Autonomous Decision Making Process TRIZ Cases

A mobile fire-response vehicle verifies detector alarms on site before extinguishing, cutting false activations without fixed suppression infrastructure.

Bidirectional V2V messaging and sensor checks let platooned vehicles change lanes and merge together at higher speeds while keeping safe gaps.

Agent trajectories are encoded as 2D time and motion channels so CNNs can predict future behavior accurately with lower computational load.

Sensors on a payload transfer shelf signal fleet control for autonomous pickup and drop-off while preserving scarce industrial floor space.

Fused laser, depth, and ultrasonic data with position history reduces robot sensor blind zones and improves obstacle-free path planning.

Real-time signal-state assessment lets UAVs reroute through accessible locations to maintain reliable transmission and navigation.

Millimeter-wave radar lets UAVs detect peers, terrain, and obstacles for autonomous navigation in GPS-denied and degraded visual conditions.

Networked transport and lift units move cargo autonomously between warehouse and aircraft, reducing human error in loading and unloading.

A brushcutter records boundary coordinates while cutting, enabling autonomous lawn robots to process edge sections without extra scanning hardware.

GPS centroid, IMU, and lidar reflections from static infrastructure are combined to correct autonomous vehicle position without pre-arranged landmarks.

Links video stimuli to ML outputs so engineers can inspect pedestrian and cyclist behavior predictions beyond motion vectors.

Historical surveillance data is converted into flight intent and state-action mappings, enabling safer autonomous control across aircraft types.

Sensor, telematics, and usage data enable dynamic insurance premiums for autonomous vehicles based on actual driving performance.

Sensor-guided control adjusts dozer elevation and path at incline-to-flat transitions to keep material layers uniform and movement stable.

Wider scene features are combined with object patches to improve vehicle object classification without adding prediction time or heavy compute.

Selective deletion and fusion of multi-rangefinder data creates virtual sensors that improve map accuracy and help autonomous robots avoid collisions.

Polyhedral geofences compress lidar point clouds into navigable 3D boundaries, enabling real-time vehicle positioning where GPS is intermittent.

Depot-based order aggregation, autonomous transfer, and batching cut congestion delays and improve ETA accuracy for perishable deliveries.

Ranks GPS, sensor, and RTC clock sources by time difference to improve autonomous vehicle sensor timestamp accuracy without costly oscillators.

RFID tag sequence checks let an industrial vehicle detect missing tags and keep navigation and vehicle functions running despite tag faults.

At busy queuing locations, riders choose an available autonomous vehicle and authenticate to confirm assignment, reducing confusion and wait time.

Intersection clearance requests, road rules, and obstacle data help warehouse vehicles avoid deadlocks and move safely through shared crossings.

Onboard sensors detect operational issues and criticality, allowing autonomous vehicles to route themselves for maintenance without manual fleet oversight.

Automated theorem proving verifies inference rules, inputs, and outputs to prevent contradictory autonomous vehicle commands.

Real-time self-tuning guidance adapts tractor control to soil changes, hitch forces, and speed without manual parameter tuning.

A scheduler-driven control pipeline aligns sensor processing and actuator updates to reduce latency and jitter in real-time flight control.

Difference histograms compare GPS, sensor, and RTC clocks to pick a low-cost time source for accurate autonomous vehicle sensor timestamps.

Vehicle-side signaling and NFC verification help autonomous vehicles alert attendants, confirm vendor identity, and secure refueling payment.

Distance sensing and path tracing let an AGV follow an operator, adjust speed through turns, and stop automatically to reduce warehouse collisions.

Pre-scanned and sensor-updated return paths help remote aerial vehicles get home quickly while avoiding obstacles and unnecessary maneuvers.

Constraint files update local inclusion and exclusion zones so autonomous vehicles can reroute around closures and events without full map updates.

Digital twin simulation selects safe platooning locations and reorders vehicles using real-time and predicted traffic data.

Centralized operations-control vehicles fuse multi-vehicle sensor data to cut latency and improve real-time routing decisions.

A rotating range sensor detects sudden distance changes so the robot can pivot and approach down-steps without falling.

Rare earth phosphor road coatings convert light into detectable signals, enabling precise vehicle and pedestrian localization for safer guidance.

Onboard sensor analysis detects maintenance needs and dispatches autonomous vehicles to service, reducing manual fleet oversight and routing errors.

Using UAV and machine data, this case plans forestry equipment assignments and routes to cut fuel use, coordination burden, and forest damage.

A leader-follower controller combines source-intensity sensing and obstacle avoidance to keep multi-vehicle formation stable under noisy communication.

A recessed well deck and buoyancy control enable autonomous payload launch and recovery in high sea states without winches or davits.

Joint sparse dictionary learning replaces linear feature-attribute mapping to improve unseen object recognition and downstream vehicle control.