SPAT Message Confidence Scoring for Reliable Vehicle Control
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Solution Overview
Problem
Traffic control devices sometimes send unreliable SPAT-compliant messages, leading to suboptimal or dangerous vehicle actions due to incorrect or intentionally altered information.
Innovation Solution
A system that determines a confidence score for SPAT-compliant messages by comparing them to V2X-compliant messages from surrounding vehicles, preventing actions when the score is below a threshold and allowing controlled vehicle operations when the score is above the threshold, without relying on visual image processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If SPAT messages are received and used for vehicle control actions, then vehicle automation and efficiency are improved, but reliability deteriorates when messages contain incorrect or intentionally altered information
Solution Approach 1:
The system implements feedback by comparing the received SPAT message against actual traffic light observations from cameras and sensor data from other vehicles. This closed-loop verification ensures that automated vehicle actions are based on validated information, resolving the reliability issue while maintaining automation.
Solution Approach 2:
The patent introduces an intermediary verification system that acts as a mediator between the raw SPAT message and the vehicle control system. This intermediary layer cross-checks message authenticity using multiple data sources before allowing automated actions, thus improving reliability without reducing automation extent.
2Measurement precision
If visual image processing is used to verify traffic light status, then measurement precision is improved, but device complexity and processing overhead increase
Solution Approach 1:
The system achieves multi-functionality by using the same camera and sensor array for multiple purposes: primary driving assistance, traffic light verification, and environmental awareness. This universal approach improves measurement precision without significantly increasing device complexity, as existing components serve multiple roles.
Solution Approach 2:
Instead of processing complex visual images directly, the system creates simplified digital representations or copies of traffic light states from multiple sources (SPAT messages, other vehicles' data, camera feeds). These copied data points are easier to process and compare, maintaining precision while reducing computational overhead.
Data Source
AI summary
A confidence score (or measure) that is related to the reliability of signal phase and time (SPAT)-compliant messages received at a vehicle. Vehicle-to-everything (V2X)-compliant messages are received from other vehicles and compared to the SPAT-compliant messages. Behavior of vehicles (as indicated in the V2X-compliant messages) in view of the content of the SPAT-compliant messages is evaluated for consistency and a numeric (or other type of) score or measure assigned to the SPAT-compliant message (indicating reliability of the SPAT message). The score is compared to a threshold and based upon the comparison, a determination can be made as to whether to use the SPAT-compliant message to perform an action.