Analysis of Investment Opportunities in Intelligent Transportation and Computing Infrastructure under AI+Transportation Policy

Based on the latest “AI+Transportation” policy issued by the Ministry of Transport, this report systematically analyzes its impact on investment opportunities in the fields of intelligent transportation and computing infrastructure.

The Ministry of Transport’s “Implementation Opinions on Accelerating the Development and Utilization of Public Data Resources in Transportation” marks that the digital transformation of the transportation industry has entered a

. The core points of the policy include:

1. Development and Utilization of Data Resources
   : Promote the construction of high-quality datasets in the transportation industry and break data silos
2. Collaboration of Computing Resources
   : Make full use of computing resources at national hub nodes to implement the “Eastern Data Western Computing” initiative in the transportation sector
3. AI+Transportation Applications
   : Support “Artificial Intelligence + Transportation” application scenarios, upgrading from traditional informatization to intelligentization
4. Open Sharing of Public Data
   : Establish a system for the development and utilization of transportation public data resources to promote the marketization of data elements

:

1. Vehicle-Road Collaboration (V2X) Infrastructure
   • Deployment of Road-Side Units (RSU)
   • Construction of edge computing nodes
   • Coverage of 5G+V2X networks

2. Intelligent Connected Vehicle Industry Chain
   • Smart cockpit systems
   • Autonomous driving algorithms
   • High-precision maps and positioning

3. Intelligent Traffic Management Platform
   • Traffic big data analysis
   • Intelligent signal control
   • Urban traffic brain

• Communication module manufacturers
  : Benefit from large-scale deployment of vehicle-road collaboration equipment
• Road-side equipment suppliers
  : Surge in demand for intelligent road-side units (RSU) and road-side perception devices
• Automotive-grade chip enterprises
  : V2X communication chips, on-board computing chips

• Urban intelligent traffic solution providers
  : Traffic signal optimization, violation monitoring, parking management
• Highway intelligent transformation enterprises
  : ETC upgrade, free-flow toll collection, intelligent monitoring
• Port and shipping intelligent service providers
  : Automated terminals, intelligent scheduling systems

• Traffic big data companies
  : Data cleaning, annotation, analysis services
• Travel service platforms
  : AI-based intelligent travel planning
• Logistics technology enterprises
  : Intelligent scheduling, route optimization, supply chain management

AI applications in the transportation industry will bring

:

1. Training computing power
   : Autonomous driving model training, traffic prediction models
2. Inference computing power
   : Real-time traffic signal optimization, intelligent scheduling decisions
3. Edge computing power
   : Edge computing capabilities of road-side devices

• Third-party IDC operators
  : Benefit from the growth of computing demand in the transportation industry
• Green energy-saving solution providers
  : Liquid cooling technology, waste heat recovery
• Power distribution and temperature control equipment manufacturers
  : UPS, precision air conditioners, cabinet equipment

• Intelligent computing center operators
  : Provide AI training and inference services
• Computing power leasing platforms
  : Flexible computing resource allocation
• Computing power scheduling service providers
  : Computing network optimization, load balancing

• Optical communication module enterprises
  : 400G/800G high-speed optical modules
• Network equipment suppliers
  : Switches, routers, load balancers
• Chip design companies
  : AI chips, GPU, FPGA

• Western data center operators
  : Leverage low-cost electricity and climate advantages
• Data transmission enterprises
  : Construction of east-west data transmission networks
• Computing power scheduling platforms
  : Cross-regional computing resource optimization and allocation

Segment	Key Technical Elements	Focus Areas
V2X Equipment	Communication modules, RSU	Technology leadership, market share
Intelligent Traffic Platform	Big data, AI algorithms	Project implementation, operational capability
Autonomous Driving	Perception, decision-making algorithms	Technical accumulation, ecological cooperation
Smart Cockpit	Human-machine interaction, system integration	Mass production capability, customer resources

Segment	Core Competitiveness	Focus Areas
Data Center Operation	Cabinet scale, PUE level	Expansion capability, customer structure
Intelligent Computing Services	Computing scale, scheduling capability	Technical barriers, profit model
Computing Equipment	Performance, energy efficiency ratio	Technology leadership, domestic substitution

:

• Intelligent traffic demonstration projects
  : First-tier cities, highways, ports and airports
• Computing power leasing market
  : Explosive short-term computing demand, high elasticity of leasing services
• Data element concept
  : Traffic data trading platforms, data service providers

:

• AI algorithm companies
  : Companies with independent intellectual property rights in traffic AI models
• Chip design enterprises
  : Domestic automotive-grade chips, AI training chips
• Platform-type companies
  : Companies building ecosystems with significant network effects

1. Policy implementation below expectations
   : Local fiscal pressure may affect project progress
2. Technology iteration risk
   : Rapid changes in AI technology lead to uncertain technical routes
3. Valuation risk
   : Some targets have high valuations; vigilance against callback risks
4. Deterioration of competitive landscape
   : Massive capital inflow may lead to price wars

:

1. Policy progress
   : Bidding status of intelligent traffic projects in various regions
2. Technology breakthroughs
   : Progress in core technologies such as autonomous driving and V2X
3. Business model
   : Profitability verification of data operation and computing power leasing
4. Capital expenditure
   : Investment intensity of industry leaders in the AI+Transportation field
5. International cooperation
   : Technical cooperation with internationally advanced enterprises

---

The Ministry of Transport’s “AI+Transportation” policy brings

to the intelligent transportation and computing infrastructure sectors. Investors are advised to:

1. Grasp core themes
   : V2X infrastructure, intelligent traffic platforms, computing power services
2. Focus on leading enterprises
   : Head enterprises with technical accumulation and project implementation capabilities
3. Diversify investment risks
   : Balanced allocation across equipment, software, and operation links
4. Long-term value investment
   : AI+Transportation is a long-term trend; avoid short-term speculation

The current period is a policy dividend release phase. Investors are advised to actively pay attention to relevant investment opportunities while remaining rational and selecting high-quality targets with real core competitiveness and sustainable profitability.

: Due to limited access to real-time data, the above analysis is based on policy logic and industry trends. It is recommended to conduct a comprehensive judgment combining specific companies’ financial data, valuation levels, and market performance before making actual investment decisions.