Neural Network
A machine learning model that mimics the human brain, allowing self-driving cars to learn from data.
Cruise control has long been a staple of long-distance driving, but Adaptive Cruise Control (ACC) takes things to the next level. Unlike traditional cruise control, which maintains a fixed speed regardless of what’s happening on the road, ACC continuously adjusts the vehicle’s speed based on traffic conditions, keeping a safe distance between you and the car ahead.
How It Works
ACC uses a combination of sensors—such as radar, cameras, and sometimes LiDAR—to monitor the road ahead. When the system detects a slower vehicle, it automatically reduces your car’s speed to maintain a pre-set following distance. Once the road clears, ACC accelerates back to your chosen speed. This ensures a smooth, safe ride without the need for constant manual adjustments.
Safety First
The real value of Adaptive Cruise Control lies in its ability to enhance driver safety. By automatically adjusting to traffic conditions, ACC reduces the chances of rear-end collisions caused by delayed human reactions. It also reduces driver fatigue, as you no longer need to continuously manage your speed during stop-and-go traffic or on long highway drives.
The Link to Autonomy
While ACC is considered a driver assistance feature today, it’s also a building block for fully autonomous driving. Systems like Artificial Intelligence (AI) play a key role in making ACC smarter by learning from real-world driving data and improving its ability to anticipate traffic patterns. Many higher-level autonomous driving systems, such as those at Level 2 or Level 3, build upon ACC’s foundation to enable even more complex driving tasks like lane-keeping and autonomous lane changes.
Adaptive Cruise Control may seem like a small convenience, but it’s a glimpse into the future of driving—where cars will handle more of the mundane tasks, and humans can focus on the road ahead, or maybe, one day, not focus at all.