Instruments For Road Network Navigation TRIZ Cases

When onboard sensors detect a health emergency, remote driving commands guide the vehicle to a safe location without occupant input.

A multi-cubby delivery assembly uses AV navigation and user authentication to securely deliver and pick up varied item types.

User-profile and situation-aware stop suggestions add suitable facilities along an autonomous vehicle route to improve navigation convenience.

Grouping protolane flowcharts by common graphs reuses tests across road segments, cutting test space while preserving validation coverage.

Probe data is converted into time-space diagrams to quantify road obstruction intensity and output diversion confidence for routing.

Matches EV location, battery status, and preferred energy source to recommend charging facilities that fit cost and environmental priorities.

Selective frequency filtering emphasizes location-relevant external sounds in the cabin while suppressing noise that can mask critical driver alerts.

Balances delivery time, battery wear, and charging cost by iteratively planning when, where, and how long each fleet EV should charge.

Off-screen object indicators and segmented vehicle data help operators avoid overload while making safer real-time navigation decisions.

Automatically identifies conflicting lane segments and builds intersection boundaries to create consistent road maps for autonomous navigation.

Road elevation and vehicle inclination models align detected and mapped landmarks for more accurate localization on curved surfaces.

Temporal distance discontinuity checks flag false lane-marking detections before untimely trajectory correction reduces passenger comfort.

A constrained MPC trajectory plan adds a zero-cost backup stop path so vehicles can keep stable tracking while remaining able to reach a safe state.

Sensor and wireless signal detection verify when a display unit is correctly mounted, enabling fast activation, stable data links, and secure locking.

When a rider leaves belongings behind, the system returns the automated vehicle only if timing allows without delaying another passenger.

Predetermined resolution modes coordinate fast reflex actions with deliberate driving decisions to improve autonomous travel safety and comfort.

Passengers can switch to less crowded stops while onboard dispatch books an autonomous vehicle in advance to cut transfer delays and stop congestion.

Spring-loaded handlebar arms secure a rider's phone while a stem display adds trip data, improving comfort and convenience on 2-5 mile rides.

Frequency-domain processing of inertial and GNSS data estimates wheel speed and size to sustain accurate vehicle position, velocity, and attitude.

Behavior and vehicle state data guide reprogramming delivery timing to improve programming reliability while avoiding battery drain.

A platform locates private in-house hydrogen units, authenticates vehicle access, and guides drivers to nearby refueling points to ease range anxiety.

Onboard sensors detect a vehicle approaching a one-way road in the wrong direction, then warn occupants and slow entry to prevent collisions.

Sensors and route data identify photogenic stops and create ride highlight reels, making autonomous trips more memorable and shareable.

Sensor-based anomaly detection identifies distracted or disabled remote vehicles and triggers coordinated alerts and mitigation to reduce crash risk.

Computing forward and reverse parking paths with an evaluation function improves parking accuracy, completion success, and maneuver time.

Weighted filtering merges current and future occupancy grids into one map, cutting replanning load while handling moving objects.

When traffic or vehicle parts block the camera, GPS and map DB image matching keep the XR navigation screen aligned with the driving course.

An integrated helmet system automates deployment, wear validation, sanitation, and retrieval in shared ride vehicles to cut labor and improve safety.

By merging detected lane markings with route link data, this case improves AR driving guidance accuracy and realism at speed.

Importance scoring ranks nearby agents by trajectory impact, focusing prediction resources on critical actors for timely autonomous driving decisions.

Map-matched regions keep critical driving details while non-relevant image areas are compressed to cut bandwidth for remote vehicle assistance.

When road markings are hidden in congestion, the controller lengthens following distance so the camera can capture signs and correct map position.

A concave mirror and transmissive optical element fold the HUD optical path to keep windshield virtual images clear in a smaller package.

Preassigns a shared ride before pickup is known, using later vehicle location data to match riders, build routes, and improve fleet availability.

Segmented curve alignment with tag-based tolerances helps vehicles detect map feature changes from object coordinates more reliably.

Payment codes shift to the passenger display during driving, reducing driver distraction while keeping in-vehicle payment access usable.

Combining lane, parking, and post-exit route networks, this case selects parking spaces by balancing vehicle travel and user burden.

Adaptive care suggestions adjust EV battery charging and discharging by temperature, route, and charge history to slow battery aging.

Ad timing is synchronized with automated-to-manual driving transitions to improve occupant attention and notification effectiveness.

Sets SLA response times and review cadence from encounter rates and detector precision to mitigate autonomous vehicle map errors promptly.

Remote operators can update map elements and suggest validated paths so autonomous vehicles handle lane closures and other irregular road events safely.

Compares automated driving and walking times from a parked vehicle to help users choose the faster parking lot exit route.

RNN-based position prediction preserves driving sequence data to correct GPS errors on underpasses and branch roads.

Spatial penetration costs steer autonomous vehicles away from no-block zone centers while maintaining enough speed to clear these regions safely.

Routes are scored by bend count, spacing, and curvature so navigation can highlight paths that lower vehicle oscillation and motion sickness.

Ground surface shape estimation helps distinguish drivable road surfaces from obstacles, reducing false positives from low-accuracy sensors.

Spatial maps of wireless signal strength let vehicle systems predict weak coverage areas and adjust operation for more reliable coordination.