Instruments For Road Network Navigation TRIZ Cases

A shared data structure lets separately launched AR and web-based components exchange state, reducing repeated operations and disjointed messaging-app experiences.

Sensor facts trigger predefined rules so a virtual assistant can start timely conversations without waiting for user interaction.

A user's visit frequency and recency identify familiar landmarks for annotated search suggestions and navigation guidance when street signage is poor.

Vehicles crowd-source line-of-sight and signal data to build road-link 5G coverage maps that reflect real road conditions with lower map-matching overhead.

A route-comparing system uses an envelope to isolate cross-system deviations, classify their causes, and guide map or routing-logic corrections.

Traffic-density thresholds and lane-position data help detect road works zones when high-density traffic blocks direct visual observations.

Distance-based accuracy keeps nearby charging stops detailed while reducing CPU time on longer motor-vehicle routes.

Turning raw latitude/longitude into point-of-interest context, this mobile notifier enables intuitive sharing without map-based interpretation.

Position and map uncertainty cause errors near parallel roads; separate criteria and topology improve complex-road map matching.

A modular logistics system calculates route emissions for candidate vehicles and assigns each driving route to the lowest-emission option.

A management system selects potential routes and roadway detection elements to locate emergency vehicles and adapt traffic for passage.

Continuous lane markings provide weak traveling-direction cues; endpoint extraction and scan-aware correction improve vehicle position accuracy.

An intermediary parking/charging manager checks EV battery, charger, and lot constraints before confirming executable fleet plans.

Traffic-event monitoring updates travel and driving plans as vehicles transition from crewless autonomous sections to driver-led roads.

See how a mobility service combines transit, taxis, shared mobility, and walking to recommend routes within user budgets.

Fixed bus routes lack flexibility; this case continuously updates uncommitted segments to balance vehicle costs with passenger service quality.

Route risk scores use safety attributes, user preferences, and behavior feedback to reduce anxiety in multimodal mobility.

Abstract queries run on each vehicle to aggregate fleet results, reducing network transmission and keeping raw telematics data local.

A camera switches between video and single images by location relevance, reducing storage costs while preserving key vehicle features.

Simulating walking, train, and bus routes reveals crowd density and wait times, enabling visual or auditory information to ease event congestion.

Vehicle mass, height, width, and road grade inform comfort scores for routes that reduce propulsion stress and occupant discomfort.