Almost all vehicle accidents are caused by human error, which can be avoided with Advanced Driver Assistance Systems (ADAS). The role of ADAS is to prevent deaths and injuries by reducing the number of car accidents and the serious impact of those that cannot be avoided.

Autonomous application solutions are partitioned into various chips, called SoCs (systems on a chip). These chips connect sensors to actuators through interfaces and high-performance ECUs (electronic controller units).

Self-driving cars use a variety of these applications and technologies to gain 360-degree vision, both near (in the vehicle’s immediate vicinity) and far. That means hardware designs are using more advanced process nodes to meet ever-higher performance targets while simultaneously reducing demands on power and footprint.

Some of the most common ADAS applications are:

Adaptive cruise control (ACC) is particularly helpful on the highway, where drivers can find it difficult to monitor their speed and other cars over a long period of time. Advanced cruise control can automatically accelerate, slow down, and at times stop the vehicle, depending on the actions other objects in the immediate area.

Glare-free high beam and pixel light uses sensors to adjust to darkness and the vehicle’s surroundings without disturbing oncoming traffic. This new headlight application detects the lights of other vehicles and redirects the vehicle’s lights away to prevent other road users from being temporarily blinded.

Adaptive light control adapts the vehicle’s headlights to external lighting conditions. It changes the strength, direction, and rotation of the headlights depending on the vehicle’s environment and darkness.

Automatic parking helps inform drivers of blind spots so they know when to turn the steering wheel and stop. Vehicles equipped with rearview cameras have a better view of their surroundings than traditional side mirrors. Some systems can even complete parking automatically without the driver’s help by combining the input of multiple sensors.

Autonomous valet parking is a new technology that works via vehicle sensor meshing, 5G network communication, with cloud services that manage autonomous vehicles in parking areas. The vehicles sensors provide the vehicle with information about where it is, where it needs to go, and how to get there safely. All this information is methodically evaluated and used to perform drive acceleration, braking, and steering until the vehicle is safely parked.

Car navigation systems provide on-screen instructions and voice prompts to help drivers follow a route while concentrating on the road. Some navigation systems can display exact traffic data and, if necessary, plan a new route to avoid traffic jams. Advanced systems may even offer Heads Up Displays (HuD) to reduce driver distraction.

Night vision systems enable drivers to see things that would otherwise be difficult or impossible to see at night. There are two categories of night vision implementations: Active night vision systems project infrared light, and passive systems rely on the thermal energy that comes from cars, animals, and other objects.

Blind spot detection systems use sensors to provide drivers with important information that is otherwise difficult or impossible to obtain. Some systems sound an alarm when they detect an object in the driver’s blind spot, such as when the driver tries to move into an occupied lane.

Automatic emergency braking uses sensors to detect whether the driver is in the process of hitting another vehicle or other objects on the road. This application can measure the distance of nearby traffic and alert the driver to any danger. Some emergency braking systems can take preventive safety measures, such as tightening seat belts, reducing speed, and adaptive steering to avoid a collision.

This relatively new ADAS feature supports the vehicle in counteracting strong crosswinds. The sensors in this system can detect strong pressure acting on the vehicle while driving and apply brakes to the wheels affected by crosswind disturbance.

Driver drowsiness detection warns drivers of sleepiness or other road distractions. There are several ways to determine whether a driver’s attention is decreasing. In one case, sensors can analyze the movement of the driver’s head, and heart rate to determine whether they indicate drowsiness. Other systems issue driver alerts similar to the warning signals for lane detection.

The driver monitoring system is another way of measuring the driver’s attention. The camera sensors can analyze whether the driver’s eyes are on the road or drifting. Driver monitoring systems can alert drivers with noises, vibrations in the steering wheel, or flashing lights. In some cases, the car will take the extreme measure of stopping the vehicle completely.

Automobiles are the foundation of the next generation of mobile-connected devices, with rapid advances being made in autonomous vehicles.

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