Instruments For Road Network Navigation TRIZ Cases

Map-based communication sections let the vehicle switch between system-driven and driver-driven control when connectivity drops.

Classified trip, device, physical, and personality contexts let ML generate personalized driving outputs with more accurate risk scoring.

Checks battery charge and alternator output before OTA updates so vehicles update only when power is sufficient to finish safely.

Speed-based GNSS jump thresholds matched to vehicle characteristics help switch between satellite and autonomous navigation positions more stably.

Real-time vehicle data is compiled into current state maps so forward regions can be predicted quickly for safer automated driving.

Color cues on road signs and traffic lines guide a vehicle's route, reducing screen distraction and missed turns in complex roads.

Gyro-based azimuth control uses marker-derived lateral shift only as a correction term, reducing steering error from imperfect magnetic marker placement.

Combining default routes from multiple users cuts waiting time and improves autonomous ride sharing with time, location, and fare factors.

Motion sensor data from vehicle components reveals roadway height changes, enabling lane boundary detection when markings are soiled or covered.

Predicted object states are checked against later sensor measurements to retrain multisensor vehicle perception without annotated data.

Charging station search is merged with co-located business display, cutting separate lookups, battery drain, and unnecessary mileage.

Detects route branches missing from the location-estimating map by marking end road zones, helping vehicles stay on the intended path.

Mobile charging stations and detachable battery-on-wheels units extend EV range by enabling in-motion charging and optimized charge routing.

Recorded trailer path, hitch angle, and pose estimation guide autonomous parking into standard spaces despite large turning-radius limits.

Onboard passenger and baggage scanning shifts screening into transit, reducing checkpoint stress and congestion while maintaining secure-area verification.

When autonomous driving hits construction, weather, or failures, remote operator inputs guide the vehicle through difficult route segments.

Candidate pickup and dropoff points are re-evaluated in real time to cut travel time and distance while limiting unnecessary route changes.

Advance travel plan signaling gives nearby vehicles time to recognize lane-change intent and respond more safely to autonomous maneuvers.

Routes and parking spots are selected by vehicle size and turning radius to prevent large vehicles from blocking auto-valet parking flow.

Color and number connector codes unify charger type and power data, making compatible EV station search and charge-time estimation easier.

Predicted driver availability and road release data are combined to route vehicles toward longer automated driving segments and fewer manual takeovers.

Ultrasonic signals from existing vehicle speakers and sensors detect breathing and cardiac motion without added hardware, even in noisy cabins.

Spatial sensing lets drivers operate windshield HUD images with small eye movement while keeping the display unit compact for vehicle installation.

Monitors power, sensor, navigation, memory, and processor faults to restart autonomous driving with higher reliability and stability.

Vehicle-mounted LiDAR, cameras, and ultrasonic sensors predict parking space distribution to cut search time without parking-lot infrastructure.

Shared trajectory quality from multiple vehicles helps route control stay accurate when lane scans fail or map data is outdated.

Concavity-based logical boundary segments reveal likely pedestrian goal points, improving trajectory prediction and collision avoidance in autonomous driving.

Turn-signal, position, and surroundings data help verify newly established branching routes before updating high-precision maps.

Confidence intervals trigger model relearning only when motion estimates drift, improving work vehicle operation in unknown environments.

Confidence scoring filters unreliable LiDAR outline segments before map matching, improving localization accuracy in autonomous driving.

By comparing a computed safety zone with the safe travel corridor, the controller can trigger braking, speed reduction, or steering before unsafe departure.

Local grid segmentation and turn-point removal cut path-planning latency and memory use while preserving obstacle avoidance in large no-fly areas.

Real-time sensor and contextual data trigger proactive driver alerts when risky behavior exceeds thresholds, improving safety and fuel efficiency.

Nearby vehicles share travel direction through Car2X, enabling faster, more reliable wrong-way detection and earlier road-user warnings.

Continuously recorded and merged forward segments let drivers start assisted reversing late without losing usable path data.

Surrounding-data analysis identifies a candidate handover position and alerts the driver with distance, timing, and map cues for safer manual takeover.

Aggregating cellular and occupant-device links helps vehicles overcome coverage gaps, congestion, and bandwidth limits for real-time data transfer.

A mobile screening vehicle combines passenger scanning, approval verification, and transport to cut checkpoint waits and reduce stress for disabled travelers.

Neighbor vehicle trajectories train a recursive self-organizing map to infer virtual lanes when road markings are unclear or misleading.

Scenario-specific control modules exchange operational data with an external system to guide autonomous vehicles through complex traffic.

Conditional steering enable criteria cut unwanted lane-keeping interventions while preserving support for unintentional lane departure.

Partitioned roadgraph levels and warp zones let autonomous vehicles switch map layers accurately when passing under overpasses.

Charging current waveform features are used to model vehicle-specific charge behavior and recommend stations that improve efficiency and reduce battery stress.

Cross-checking map, vehicle behavior, and external sensor data improves road recognition reliability and helps correct sensing errors.

