Collective Vehicle Pattern Clustering for Lane Identification

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Solution Overview

Problem

Conventional lane identification systems for vehicles rely on single-vehicle data, which is often inadequate or unavailable, leading to uncertain and inaccurate lane estimation, posing risks for safe navigation and accident prevention.

Innovation Solution

A method and system that utilize sensor data from a plurality of vehicles to identify lane-level patterns, cluster vehicles with similar patterns, and generate a lane identification distribution for improved estimation based on collective vehicle data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If single-vehicle sensor data is used for lane identification, then the system complexity is reduced, but the lane identification accuracy and reliability deteriorate due to insufficient data

Engineering Contradiction:

Improvesystem complexityVSAvoidlane identification accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The patent combines sensor data from multiple vehicles into a unified dataset for lane identification. By merging data from connected vehicles traveling on the same road segment, the system overcomes the limitations of single-vehicle data insufficiency while maintaining manageable system complexity through centralized processing.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent introduces a server as an intermediary that collects, processes, and analyzes sensor data from multiple vehicles. This intermediary component enables the system to leverage collective vehicle data without requiring direct peer-to-peer communication between vehicles, thus improving accuracy while controlling complexity.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Ease of operation

If conventional single-vehicle data is used, then the data collection process is simplified, but the reliability of lane identification deteriorates due to data insufficiency

Engineering Contradiction:

Improvedata collection simplicityVSAvoidlane identification reliability

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The patent makes the sensor data collection process universal by having multiple vehicles independently collect data using their own sensors. Each vehicle's sensor system serves multiple purposes: its own navigation and contributing to the collective dataset, thereby improving reliability without complicating individual vehicle operations.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent implements a feedback mechanism where sensor data from vehicles is transmitted to a server, processed to identify lanes, and then used to improve future lane identification accuracy. This continuous feedback loop enhances reliability by leveraging accumulated data from multiple vehicles over time.

Inventive Principle:

Principle #23Feedback

3Loss of time

If single-vehicle sensor data is used for lane identification, then the processing time is reduced, but the measurement precision and uncertainty of lane estimation worsen

Engineering Contradiction:

Improveprocessing timeVSAvoidlane estimation precision

Core Design Contradiction:

Loss of timeVSMeasurement precision

Solution Approach 1:

The patent performs preliminary data collection by gathering sensor data from multiple vehicles before conducting lane identification analysis. By pre-collecting and storing data from connected vehicles, the system reduces the computational burden during critical identification moments while improving precision through aggregated data.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent segments the lane identification process into distinct phases: data collection from multiple vehicles, data transmission to server, server-side processing and pattern identification, and result distribution to vehicles. This segmentation allows parallel processing and optimizes the balance between processing time and measurement precision.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20260030977A1Systems and methods for lane identification using collective patterns of connected vehicles

Publication Date: 2026.01.29 TOYOTA MOTOR ENG & MFG NORTH AMERICA INC

AI summary

Systems and methods are provided for lane identification for a first vehicle on a road segment. The systems and methods may identify a plurality of lane-level patterns for a plurality of other vehicles that traveled on the road segment. The systems and methods may assign each vehicle of the plurality of other vehicles to one of the lane-level patterns to sort the vehicles of the plurality of other vehicles into one or more clusters of vehicles. The systems and methods may determine a lane identification for each cluster of vehicles. The systems and methods may generate a lane identification distribution for the first vehicle based on sensor data of the first vehicle and the lane identification for each cluster of vehicles. The systems and methods may estimate a lane identification for the first vehicle based on the lane identification distribution.