Road Vehicles Traffic Control TRIZ Cases

Displaying every available vehicle burdens map servers and bandwidth; route-based future positions preserve broader nearby choice.

Machine-learning plate matching helps replace staffed booths, reduce entry congestion, and track paid vehicles within the venue.

TMC reports and vehicle sensor observations are aligned through map road links to verify incident extent despite differing location references.

Onboard sensors detect drum rotation, chute position, and engine activity to replace manual status updates for concrete truck dispatch.

This case combines trained neural-network screening with social simulation to select operation schedules while balancing calculation time and evaluation accuracy.

Analyzing traffic-light point clouds from multiple vehicle traversals improves lane assignment at complex intersections without precise vehicle localization.

Remote schedule updates and augmented reality guidance standardize vehicle inspections, reducing search delays and staffing needs in secure delivery areas.

A reconfigurable ultra-thin metalens switches imaging angles through one sensor, reducing camera movement while preserving compact form.

Satellite pings from multiple vehicles are classified by geofence cells to pinpoint site entrance and exit locations for safer navigation.

Predicted vehicle positions identify map regions while remote processing reduces onboard computation, storage, and update demands.

RSUs and cameras detect open roadway gaps, then send C-V2X nudge messages to improve traffic flow at congested intersections.

Context-aware VRU reporting adjusts frequency and filters irrelevant data, reducing network traffic and driver presentation complexity.

This case uses geofence cells and vehicle location transitions to assign accurate site entrance and exit points from GNSS pings.

This case simulates vehicle traffic scenes, validates scene adaptation, and converts large data into compact parameters for transmission.

Fused radar detections, motion flags, and historical counters improve object classification despite sparse urban observations.

An M2M mesh shares sensors, visual range, and resources between autonomous machines when weak networks disrupt obstacle avoidance.

Separate sensor tracks and similarity measures improve moving-object association accuracy while reducing processing latency.

Time-location validity lists shorten certificate checks for vehicle-roadside communication.

Forecast provisioning levels to position service providers and reduce wait times.

A network entity fuses vehicle and external data to predict nearby positions and intentions when local sensors are unreliable.

Plug-in and swing-in brackets enable safer ground-level signal head installation.

This case distributes target vehicle lists to V2X endpoints, which return sighting reports for precise lawful tracking.

The case selects user-preferred pickup alternatives away from predicted crowds and guides passengers toward smoother boarding.

This case layers lidar points, map-based virtual objects, and a display mask to clarify autonomous vehicle surroundings for passengers.

This case compares position, speed, and other analogous fields across V2X message types to detect misbehavior and report inconsistencies.

Peer vehicles return signed location and time data, enabling anonymous V2X verification with limited infrastructure.

A staged recognition process combines approximate GPS location, camera scans, and attribute matching for safer autonomous pickups.

NLP replaces fixed event mappings, enabling a server to generate personalized responses from vehicle and device data across service domains.

A server fuses GNSS, WiFi, Bluetooth, and movement data to maintain reliable PMV positioning when GPS is unreliable.

A central unit compares obstacle detections with relative poses from multiple objects to evaluate vehicle detection performance.

Internal illumination improves cone visibility while radiofrequency links enable networked control.

A server aggregates local dynamic data from multiple vehicles into a broader high-definition map for safer driving planning.

UWB anchors help an intelligent key determine vehicle direction and relative position for covered-parking guidance.