Collaborative Vehicle Sensing With Mutual Filtering for Detection Reliability

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Solution Overview

Problem

Current autonomous driving sensing algorithms focus on single-vehicle sensor recognition, neglecting the information interaction advantages of the Internet of Vehicles, which reduces accuracy and reliability in complex environments.

Innovation Solution

Implement a method that integrates multi-vehicle collaborative sensing through structured pruning of fusion sensing models, utilizing the Internet of Vehicles to enable vehicles to share and coordinate sensing data, and perform filtering to enhance accuracy and reliability.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Device complexity

If single-vehicle sensor recognition is used, then device complexity is reduced, but measurement precision and reliability deteriorate

Engineering Contradiction:

Improvesensing system complexityVSAvoidvehicle detection accuracy

Core Design Contradiction:

Device complexityVSMeasurement precision

Solution Approach 1:

The patent merges sensing data from multiple vehicles through the Internet of Vehicles platform, combining environmental information from different sources to create a comprehensive sensing result that improves detection accuracy while distributing system complexity across multiple vehicles

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent introduces a data platform as an intermediary that collects, matches, and processes sensing data from multiple vehicles, enabling accurate multi-vehicle collaboration without requiring direct complex communication between all vehicle pairs

Inventive Principle:

Principle #24Intermediary (Mediator)

2Device complexity

If single-vehicle sensor recognition is used, then device complexity is reduced, but reliability deteriorates

Engineering Contradiction:

Improvesensing system complexityVSAvoidvehicle detection reliability

Core Design Contradiction:

Device complexityVSReliability

Solution Approach 1:

The patent combines sensing results from multiple vehicles to improve reliability, using the collective data from different perspectives and sensors to verify and enhance the accuracy of vehicle detection in complex environments

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent implements a feedback mechanism where sensing results are corrected by comparing and matching data from multiple vehicles, continuously improving detection reliability through iterative validation and error correction

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20260035000A1Autonomous Driving Sensing Method and System, Controller and Computer-Readable Storage Medium

Publication Date: 2026.02.05 ZTE CORP

AI summary

An autonomous driving sensing method and system, and a controller and a computer-readable storage medium. The method includes: acquiring external environmental information, and generating at least one first environment sensing result according to the environmental information (S110), wherein the environmental information is a road condition where a first vehicle is located; matching the first environment sensing result to obtain a mutual sensing result (S120), wherein the mutual sensing result is obtained by mutual sensing of the first vehicle and a target vehicle; filtering the mutual sensing result to obtain a comprehensive sensing result (S130); and correcting the first environment sensing result according to the comprehensive sensing result (S140).