Control Devices TRIZ Cases
- Autonomous Vehicle Trajectory Planning for Route-Aware Mode Selection
Candidate trajectories are scored by state quality and transition quality to keep autonomous driving route-aware, safe, and less prone to mode mixing.
- Vehicle Cabin Display for Lane Change Perception Confirmation
Before autonomous lane changes, the cabin display shows lane status and destination-lane confirmation to reduce occupant uncertainty.
- Vehicle Recognition Confidence Alerts for Autonomous Driving
Low-confidence target alerts help vehicle supervisors judge AI recognition reliability without overwhelming them during autonomous driving.
- Driver Assistance Alerts for Failed Automation Level Switching
Shortened hands-on alerts after a failed switch to higher automation help drivers recognize the true assistance level before safety is compromised.
- Rental EV Battery Display Using Allocated Capacity
Allocated battery capacity lets a rental EV display start at 100% and fall to 0% over the user’s usable range, improving vehicle utilization.
- ACC Fallback Vehicle Stopping Under Detector Failure
When ACC sensors fail near a stop, fallback vehicle-stopping control uses inter-vehicle distance conditions to reduce collision risk.
- Vehicle Motion Manager for Source-Agnostic Kinematic Plan Arbitration
By classifying kinematic plans without tying them to app IDs, the motion manager cuts redesign work and speeds vehicle function updates.
- Autonomous Vehicle Mover Model Selection for Ambiguous Actor Motion
Multiple kinematic models are compared by trajectory divergence so autonomous vehicles can forecast ambiguous actor motion more reliably.
- Axle Disconnect Clutch Control for Faster Turn Engagement
Sequential clutch engagement based on lateral acceleration cuts axle reconnect time in turns while preserving stability and fuel economy.
- Autonomous Vehicle Control Parameter Tuning for Changing Road Conditions
Sensor-based MCU tuning updates control weights from expected vs. actual vehicle state to reduce oscillation across road and weather changes.
- Vehicle Alert Timing for Obstacle Recognition Under Rear Approach
Earlier collision alerts are triggered when a following vehicle approaches, helping drivers notice front obstacles sooner and brake earlier.
- Automatic Parking Route Simplification for Orientation Adjustment
Training-route points are reconnected by orientation and distance thresholds to remove back-and-forth parking maneuvers and shorten auto-parking travel.
- Vehicle Control Notification for Machine Learning Transparency
When vehicle control functions use machine learning, operator notification improves transparency and reduces mistaken recognition of AI-driven control.
- 4WD Vehicle Speed Estimation Under Full-Wheel Slip
Torque limiting selected wheels suppresses full-wheel slip so estimated 4WD vehicle speed stays accurate without prolonged intervention.
- ADAS Feature Availability Layers for Sensor Uncertainty Control
Sensor uncertainty thresholds let vehicles disable high-risk ADAS functions while keeping lower-layer features available when data is incomplete.
- Driving Support Timing for Night Pedestrian Detection
Radar and LIDAR bring forward braking and alerts when headlights delay night pedestrian recognition between vehicles.
- Vehicle Display Mode Switching for Autonomous Driving Evaluation
When driving shifts to autonomous mode, the display switches from real-time vehicle state to summary metrics that help occupants judge driving results.
- Autonomous Vehicle Emergency Destination Selection Under Traffic Constraints
Sensor-based candidate stop selection helps autonomous vehicles avoid risky areas and reduce collision and traffic disruption during emergencies.
- Redundant MPC Cross-Channel Analysis for Feasible Vehicle Trajectories
Cross-channel MPC checks predicted trajectories for physically impossible motion plans and selects the safest actuator setpoint.
- Automated Driving Non-Monitoring Period Allocation for Driver Tasks
Dynamic non-monitoring periods let drivers handle short non-driving tasks while automated control adapts to conditions to maintain safety.
- Vehicle Range Display for Follow-Up Driving Benefits
By estimating added cruising range behind a selected lead vehicle, this case makes fuel-saving follow-up driving easier for occupants to understand.
- Vehicle Speed Display Layout for Recognizable Control Speed Ranges
Side-by-side speed and control-range graphics help drivers recognize preset vehicle control speed conditions without relying on memory.
- Vehicle Display Interface for Autonomous Lane Change Confirmation
Before an autonomous lane change, the interface shows destination-lane status and nearby vehicles to reduce occupant uncertainty and improve safety perception.
- Vehicle Control via ID-Based Driving Characteristic Switching
ID-linked control data lets one vehicle reproduce different driving characteristics without physical modification, reducing customization time.
- Vehicle Abnormal Sound Localization Using Body Sensitivity Data
Body sensitivity data links cabin and external monitor sounds to pinpoint unknown vehicle abnormal sound sources without prior position maps.
- Non-Holonomic Motion Planning Graphs With Maneuver Transition Costs
Graph-based planning adds maneuver states and transition costs to handle non-holonomic constraints with fewer nodes and better path quality.
- Lane Touch Root-Cause Analysis for Automated Driving Programs
Sensor-based rules detect lane touch events, trace errors across sensing, planning, and control, and speed automated driving redesign.
- Obstacle Position Prediction Evaluation Using Probabilistic Distribution
Evaluates obstacle future-position accuracy by comparing a predicted position distribution with later sensor detections to flag abnormal predictions.
- Curvature-Velocity Motion Planning for Non-Holonomic Path Smoothness
Using curvature and velocity states, this case shows smoother non-holonomic path planning with less post-processing and better real-time collision avoidance.