Road Safety Hotspot Identification Through Vulnerability State Aggregation

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Solution Overview

Problem

Existing vehicle-to-everything (V2X) systems for road safety focus on real-time collision alerts, are computationally expensive, exclude environmental and geographical data, and are vehicle-centric, leading to inefficiencies in classifying and communicating Vulnerable Road User states.

Innovation Solution

A Road User Vulnerability State Classification system using devices and servers to collect and process biometric, environmental, and positional data to dynamically classify and communicate Vulnerability States, enabling proactive risk assessment and hotspot identification.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If V2X systems use intensive data processing capabilities (machine learning algorithms, artificial intelligence, HD 3D maps) to classify nearby objects with increasing accuracy, then measurement precision is improved, but device complexity and use of energy increase

Engineering Contradiction:

Improveobject classification accuracyVSAvoiddata processing complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the data processing function by separating object detection (performed by the vehicle system using sensors) from object classification (performed by a remote server using machine learning algorithms). This division allows the vehicle to maintain simple sensing capabilities while achieving high classification accuracy through remote processing, thus reducing device complexity while improving measurement precision.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces a remote server as an intermediary between the vehicle system and the classification task. The server receives sensor data from multiple vehicles, performs intensive machine learning processing, and returns classification results. This intermediary approach enables high-precision classification without requiring complex processing capabilities in each vehicle system.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Measurement precision

Engineering Contradiction:

Improveobject classification accuracyVSAvoidenergy consumption for data processing

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The patent segments the computationally intensive classification task from the vehicle system and relocates it to a remote server. This segmentation eliminates the need for energy-consuming high-performance processors in each vehicle, while still achieving accurate object classification through the server's processing capabilities.

Inventive Principle:

Principle #1Segmentation

3Reliability

If V2X systems focus on real-time collision alerts to prevent collisions, then reliability is improved, but loss of time occurs due to latency in data communications

Engineering Contradiction:

Improvecollision prevention capabilityVSAvoiddata communication latency

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent implements preliminary classification of objects and identification of vulnerable road users before collision risk arises. By continuously classifying objects and maintaining updated information about vulnerable road users in advance, the system reduces the need for real-time communication during critical moments, thereby reducing latency while maintaining reliable collision prevention capability.

Inventive Principle:

Principle #10Preliminary action

4Measurement precision

If V2X systems use sensor-based detection (long-range radar, short-range radar, camera imaging, LiDAR, sonar, GPS) to detect and identify potential collisions, then measurement precision is improved, but device complexity and use of energy increase

Engineering Contradiction:

Improvedetection and identification accuracyVSAvoidsensing system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent merges data from multiple sensor types (radar, camera, LiDAR, sonar, GPS) into a unified detection and classification system. By integrating these diverse sensing capabilities and processing them through a centralized system with machine learning algorithms, the patent achieves high detection accuracy while managing complexity through unified data processing rather than separate processing chains for each sensor type.

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS12462673B2Road safety hotspot location identification and reporting system and method

Publication Date: 2025.11.04 MURPHY EMMETT

AI summary

An approach is provided for identifying and reporting road safety hotspot locations. The approach, for example, involves receiving a Vulnerability State Message from at least one Road User Device associated with a Road User. The Vulnerability State Message includes positional data and vulnerability state factor data, which may indicate an elevated road safety risk. This data is collated with other Vulnerability State data received from other Road User Devices associated with other Road Users concurrently located in the same geographic area. The approach also involves calculating a Vulnerability State summary value for each Road User, and an aggregate Vulnerability State summary value for the geographic area. The approach further involves reporting the geographic area as a Vulnerability Hotspot Location when the aggregate Vulnerability State summary value is determined to be above a threshold amount.