Autonomous Decision Making Process TRIZ Cases

Simulate aerial vehicle configurations to select optimal modular components for pre-flight assembly, resolving adaptability versus performance trade-offs.

Aggregates intersection exit encodings with obstacle state evolution to calculate exit probabilities for autonomous vehicle trajectory planning.

Spherical image authentication verifies co-presence between vehicles, preventing location spoofing and Man-in-the-Middle attacks in V2V networks.

An autonomous vehicle system stores preselected parking coordinates to execute automated parking maneuvers at preferred locations.

Onboard processing unit detects conflicts via ADS-B and GPS to initiate automatic contingency maneuvers for aerial vehicles.

A kinematics determination method computes target movement using polynomial path projections and smoothing filters.

Replacing mechanical interfaces with acoustic communication improves ease of operation while maintaining reliability during optional maneuver confirmation.

Segmenting scoring models into independent sub-networks provides richer training signals, improving prediction accuracy and efficiency.

A modular autonomous vehicle architecture uses distinct controllers to determine safe driving corridors and trajectories.

Camera-based visual recognition eliminates transponder armbands in self-propelling luggage, resolving user comfort and reliability trade-offs.

Recording pigeon flight paths enables UAVs to navigate metropolitan areas safely, reducing collision risks and energy consumption.

A vehicle control device identifies passengers via voice recognition to customize user interfaces and access functions.

A rescue system uses a server to coordinate multiple movable bodies equipped with cameras for continuous target monitoring.

Active thermal control reduces operating junction temperature below maximum limits, cutting power draw and cooling component costs.

Autonomous navigation reduces manual collection costs by using brake pads for directional control.

Magnetic couplers join pods to UAVs, enabling aerial transport that reduces ground infrastructure needs.

A recurrent neural network generates corrective terms from occupancy grid map features to produce predicted maps for future time steps.

A speed planning guidance line generates deceleration trajectories based on natural profiles to control autonomous vehicle motion.

Roadside units transmit only extrinsic data to vehicles, resolving bandwidth constraints while improving situational awareness completeness.

An autonomous vehicle detects service needs, selects a center, and drives there using data matrix authentication.

A single camera captures images while an infrared sensor calculates distance to identify non-planar obstacles.

Internal laser welding joins corrugated interior layers to outer walls, preventing heat damage to thin inner structures during fabrication.

A surrounding vehicle display device generates a virtual image from above the host vehicle to show surroundings.

A driving rule system modifies vehicle parameters based on observed deviations in nearby traffic behavior.

An alert control apparatus estimates lane change necessity and notifies drivers of transfer possibility with corresponding reasons.

Portable terminal camera captures driver face images to detect inattention during automated driving and issue timely warnings.

A motorcycle prevention system transmits vehicle data to adjacent cars via V2V links before lane changes.

A decentralized tracking system applies cubature information filters to sensor data for accurate state estimation.

Driver agents collect driving experiences to generate control policies using deep reinforcement learning, eliminating reliance on external labeled data.

Convolutional neural networks classify road surface projections, allowing vehicles to adjust speed and lane changes without driver intervention.

A vehicle control system dynamically configures neural nets during runtime to adapt analysis units for specific driving situations.

A vehicle control system adjusts forward-facing camera array resolution based on detected speed to optimize processing load.

Processor generates selectable autonomous actions to reduce hazardous interruptions from driver overrides in semi-autonomous vehicles.

Neural network predicts traffic participant trajectories using road topology data.

A predictive model estimates passenger comfort levels from operational data to guide vehicle action selection.

A deep neural network adjusts fusion weights for vehicle data sources using reinforcement learning.

A carrier vehicle flat plate moves via a dedicated section to adapt its configuration for different operational tasks.

A UAV navigation system detects spoofed GPS data by analyzing signal strength variance against internal sensor references.

A world model includes hypothetical dark objects in unperceived areas to update vehicle trajectories.

A control center device processes data from autonomous units to determine incident risk levels and manage operational control.

A crosswalk navigation system calculates pedestrian motion vectors to time automated vehicle entry through intersections.

A remote control center manages autonomous transit vehicles through two-way communication with onboard sensory inputs.

A driving environment segmentation system uses dedicated scenario handlers to process sensor data for specific sub-environments.

Autonomous vehicle sensor system selects data subsets based on environment complexity and channel availability to reduce bandwidth consumption.

A segmented pressure sensor detects intentional hand contact on the steering wheel rim to transfer vehicle control from autonomous guidance.

A processor constructs a knowledge matrix from driver actions to adapt lane centering, resolving discomfort caused by rigid autonomous mid-curve paths.

Autonomous ground vehicles transport items to pickup areas using a management system for scheduling and tracking.

An unmanned vehicle control system detects passenger vital signs and facial actions to determine emotional states.