

Parallel advancements are also transforming China's road networks. The Beijing-Xiong'an expressway, powered by Baidu AI Cloud, leverages the collaboration between vision and language-based large models to deliver second-level alerts for major traffic anomalies. Didi Autonomous Driving, in collaboration with Chinese automaker GAC Aion, has developed a new generation of factory-installed autonomous-driving vehicles. As autonomous driving converges with vehicle-road collaboration, a growing number of "smart vehicles" are taking to "smart roads," accelerating the evolution of intelligent mobility.

Deep integration of AI and transportation also depends on next-generation infrastructure. The guideline outlines targeted measures in terms of computing power, data, and networks to strengthen the supply of essential elements.

For computing power, the guideline calls for better coordination of computing resources within the transport sector and strengthening computing capacity based on major transport infrastructure and local conditions.

In terms of data, China will accelerate the development of comprehensive transport big-data centers, promote data sharing, and build high-quality dataset construction to fully leverage data as a production factor.

In terms of network infrastructure, the guideline calls for the integrated application of multiple network technologies, the construction of intelligent sensing systems and the development of high-speed data transmission channels to enable low-latency, high-reliability, and wide-coverage connectivity for vehicle-road collaboration, remote operations, and real-time monitoring.