Control Devices TRIZ Cases

Sector-based sensor confidence lets autonomous driving actions degrade gracefully during sensor faults, avoiding abrupt handover and preserving comfort.

A multi-orientation plug lock lets a blood pump battery connect quickly in any position while preventing contact exposure and misalignment.

Wheel movement analysis adds motion-intent cues beyond location and speed, enabling earlier collision alerts and evasive actions.

Color and shape matching for nearby vehicle images reduces display mismatch and occupant discomfort during lane change assist.

Detects when a vehicle is in an enclosed space and alerts occupants or stops the power source to limit harmful gas exposure.

Distinguishes notification faults from automatic driving function faults and prompts manual takeover when the user can drive.

Connects key points from a learned parking path to remove unnecessary turns and shorten automatic vehicle travel time.

A windshield touch interface lets a person outside a parked vehicle command short movements for parallel parking in narrow spaces.

Predicted return-lane timing and interrupt images keep occupants informed when a second lane change cannot start immediately.

Limits abrupt estimated-position shifts, detects localization errors from revision gaps, and triggers emergency control to avoid unsafe motion.

Sensor fusion and AI detect abnormal road conditions ahead and plan autonomous maneuvers to avoid hazards and improve vehicle safety.

An ABS control module engages anti-lock braking automatically from driving conditions, improving off-road braking reliability without user input.

Input noise is added to raw driving simulations so path planning can handle irrational agent behavior and uncertain kinematics more robustly.

Real-time speed and acceleration data train a model to adapt controller gain, improving speed tracking while limiting oscillations.

Suppresses side collision avoidance in front-side overlap zones to cut false alarms while preserving accurate front collision control.

Incoming-call detection is tied to lane-change progress so automated driving can suppress or continue the maneuver with appropriate occupant notification.

A dynamic vehicle indicator maps head, hand, and foot responsibility to automation mode changes and escalation levels, reducing driver confusion.

An auxiliary compute path restores state and sensor links after processor faults, cutting full-redundancy hardware in autonomous vehicles.

When a shared restart and speed-limit switch raises the set speed in traffic, driver feedback helps restore the pre-congestion limit.

Distributed ASIL controllers exchange diagnostic messages to verify safety functions during software updates and hardware changes.

Adjusted brake or steering inputs maximize the timesteps that vehicle safety constraints remain feasible during rapid target motion changes.

Vehicle sensor data is filtered, normalized, and compressed to fit an adaptive tire model that improves control accuracy without extra sensors.

Timed unload-return control and user alerts keep a temporarily moved vehicle from blocking the road after parallel parking exit.

Virtual demarcation lines and map data guide branch-lane trajectory generation when road markings are missing, enabling smoother lane changes.

Vehicle position, route, and travel history are used to suppress or reduce temporary sensor fault alerts when the car is unlikely to enter the target road.

Driving scenarios are classified to set perception resource parameters, improving accuracy and resource use without fixed all-condition settings.