Steering Parts TRIZ Cases

A reference steering angle added to MPC improves lane centering in curves, reducing overshoot and smoothing lane changes.

Driver proficiency is used to adjust lane change activation time, balancing safe control with faster response to driver intent.

Fused camera and sensor mapping helps vehicles detect curved-road parking limits and exit parallel spaces without curb or rear-vehicle contact.

By comparing steering commands with delayed actual response, this case detects blocked, jammed, or broken steering faults in real time.

A corrected parking path keeps low curvature longer and shifts the target closer to the wall while reducing collision risk from control errors.

Adjacent-lane object detection shifts the trigger line to prevent false steering interventions while preserving reliable lane departure backup.

Multiple rear sensors detect tow-bar attachments or bike racks and recalculate parking paths when sensor views are blocked.

Cloud-based digital twins predict road deterioration and guide connected vehicles away from high-penalty surfaces to limit further damage.

Calculates left and right lateral clearance to choose an evasion path that avoids obstacles while maintaining vehicle stability.

A blocking line keeps traffic space clear until corrective maneuvers are no longer needed, reducing collision risk in perpendicular parking.

When wheel chocks, bumps, or slopes disrupt parking, the controller detects the event and switches to a new path to finish safely.

Adaptive multi-resolution discretization cuts computation while preserving object accuracy for robust real-time autonomous vehicle control.

Independent sensor-based plausibility checks verify subordinate controller feedback and trigger warnings or emergency stops when values conflict.

Segmented target-vehicle prediction cuts computation while updating positions and speeds fast enough for assisted lane changes.

Obstacle positions are stored with a target parking spot, cutting repeated user input while preserving parking accuracy.

Redundant communication buses and parallel emergency commands let an automated vehicle keep lateral control and stop safely after failures.

Segmented target vehicle prediction cuts computation time and supports frequent lane change updates, even when usable gaps are not yet adjacent.

Measures the delay between control actuation and parking-aid sound output to verify legal timing without vehicle bus access.

A learned manual parking path defines a safety region so low-torque electric power steering can follow an automatic route without collisions.

Bird's-eye camera lines crossing the tractor-trailer pivot region improve trailer angle detection for reversing and video panning.

Acoustic vibration cues tied to steering input and seat position help occupants anticipate yaw behavior without slowing vehicle response.

Stored camera images let drivers distinguish among learned parking trajectories and reliably choose the correct autonomous path.

Recorded maneuver and sensor data define a navigable area, letting a vehicle later drive autonomously to new goals without repeated manual routing.

Motor-driven alignment control and sensor monitoring enable fast camber, caster, and toe correction for changing driving conditions.

Separating parking position registration from automatic movement control prevents control unit overload and keeps automated parking updates smooth.

During low-speed steering, the brake system releases wheels below a speed threshold so they roll freely and avoid tire wear.

Actual wheel angle thresholds improve automatic turn signal cancellation timing across vehicle-specific steering and chassis characteristics.

Feedforward, feedback, and disturbance estimation compensate steering delay and model error to reduce lane-keeping oscillation.

A neural network retunes PID gains in lane keep assist to maintain lane position accuracy as vehicle speed, steering, and road conditions change.

Preplanned lane split detection and speed-path adjustment help autonomous vehicles handle bifurcations smoothly and avoid confusing maneuvers.

Stored teacher-path parking is combined with object highlighting and stop prompts when new obstacles appear near the autonomous travel path.

Deleting selected ambient-area data during teacher route registration helps autonomous parking avoid moving-object errors and improve self-positioning.

Sharp trained turns are replaced with achievable substitute paths so parking assist can track tight curves with less deviation, collision risk, and steering wear.

By dividing the target lane into candidate areas and checking obstacles, this case improves automated lane change timing, safety, and success.

A cam bolt pivots the knuckle upper member for quick camber adjustment while minimizing changes to caster, toe, and alignment time.

When a vehicle leaves a recorded return path, the system checks re-entry feasibility and re-offers automated replay only under suitable conditions.

Multiple vehicle sensors estimate road wheel angle from kingpin torque and roll steer, improving control accuracy during dynamic maneuvers.

Rear-camera target selection lets a tow vehicle reverse autonomously to a trailer and align accurately with the coupler.

An intended-path overlay on intersection camera views helps remote operators grasp turning intent faster and track vehicle course more intuitively.

Predicted lateral acceleration and jerk are checked against vehicle limits to allow collision avoidance steering without violating lane rules.

By detecting lane-keeping steering input before drift occurs, the controller suppresses false lane-deviation alarms on curved roads.

Opposite-phase steering wheel vibration cancels cross-propagation at a target point, improving haptic signal clarity without extra actuators.

Low-pressure cold forming with radiused guide-element transitions reduces cracking, improves alignment, and extends chassis component life.

Priority-based filtering suppresses low-priority steering wheel vibrations so drivers receive clearer haptic alerts without added actuator cost.