Instruments For Road Network Navigation TRIZ Cases
- Road-Segment Low-Bridge Detection With Directional Truck Alerts
Road-aligned geofences combine map matching, bridge clearance, and truck height to cut false low-bridge alerts and warn drivers in time.
- Road Shape Modeling Using Sensor Resolution at Intersections
Predicts intersection appearance from sensor resolution and map data to build more accurate road models when distant sensor detail is limited.
- Train Crossing Delay Prediction for Road Travel Time Routing
Predictive train movement modeling and vehicle history improve road travel time estimates near rail crossings for better routing.
- Dynamic Pickup Point Re-Ranking for Real-Time Ride Matching
Real-time rider and driver locations plus predicted routes are used to re-rank pickup points and cut ETA and transport cost.
- Predictive Event Alerts From User Communications and Travel Time
By mining prior communications and travel duration, the system surfaces timely event and departure alerts without manual mobile search.
- Vehicle Sensor Map Updating for Timely Change Detection
Crowdsourced vehicle sensor data detects map deviations early, enabling selective high-precision map updates with lower cost and delay.
- Map-Matched Vehicle Location Processing for Reliable Probe Data
Multiple candidate map-matched coordinate sequences improve vehicle probe position reliability while limiting extra processing time.
- Road User Localization Using GNSS Gap Prediction
Historical data and motion models fill GNSS pseudorange gaps under NLOS conditions, improving relative road-user localization stability.
- Protected Parking Routing for Weather Event Vehicle Protection
Predicts severe events, checks covered parking capacity, and routes drivers to reservable spaces that better protect vehicles.
- Indoor Position Correction Using Content Operation History
Content operation history corrects sensor-based indoor position estimates, improving accuracy without beacons or Wi-Fi fingerprinting.
- Autonomous Passenger Route Scoring for Preference-Based Trip Planning
Customer preference scores, historical data, and real-time conditions are combined to choose autonomous vehicle routes that better fit each trip.
- EV Range Prediction Using Route Segmentation and Fleet Patterns
Route-segment matching with historical OEM fleet data improves EV range prediction accuracy while keeping onboard computation light.
- Deceleration Location Prediction Using Dynamic Traffic Condition Indices
Dynamic traffic indices and variation factors improve deceleration location prediction on planned routes, enabling more accurate vehicle energy estimates.
- Route Efficiency Metrics for Real-Time Alternative Route Selection
Dynamic non-temporal route metrics rank alternative pickup-to-drop-off paths to cut user interactions, processing load, and route waste.
- EV Charging Recommendations Using Traffic Prediction and Optimization
Traffic prediction and linear optimization guide EV charging timing and location to cut delays, improve range confidence, and avoid peak demand.
- Route Planning Using Historical Traffic OD Graphs
Historical OD traffic graphs help identify modal routes and improve route selection when real-time traffic alone is unreliable.
- Navigation Interface Safety Cues With Reduced User Input
Safety characteristics and route options are shown by transport mode, cutting interaction time, cognitive burden, and battery use.
- POI Parking Lot Identification Under Sparse Mobility Data
Uses transition-point clustering and nearby geographic areas to identify popular POI parking lots even when probe data is sparse or indoor.
- Separate Mobility Module Control for Shared Drive-Cabin Pairing
A server matches available drive modules with space modules to cut vehicle cost, parking occupancy, and idle resource waste.
- Electronic Map Route Plotting Across Longitude Range Boundaries
Converts out-of-range longitude points before plotting so electronic maps show the true shortest route across longitude boundaries.
- Scenic Route Graph Generation for Balanced POI Views
Equidistant scenic points and bisector-based graph building create 2D routes with balanced POI views and fewer repeated edges.
- Vehicle Marshaling RF Heat Maps for Cellular Disruption Avoidance
Dynamic RF coverage heat maps help marshaling vehicles detect cellular disruption early and adjust commands to avoid delay and stoppage.