Anti-Collision Systems TRIZ Cases

Dynamic mirror warnings enlarge when a driver turns toward an occupied blind spot, improving hazard visibility and collision avoidance.

Cross-checking object states and labels across different vehicle sensors reveals deviations, helping identify faulty readings and maintain safe navigation.

Parking-space type detection adjusts rear cross-traffic warning zone size and angle to improve collision detection and cut false alerts.

Dual minimum-distance parking zones let the controller balance collision avoidance, driver comfort, and space-efficient target positioning.

Separate gaze rules for mirror zones and other areas cut false looking-aside warnings while preserving distraction detection.

Passable-area planning and trajectory updates help a vehicle resume travel safely after yielding to an oncoming car on a narrow road.

Cornering-aware cruise control changes inter-vehicle distance or passing time to keep motorcycles safely aligned with a preceding vehicle.

Object coordinates, gaze direction, and head position are fused to estimate driver attention and suppress unnecessary vehicle warnings.

Sensor-detected flaggers trigger teleoperator guidance so the vehicle can adapt driving policy in real time and pass safely through directed traffic.

Sensor alerts, handling response, and autonomy settings are tuned to a driver's familiar vehicle profile to ease transitions between vehicles.

A central map-based interface links mixed-vendor digital signs to deliver location-specific emergency alerts and travel updates in real time.

Risk-based notification modes adapt to motorcycle merge behavior, reducing collision risk without overloading or annoying the driver.

By comparing current and past VLF heart-rate data, this case tracks health and drowsiness changes during riding despite motion disturbances.

Dynamic visual lane-change risk feedback helps drivers judge danger levels in real time and adjust speed or timing for safer maneuvers.

Precomputed emergency stop trajectories let a vehicle decelerate and stop safely when the main trajectory generator fails.

LIDAR terrain profiles are matched to stored rut patterns so self-driving cars can detect hazardous grooves early and adjust their path.

A self-propelled trailer follows a towing vehicle through a virtual tow-link, cutting EV range loss while maintaining safe trailing distance.

A server assigns real-time vehicle priority at parking lot intersections to prevent collisions and reduce passage delays.

Predicting obstructive object movement helps maintain self-location accuracy and smoother path planning when sensor views block map feature matching.

Cached intermediate ML outputs cut compute load while improving object attribute and roadway-intent classification from temporal sensor data.

By predicting vehicle motion and road gradients, this case explains temporary leading-vehicle sensor loss and helps maintain safe following distance.

Selective high-resolution LiDAR scanning and tilt control improve object detection accuracy while limiting ECU load in autonomous vehicles.

Adaptive mirror-display switching combines rear and side camera views with overlays to improve parking depth cues and driving visibility.

Adaptive alert-region width matched to intersection size improves lateral object warnings and cuts missed or unnecessary driver notifications.

By separating driver and environmental start requirements, the control logic prompts only actionable items to support smoother autonomous driving handover.

An implicit latent variable model with graph neural networks improves joint multi-actor trajectory forecasts and avoids sequential sampling errors.

Displays a speed-aware travelable region for forklifts, improving turning trajectory accuracy and helping drivers avoid unsafe maneuvers.

Timed driver alerts at toll gate areas help automated vehicles maintain traffic awareness and reduce collision risk near multiple gates.

Prior parking detections are compared with current sensor data to flag newly found hazards and raise alerts during automatic parking.

V2X messages help vehicles detect motorcycles hidden by larger vehicles at intersections and trigger warnings or interventions to cut collision risk.

AI predicts puddles and icing from multi-source sensor data, enabling smooth speed adjustment without braking, friction, or excess power use.

Sensors detect flashing lights, sirens, and related signals early so drivers can stay focused on traffic and still respond to nearby emergency vehicles.

Multi-level amplitude modulation raises photoelectric signal transfer rate without extra output pads, helping limit size, noise, and image degradation.

By evaluating other road users' behavior, the control unit detects zipper merging and other alternative rules to avoid route errors and collisions.

Camera-based lane marking classification keeps vehicles offset from lane edges for smoother lateral control without complex object detection.

Driver gaze and front-rear hazard detection are combined to report only unrecognized risks, reducing alert overload and distraction.

Side-mounted sensors on the tow vehicle extend detection past wide trailers, improving merge warnings and collision avoidance.

Priority-based role assignment and costed preemption or yielding reduce false braking and acceleration during vehicle trajectory conflicts.

Periodic amplifier gain switching creates high-power pulse envelopes for short- and long-range LiDAR detection with less speckle processing.

A recessed windshield module keeps radar off the grille, avoids glass attenuation, and pairs with a camera for stronger forward object detection.

A wheel speed sensor triggers visual or audible alerts when a trailer drops below a set speed, warning nearby drivers of highway speed differences.

A windshield virtual image adapts its position and width to object status and driver position, reducing missed hazards without distraction.

Angular-width and distance calculations locate forward objects against road boundaries, improving lane-intrusion support control.

Past obstacle feature distributions help flag erroneous image-based detections, improving autonomous vehicle recognition accuracy.

A two-stage vehicle display sequence shows takeover alerts on a secondary screen first, then the main screen, reducing occupant distress.

When obstacle paths overlap, this case plans low-speed yielding or right-of-way maneuvers to cut unnecessary braking and improve passing efficiency.

By inducing roll or pitch before a turn or deceleration, this control approach helps occupants brace naturally and reduces ride discomfort.

Distance-based merge control compares vehicle spacing with regulation body boundaries to prevent interference and avoid unnecessary actions.

When a rear vehicle is closing in, lane departure control stays active despite turn signaling to avoid unsafe lane changes and rear-vehicle conflicts.

Grip-state sensing on the steering wheel switches between parking assist modes automatically, reducing driver distraction and input errors.