Edge Vehicle Behavior Scoring Using Road User and Infrastructure Data
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Solution Overview
Problem
Conventional methods for monitoring and quantifying vehicle behavior are insufficient as they do not consider interactions with other vehicles and road infrastructure, leading to an incomplete and non-robust view of driving behavior, and do not account for adverse behavior towards other road users.
Innovation Solution
An edge computing device analyzes vehicle behavior by receiving data from vehicles, remote vehicles, road users, and infrastructure devices to calculate a vehicle behavior score, comparing it to a threshold, and generating control signals for adjustments when the score is below the threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional methods use only vehicle sensors and databases to monitor driving behavior, then the monitoring system is simple and low-cost, but the view of driving behavior is insufficient and non-robust
Solution Approach 1:
The patent combines data from multiple sources including vehicle sensors, remote vehicles, road users, and road infrastructure devices into a unified monitoring system. This integration creates a comprehensive view of driving behavior by merging previously separate data streams, thereby improving robustness while managing complexity through coordinated data collection.
Solution Approach 2:
The monitoring system is designed to serve multiple functions: it assesses individual vehicle behavior, evaluates interactions with other road users, monitors infrastructure compliance, and generates comprehensive behavior scores. This multi-functionality allows a single system to address various aspects of driving behavior assessment simultaneously.
2Reliability
If conventional methods focus only on vehicle condition and basic driving actions, then the scoring system is simple to implement, but it does not consider adverse behavior towards other road users
Solution Approach 1:
The behavior scoring system is divided into multiple components: individual vehicle behavior scoring, interaction behavior scoring with other road users, and infrastructure interaction scoring. Each component evaluates specific aspects of driving behavior independently, then combines them into an overall assessment. This segmentation allows comprehensive evaluation while maintaining manageable complexity through modular scoring.
3Measurement precision
If edge computing device processes all vehicle behavior data in real-time, then the behavior score calculation is comprehensive and accurate, but the processing demands and latency increase
Solution Approach 1:
The system performs preliminary processing of data from various sources before final behavior score calculation. Data from vehicles, road users, and infrastructure devices is collected and pre-processed in advance, allowing the edge computing device to focus computational resources on the actual behavior assessment rather than raw data handling, thereby reducing latency while maintaining accuracy.
Data Source
AI summary
The disclosure herein pertains to monitoring and quantifying vehicle drive behavior using an edge computing device. In one example, a method may include receiving vehicle data from a vehicle; receiving remote vehicle data from a remote vehicle; receiving road user data from a road user; receiving road infrastructure data from a road infrastructure device; calculating a vehicle behavior score of the vehicle using vehicle data and one or more of remote vehicle data, road user data, and road infrastructure data; and outputting and storing the vehicle behavior score.