Instruments For Road Network Navigation TRIZ Cases

Pre-set passenger ethics and activity-aware routing help self-driving vehicles avoid travel disruptions and act automatically in critical scenarios.

Clustered road surface profiles and terrain-based offsets correct GNSS drift and improve lane ordering on complex multi-lane roads.

Timed confirmation or travel-status notifications help occupants verify the intended route during hands-off automated driving and avoid route deviation.

Route calculation uses preprocessed road lighting data and user brightness limits to improve comfort and guidance reliability.

Adaptive waiting based on vehicle scene and network prediction cuts offline synthesis frequency and preserves voice response quality.

Recorded human driving data and passenger presence guide lane planning that adapts to vehicle capability for safer, more comfortable autonomous driving.

Vehicle location and orientation traces from multiple cars let a central system reconstruct parking lot shapes and aisles more accurately.

Monitors power demand, airflow, and door-open duration to alert drivers and help protect cargo conditions while reducing energy waste.

Risk zones built from multiple virtual vehicle positions make hazards easier to perceive and help drivers react sooner.

Position-based lane width lookup tables give autonomous vehicles flexible spatial constraints for smoother lane changes around obstacles.

A driverless taxi tracks the rider's mobile position to shift pickup in real time, cutting wait time while preserving pickup reliability.

Unused onboard compute from autonomous vehicles is predicted and pooled to distribute requests with lower latency and better resource use.

An independent speed profile check compares route-based target speeds to catch optimization faults and keep vehicle energy use efficient.

Calculates driving and air-conditioning power together, then shows reachable stops and nearby charging spots before battery range falls short.

Sensor feedback corrects recorded parking paths so repeated automatic maneuvers reach the intended space position more accurately.

Lattice road data and crossable dipole graphs simplify road-lane mapping for more accurate autonomous driving plans.

Connected vehicle and IoT road data are combined to detect hazards and trigger coordinated illumination that improves visibility for drivers.

Combining map, V2X, and sensor sources lets one localization service support multiple vehicle apps with lower processing, memory, and bandwidth use.

Microphones replace costly rain sensors by classifying windshield rain sounds and weather data to drive wiper speed automatically.

Trip schedules are revised by locking fixed stops by vehicle attributes, allowing new destinations without breaking operational rules.

Adaptive sensor selection distinguishes sleeping from abnormal driver states while reducing unnecessary monitoring in sleep-permitted automated driving.

Calculates each EV's travelable distance and guides the group through reachable charging stations to avoid battery depletion and dispersion.

Camera images are transformed to a top-down view and matched with aerial maps to achieve lane-level vehicle positioning beyond GNSS accuracy.

Stored manual driving experience helps autonomous control handle more road situations and reduce unexpected cancellation events.

Fusing camera, sensor, and GPS outputs with sparse maps cuts data load while preserving autonomous navigation accuracy and safety.

Cloud routing allocates restricted lanes and stops to non-priority vehicles while avoiding conflicts with priority vehicle routes.

A map-based reachable range display turns remaining mileage into a visual travel area, reducing manual estimation during route planning.

Adaptive LiDAR road-line range selection captures enough broken or curved line data to improve vehicle position estimation accuracy.

Human-guided lead vehicles help autonomous transport services handle uncertain urban routes with safer passage and less braking.

Validated technician commands let roadside assistance safely change an autonomous vehicle's state when it cannot continue without human help.

DNN-based LiDAR point classification and curve fitting improve landmark detection and localization precision on curved roads.

A vehicle-linked point platform combines driving and smart-device activity data to reward eco-driving, health, and social contribution actions.

Sparse road-segment maps preserve autonomous navigation accuracy while cutting storage, processing, and data transfer overhead.

When charge runs low, route-side battery depositories let a delivery robot swap packs instead of returning home, cutting travel, time, and power use.

Real-time and historical road-segment data predict autonomous driving levels, helping drivers compare routes by automation coverage.

Fusing sensor data with mapped lane geometry improves target vehicle lane assignment in complex road scenarios with limited sensor view.

When a driver remains unresponsive, the vehicle switches to autonomous travel, alerts nearby traffic, and heads to a suitable medical facility.

Accelerometer and gyroscope patterns classify vehicle entry side to distinguish drivers from passengers without in-vehicle hardware.

Cloud ML models combine high-fidelity simulations and telematics to configure heavy-duty trucks for route-specific performance and emissions compliance.

Historical route-segment data and real-time battery sensing predict energy demand and flag maintenance before remote machines run low.

Ultra-wideband ranging and angle detection locate a future passenger in crowds, helping the vehicle choose a precise pick-up position.

Advance display of planned vehicle actions and behavior options reduces driver anxiety and supports smoother autonomous-to-manual takeover.

By fusing onboard sensor data, the vehicle detects icy road conditions early and adapts braking, traction response, and routing.

Adjusting HUD white-light color temperature against headlamp output preserves virtual image visibility and reduces driver eye fatigue.

