On-Board Computing Power

On-board computing power (On-Board Computing Power / Vehicle-Level Computing Performance) refers to the total computational instructions executed per unit of time by all on-board central processing units (CPUs), graphics processing units (GPUs), microcontrollers (MCUs), and dedicated artificial intelligence neural network processing chips (such as NPUs and ASICs) within an intelligent connected vehicle. Floating-point operations per second (FLOPS, alongside TOPS and TFLOPS) serve as primary measurement benchmarks. As vehicles advance towards high-level autonomous driving, intelligent cockpits, and centralized electronic and electrical (E/E) architectures, on-board computing power has become a definitive benchmark for assessing a vehicle's intelligence, data throughput, and AI processing capability.

Core Technical Architectures and Application Scenarios

The technical deployment and hardware architecture of on-board computing power primarily centre on two core functional domains: autonomous driving and the intelligent cockpit: 

AI neural network real-time inference in autonomous driving (Autonomous Driving AI Inference):

In advanced driver assistance systems (such as urban navigation assistance and autonomous driving), the vehicle continuously gathers ambient environmental data at high frame rates via comprehensive sensor suites, including LiDAR, high-definition cameras, and millimetre-wave radars. High-performance on-board computing chips (such as those from NVIDIA, Qualcomm, or proprietary silicon developed by carmakers) must execute millisecond-level parallel computing, point cloud processing, object detection, and path planning across multi-modal data streams, prompting precise steering, acceleration, or braking decisions. 

Multi-modal interaction and virtual engine rendering in intelligent cockpits (Smart Cockpit Multi-Modal Interaction & Rendering):

In modern intelligent cockpits, on-board computing power drives multi-screen setups, 3D dynamic vehicle UI rendering, localized full-duplex wake-word-free voice AI models, and in-cabin biometrics (such as driver fatigue monitoring and gesture control). This robust computing performance eliminates lag in in-vehicle infotainment (IVI) systems, delivering a fluid, responsive human-machine interface (HMI) experience on par with premium consumer tablets.

Safety Specifications and Physical Limitations 

Strictly avoid participating in a "computing power arms race" by fitting ultra-high-power chips while neglecting the thermal dissipation limits of automotive-grade silicon under sustained heavy loads (Prohibiting Overlooking Thermal Dissipation Limits of High-Power Chips):

Automotive-grade chips demand uncompromising stability and reliability. Operating high-load computing systems without matching cooling capacity or running unauthorized overclocks is strictly discouraged. Under prolonged exposure to scorching sun or extreme tropical heat, if liquid or air cooling fails and chip temperatures exceed junction limits (Tj), the system will trigger automatic thermal throttling. This can result in instant lag, black screens, or full system reboots across the autonomous driving domain or infotainment display, posing severe safety hazards. 

Strictly avoid equating high on-board computing power figures with actual on-road safety, and do not activate unsupervised autonomous driving under complex or non-standard road conditions (Prohibiting Equating High Computing Power with Unconditional Autonomous Safety): 

Computing power provides the essential hardware foundation for vehicle intelligence, but it does not guarantee absolute driving safety. Placing blind faith in raw specifications and neglecting human supervision is dangerous. Even with computing performance exceeding hundreds or thousands of TOPS, software algorithms can still face blind spots caused by adverse weather, sensor occlusion, or rare edge cases. Drivers must remain vigilant at all times and stay prepared to intervene immediately to ensure overall vehicle safety.