Four Functions of Automotive Inertial Sensors

Since automakers first adopted MEMS accelerometers to trigger airbags, inertial sensors have laid the foundation for the widespread application of accelerometers in modern Advanced Driver Assistance Systems (ADAS). Analog Devices developed the world’s first accelerometer dedicated to automotive airbag deployment.

Modern vehicles integrate multiple MEMS inertial sensors, including gyroscopes, pressure sensors and magnetometers. Despite their compact size, automotive inertial sensors greatly improve the comfort and safety of ADAS and play an essential role in automobiles.

1. Rollover Sensing Vehicle rollover sensing belongs to passive safety functions. It detects vehicle rollover events and triggers airbags timely. During rollover, inertial sensors provide core data such as roll rate, lateral acceleration and vertical acceleration for crash calculation.

Generating reliable sensor signals under diverse conditions, such as extreme high/low temperatures and gravel roads, remains a major challenge. This requirement also applies to inertial sensors for Electronic Stability Control (ESC), an active safety system that prevents skidding by regulating vehicle brakes.

To address these challenges, products must be carefully designed by combining MEMS expertise with full understanding of automotive system specifications. Products need laboratory verification against design specifications, followed by extensive real-road tests under winter conditions or on gravel roads.

2. Inertial Navigation Dashboard navigation systems support urban canyon navigation, reducing navigation difficulty when driving in unfamiliar cities. Integrated with maps, Global Navigation Satellite System (GNSS) signals, routing algorithms and connected vehicle services, these systems deliver real-time traffic alerts.

Automotive engineers integrate inertial sensors into navigation systems because inertial navigation can keep working in urban canyons or areas with weak, invalid or missing GNSS signals. After receiving the last valid GNSS fix before signal loss, inertial sensors continuously estimate position changes. For instance, when vehicles pass through tunnels without GPS coverage, inertial sensors calculate travel direction and distance. Dead reckoning algorithms compute position updates based on inertial measurements to locate the vehicle continuously.

3. Driver Assistance Driver assistance technologies cover far more than cruise control and rear-view cameras. Adaptive Cruise Control (ACC), lane keeping and lane change assistance, advanced emergency braking and active front steering all rely on intelligent fusion of MEMS inertial sensors with cameras, radar and LiDAR.

Compared with conventional cruise control, ACC adjusts vehicle speed dynamically to maintain safe spacing from preceding vehicles instead of holding a fixed speed. ACC mainly uses radar, cameras or lasers to measure object distance. The same inertial sensors used for ESC also enhance ACC performance by predicting vehicle trajectory and linking trajectory information with obstacle detection. Similar inertial devices support hill-start assist; low-gravity sensors measure tilt angle to prevent backward sliding during uphill driving.

Active steering is another assistance function. It reduces steering angle variation per wheel turn at high speeds to improve highway driving precision, while yaw rate sensors feed information for emergency scenarios. In combination with cameras, radar and laser sensors, inertial sensors enable motion prediction for autonomous driving.

4. Fusion of Inertial and Perception Sensors Vision and perception sensors detect moving objects, estimate vehicle motion and calculate distances to surrounding targets. However, their performance is affected by weather, lighting, snow and occluded landmarks.

Inertial sensors measure physical motion rather than extracting data from images, so they are immune to lighting and environmental conditions. They also feature high reliability because no external data communication is required. Relevant research investigates two cooperation modes between kinematic inertial sensors and vision systems: loose coupling and tight coupling.

Under loose coupling, perception systems and inertial sensors calculate vehicle position independently and cross-validate results mutually. Under tight coupling, pixel-level visual measurements are directly fused with IMU readings.

In both modes, MEMS inertial sensors improve frame-to-frame object tracking of perception systems and achieve higher positioning accuracy.