Road-surface sensing and virtual image plane correction keep HUD AR graphics aligned on sloped roads and prevent surface penetration.

Recorded human driving data and self-aware vehicle capability parameters enable adaptive lane planning that better matches real road behavior.

Digital-map localization and cross-correlation keep a vehicle in lane through curves when markings are missing or unreliable.

A vehicle system steers laterally around detected road irregularities using sensor data and external databases to maintain a safe trajectory.

Vehicle navigation systems use customizable skins and voice autocompletion to resolve screen size constraints while maintaining operational reliability.

A computing device determines personalized estimated time of arrival using anonymized user driving data and real-time mapping parameters.

A navigation system calculates vehicle travel routes traversing destination parking lots using identified entry and exit points.

Automated image recognition extracts street names and associates them with GPS coordinates to resolve manual data entry bottlenecks.

Spatio-temporal clustering of vehicle probe data identifies significant locations for personalized navigation and service delivery.

A destination matching algorithm calculates selection probabilities from historical records to suggest locations.

Navigation system uses rear camera images to calculate vehicle lane position through distortion adjustment and pixel correlation.

A tire pressure monitoring system switches between direct and indirect measurement modes based on environmental conditions.

Pre-computed spatial boundaries for road links enable fast map matching of probe data, eliminating expensive real-time spatial searches.

A vehicle dispatch system uses image recognition to identify visually impaired users and generates voice guidance directing them toward the autonomous driving vehicle.

Classifying map segments by road curvature reduces download time, ensuring timely position determination for autonomous vehicles.

Geographical feature scoring engine assigns categorical scores to road segments based on visibility metrics for navigation routing.

Vehicle system predicts key-on time to request optimization data from a remote server ahead of use.

A vehicle positioning system receives and analyzes surrounding vehicle information to determine positioning performance.

Dynamic field of view adjustment resolves visibility loss by rotating the simulated perspective toward points of interest, preventing missed landmarks.

An information processing device generates movement plans and specifies experience providers capable of delivering services at the user's destination.

A traffic optimization system generates density maps from network data to rank routes by vehicular throughput.

Processor extracts movement event information from user messages to proactively recommend vehicle functions.

A mapping application predicts future destinations and displays dynamic route notifications to streamline navigation setup.

Local pattern caching maintains navigation accuracy when network connectivity is unavailable.

A mobile device localizes users indoors using fingerprint measurements and wireless signal signatures to determine customized navigation routes.

A wireless position detection apparatus generates positioning loci using coverage maps and auxiliary points to specify moving object coordinates.

A routing system merges vehicle telemetry with driver profiles to generate personalized navigation paths.

A mapping system builds closure graphs around source objects to identify anchor nodes for accurate target object location.

A route search system processes drag events on a map screen to dynamically update passing roads and destinations.

A function management server acquires driving data to specify and distribute recommend functions to an in-vehicle system.

Navigation apparatus receives user-defined control parameters and weights to generate optimum routes for autonomous vehicles.

Floor patterns with periodic optical density allow a single sensor to correct dead-reckoning errors via Fourier analysis without complex path changes.

A distributed neural network architecture leverages proximate vehicle compute resources to process sensor data locally.

A modular vehicle architecture with interchangeable cabin units and standardized interfaces enables on-demand service provision during travel.

Focusing factors filter unnecessary nodes during decoding, reducing computational load and improving accuracy for navigation systems.

Onboard detection unit identifies pathogens on high-touch surfaces to enable precise UV or chemical disinfection between rides.

Backend servers reconstruct vehicle routes to transmit only relevant georeferenced predictive information, reducing communication bandwidth requirements.

Server compares secondary sensor states against predetermined patterns to generate revised route information for electronic devices.

A vehicle display device categorizes road states and adjusts visual output based on detected curve curvature.

Information processing device generates a recommended route with specific line lengths and angles to direct the driver's line of sight.

A navigation system offers re-route options when a device leaves a predetermined path.

Geographic database incorporates lane direction patterns to predict traffic conditions, resolving network unavailability constraints.

Dehydrating routes via breadcrumbs and hints reduces transmission volume while preserving routing accuracy for client devices.

A telematics program automatically learns commuter routes through pattern recognition and voice activation.

A terrestrial sensing system detects sidewalk surfaces using accelerometer data to adjust personal mobility vehicle operations.

A navigation device uses pivotally coupled secondary display screens to expand the visual field beyond a primary screen.

Incorporates inertial navigation system uncertainty distributions into image geo-registration to enable full six degree of freedom position and attitude updates.

A travel way recommendation system generates vectors from historical data correlations to capture mode heterogeneity.

A vehicle position estimation method acquires time-series vertical motion data and compares it with reference parameter maps.

Processor synchronizes air conditioner wind output with virtual open roof visuals, resolving visual-only immersion limits in moving bodies.

A navigation device calculates estimated arrival time and instructs a connected portable telephone to create and transmit mail containing this information.

A route planning system selects external power sources to optimize plug-in hybrid electric vehicle charging.