Manual driving logs and route segments are replayed in simulation to compare autonomous vehicle progress and tune caution without overyielding.

Processing circuitry allocates EV battery charge to connected accessories using SOC, energy needs, and charging waypoints to reduce range anxiety.

Precomputed grade- and vehicle-based route constraints guide short-horizon AV routing to prevent brake wear, collisions, and fuel waste.

Compares continuously travelable distances across lanes to guide lane changes when road geometry makes lane markers hard to recognize.

A global optimizer updates AV compute node dependencies and resource assignments after hardware or software changes to sustain parallel performance.

When an EV crosses a power grid border, server-led area code and fee updates reshape V2G charging times to cut cost and improve energy use.

Inflatable seat bladders convey route guidance via tactile pressure, reducing driver distraction from verbal or visual navigation instructions.

A mobile map dialog toggles between manipulation and control modes using a single interface element.

Computing devices determine safety scores for candidate pickup locations using surveillance and crime data.

A vehicular information provision system specifies vehicle position using satellite positioning and map data to retrieve event-correlated output data from a central server.

An expanding anchor mechanism secures magnetic road markers, eliminating labor-intensive drying time for liquid protective materials.

A route determination method groups geolocation data to identify representative trajectories between geographic zones.

Forward probability algorithm calculates joint emission and transition likelihoods to measure map matched trajectory accuracy despite GPS interference.

Computes route reliability from link-level variance to resolve the trade-off between decision quality and system complexity.

A road boundary detection system uses a scoring Hough transform to prioritize straight lines based on contact points.

A mobile terminal transmits position data to a second device for real-time route tracking.

Processor fuses GNSS and path sensor data to adjust steering direction, resolving measurement gaps in irregular fields.

Navigation system retrieves vehicle black box video data mapped to precise location coordinates for display.

A coordinated vehicle response system modifies multiple subsystems to enhance driver alertness.

A vehicle routing system recommends traffic routes based on estimated passenger demand using GPS and historical data.

A navigation system generates adaptive video segments based on user input and GPS data to display route guidance across multiple devices.

A vehicle controller automatically adjusts charging parameters based on the next journey requirements.

A travel control device merges camera images with vehicle signals to determine precise movement paths.

Mobile devices detect matrix codes to retrieve business entity data and GPS coordinates for location queries.

A route planning unit selects a viaport from multiple charging ports based on priority information to set a moving route.

A travel control system collates route information with a dedicated map to ensure continuous automated driving.

A mobile navigation system generates disembarkation alerts by detecting proximity to a destination via GPS tracking.

EVSE transmits RF beacons to deliver location-based services to wireless devices.

A travel coordination system generates zone scores to guide service providers toward high-demand areas.

Automated evaluation system analyzes user position data to determine point of interest attributes.

A vehicle navigation controller predicts route deviation using GPS and speed data to display alternative paths.

A route searching system segments probe car data into segments to generate derived routes reflecting driver know-how.

A scene-aware navigation system generates driving instructions based on real-time object detection and driver perspective.

A navigation system accepts street names via base or full name input in a single field.

Preprocessing text display attributes for digital map data sets to determine which street names appear at specific resolutions.

Synchronizing virtual highlights with real objects resolves spatial limitations in head-up displays, improving intuitive information linkage.

A trip planning system generates customized itineraries using geo-tagged photographs and travelogues.

Route guidance apparatus calculates lane change timing based on required distance and remaining course distance.

Safety visualization system overlays alerts on navigation maps and instrument clusters, reducing cognitive load when drivers focus on route information.

A navigation apparatus displays selectable routes using or avoiding car pool lanes based on user input.

A mass transit platform moves personal vehicles while transmitting electrical charge to their energy storage devices via onboard transmitters.

A navigation device pre-loads terminal-use speech recognition data before entering communication impossible areas to enable local processing.

An information processing apparatus extracts relevant facility data based on user schedules and current positions.

A GPS-based system tracks watercraft position to measure passage time without physical course attachments.

A vehicle localization system switches between 3D map and sensor-based positioning modes to maintain accurate location tracking.

An IoT management platform processes sensor data to determine vehicle limit information for emission control.

A navigation system recommends charging stations by evaluating route proximity and total travel time for electric vehicles.

Cloud-based route planning marks signal blind areas via failure logs, ensuring stable positioning.

An automated detection method extracts invariant image components to identify road signs, reducing manual data collection time while maintaining high accuracy.

Navigation systems adjust voice guidance intervals based on user suppress and request commands.

Automated image analysis estimates available trailer volume to resolve shipping delays caused by inaccurate manual space measurement.

A navigation system extracts characteristic points from street view images to prompt drivers at turns.

A processing device segments a vehicle's future trajectory into distinct parts based on obstacle proximity to display clear path visualization.

A self-position estimation unit uses a reflecting body map to determine vehicle location via radar detection.

Client application manipulates coarser raster imagery to match desired zoom levels, reducing data transfer time and bandwidth consumption.

A vehicle route determination apparatus selects reference points from geographical position data to identify probable road paths.