Cooperative Vehicle-Infrastructure System (CVIS)

The Cooperative Vehicle-Infrastructure System (CVIS) refers to an intelligent transport system that leverages next-generation telecommunications and internet technologies to facilitate comprehensive, real-time data exchange and coordinated control across vehicles, road infrastructure, other road users, pedestrians, and cloud platforms. It represents a vital roadmap for Intelligent Connected Vehicles (ICVs) transitioning from standalone "single-vehicle intelligence" to holistic "vehicle-road-cloud" integrated intelligence, serving as a core pillar for the future smart mobility ecosystem.

Concept Distinction: Intelligent Connected Vehicles vs. CVIS

While Intelligent Connected Vehicles (ICVs) focus on on-board intelligence and connectivity features within the vehicle itself, CVIS centres on system-level collaboration between vehicles and infrastructure. Its underlying philosophy shifts the vehicle from being an isolated perception and decision-making unit to one empowered by external infrastructure, sharing comprehensive real-time data to refine driving decisions. Put simply: intelligent connectivity equips each vehicle with a "smart brain", while CVIS plugs that brain into a wide-area "bird's-eye view" sensory network.

Core Components and Technical Architecture

CVIS operates on an integrated four-in-one architecture of "Vehicle-Road-Cloud-Network", with Roadside Units (RSUs) and roadside edge computing nodes serving as pivotal infrastructure.

• Roadside Perception Layer ("Eyes"): Roadside equipment such as cameras, millimetre-wave radars, and LiDAR sensors monitor real-time movements of vehicles, pedestrians, and obstacles within a 500-metre radius, effectively eliminating blind spots beyond the reach of on-board vehicle sensors.

• Communication Network Layer ("Nerves"): Utilises C-V2X (Cellular Vehicle-to-Everything) or Dedicated Short-Range Communications (DSRC) to deliver millisecond-level, low-latency transmission. The vast bandwidth of 5G networks further enables real-time high-definition (HD) mapping updates along with seamless sensor data fusion and sharing.

• Edge Computing and Cloud Control Layer ("Brain"): Roadside edge computing nodes process and synthesise massive streams of raw sensory data locally into actionable structured information. Simultaneously, the cloud platform manages macro-level traffic optimisation and AI model training, harmonising broad-scale traffic management with hyper-local real-time responses.

Core Application Scenarios: From Safety to Traffic Efficiency

The real-world value of CVIS spans traffic safety, road efficiency, and the deployment of autonomous driving:

• Active Safety and Hazard Alerts: Offering "beyond-line-of-sight" detection, it provides fundamental safety warnings for intersection collisions, emergency braking, and vulnerable road users. Vehicles can detect hidden hazards well in advance, affording drivers vital reaction time. Pilot data from Wuxi, China, demonstrated a 28% reduction in traffic accidents following the implementation of this technology.

• Traffic Flow Optimisation: Smart traffic signals dynamically adjust cycle times based on live traffic volume, facilitating "green wave" corridors where platoons of vehicles along arterial roads can travel through successive green lights with minimal stops. Studies show this can trim average journey times by 15% to 20% while cutting fuel consumption by roughly 10%.

• Enabling High-Level Autonomous Driving (L4/L5): In intricate urban environments or adverse weather, CVIS functions as a critical redundancy layer for standalone vehicle intelligence, overcoming the sensory limitations of on-board hardware to bolster autonomous safety and operational efficiency. Notably, Baidu Apollo's Robotaxi registered a 35% improvement in junction clearance efficiency through CVIS integration.

Industry Landscape and Standardisation

As of 2026, the fitment rate of Level 2 and higher driver assistance systems in new passenger cars in China has surpassed 60%, marking an accelerated transition from standalone vehicle intelligence towards collaborative ecosystem intelligence. Against this backdrop, standardisation has emerged as a crucial catalyst. In March 2026, the Chinese Association of Automation rolled out two key standard frameworks: "Cooperative Intelligent Connected Vehicles Based on Advanced Mobile Communications" and "Autonomous Driving on Complex Roads". These represent the first systematic technical standards tailored for vehicle-road-cloud collaborative driving and complex urban driving conditions, aiming to eliminate data silos among vehicles, roads, and the cloud while establishing a technical bedrock for connected mobility.

Key Takeaway: CVIS serves as a system-level infrastructure supporting automated driving and smart transport networks. While it functions as a crucial complement and performance booster for standalone vehicle systems, its efficacy and real-time reliability remain heavily dependent on cellular network coverage and stability. Motorists must never rely solely on roadside alerts at the expense of their own situational awareness, and remain ultimately responsible for vehicle safety behind the wheel.