Character And Pattern Recognition TRIZ Cases

A camera-guided trailer backing interface sets and holds a driver-selected trailer angle to reduce jackknife and collision risk while reversing.

Camera lane models backed by vibration and acoustic sensing help extend hands-off highway driving beyond roads with physical lane barriers.

Occupant gaze and gesture input dynamically reallocate vehicle display regions, improving multi-user viewing comfort and reducing distraction.

Combining 5G EM reflections, camera data, and machine learning improves wide-area weapon detection and AR visualization.

A visual prompt placed away from the forward view checks driver wakefulness while supporting surrounding monitoring and immediate takeover readiness.

A fixed lateral target line helps lane-keeping control avoid wobble when adjacent lanes are present, improving alignment and driver comfort.

Non-uniform top-view grids match vehicle shape and sensor coverage to cut wasted processing and improve feature detection for driving assistance.

Filters out lane-changing vehicles when checking lane boundaries, improving line correctness determination for automated driving.

Selective mining of ambiguous lane images improves autonomous driving training data while reducing bandwidth and storage cost.

Passenger profiles and 3D gesture recognition let semi-autonomous vehicles interpret commands safely without a steering wheel.

Selective environment models and integrity indices improve autonomous vehicle decision timing while keeping perception data consistent and reliable.

Front camera visibility detection triggers rear window defogging to clear fog or freezing without adding dedicated rear sensing hardware.

By selecting route segments around straight ends and curvature changes, this control approach balances responsive tracking with stable travel without high-precision maps.

Trajectory and speed are shaped to limit lateral acceleration and jerk, reducing motion sickness during autonomous vehicle maneuvers.

Camera-guided reference and offset targets cut repeated measurements, enabling precise vehicle sensor calibration in field setups.

Consecutive sensor data is compared to detect sensor position or orientation drift from vibration, preserving autonomous driving accuracy without extra hardware.

Image-pattern matching locates a trailer hitch coupler for steering assist, then prompts manual hitching when detection is unavailable.

Transport sensors validate gait and gesture patterns to authorize vehicle access and functions remotely while improving authentication security.

Zone-based speed control slows a mobile object before a road-sidewalk contact point to avoid abrupt deceleration and improve transition safety.

A neural network classifies rain, ice, snow, dirt, or cracks and triggers heat, gas, or liquid cleaning to keep vehicle sensor lenses clear.

Analyzes occupant, cargo, and environmental context to predict injury risk and trigger alerts or vehicle adjustments before hazards escalate.

Steering angle, steering speed, and vehicle speed adjust gaze limits to avoid false distracted-driving alerts on curves.

A vehicle camera guides head alignment and eye tracking to detect inebriation without breath analyzers or officer-administered tests.

Overlay files extend the VSS catalog with occupant signals, enabling preference updates and control of face recognition, mood, and air quality features.

Passive sensing identifies target objects so active light pulses are used selectively, cutting LiDAR energy use and crosstalk while preserving 3D-map detail.

Road-scene indices from time-series images flag low-alertness driving and trigger notifications to maintain takeover readiness.

Occupant monitoring and voice input reposition a vehicle display for easier viewing and reach interaction under changing user needs.

Time-stamped camera and sonar views let drivers identify registration positions without map data while suppressing repetitive peripheral screen display.

Multiple imaging sensors detect mapped stationary objects to improve vehicle localization accuracy and derive orientation and elevation.

Stepwise cropped-image scanning along the hitch drawbar improves hitchball location accuracy for trailer angle detection and driver assistance.

Straight-lane sensor data and lane geometry reveal vehicle sensor offset, improving trajectory derivation, map encoding, and model training.

Imaging and radar detect roads for a second course change, letting the vehicle stop unnecessary turn-signal blinking when lane lines are unclear.

When lane lines drop out, display control switches to road edge icons only if edge structures are recognized, reducing intermittent alerts and driver annoyance.

Road branch detection lets the controller switch off turn indicators after a lane change even when boundary lines are missing or unreadable.

Distance sensors and an actuator auto-center and level a camera mount, cutting lane-centering benchmark setup and calibration time.

Imaginary lane-edge unification stabilizes steering assist in narrow lanes, reducing hunting and unnecessary wheel corrections.

A vehicle camera shortens its visibility check window when wipers or headlights operate, enabling faster poor-visibility detection.

Vehicle position and camera data are filtered into layered HD map content, speeding landmark updates and map delivery for navigation.

Randomly labeled out-of-distribution inputs train the ANN to lower confidence on non-number plate signs and avoid false vehicle matches.