Vehicle Sensor Fusion for Resolving Contradictory ADAS Data
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Solution Overview
Problem
Current advanced driver-assistance systems (ADAS) and automated driving systems struggle to distinguish correct information when receiving contradictory data about the vehicle's environment.
Innovation Solution
A system comprising multiple vehicle sensors and a controller programmed to detect contradictions using a transformer model machine learning algorithm, resolve conflicts by constructing if-then clauses and evaluating them with additional sensor data, and determine truth scores to select the valid information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple sensors are used to gather environmental information, then the quantity and variety of information increases, but the likelihood of receiving contradictory information increases
Solution Approach 1:
The system implements a feedback mechanism where the controller continuously monitors information from multiple sensors, detects contradictions, and resolves them by evaluating additional sensor data. This closed-loop approach ensures that contradictory information is identified and corrected, maintaining reliability while utilizing multiple sensors for comprehensive environmental perception.
Solution Approach 2:
The controller acts as an intermediary that mediates between multiple sensors and the vehicle's decision-making systems. It receives information from various sensors, detects contradictions using a contradiction detection algorithm, and resolves conflicts by evaluating additional sensor data, thereby ensuring reliable information flow throughout the system.
2Reliability
If contradiction detection and resolution mechanisms are implemented, then information reliability improves, but system complexity increases
Solution Approach 1:
The system employs self-service mechanisms where the contradiction detection algorithm and resolution process are integrated into the existing controller, eliminating the need for separate dedicated hardware. The controller uses its existing processing capabilities to detect and resolve contradictions, reducing overall system complexity while maintaining reliability.
Solution Approach 2:
The controller is designed to perform multiple functions: it processes sensor data, detects contradictions using a specialized algorithm, resolves conflicts by evaluating additional sensor information, and communicates with external systems. This multi-functionality reduces the need for separate dedicated components, thereby managing system complexity while ensuring reliable information processing.
3Measurement precision
If transformer model machine learning algorithm is used for contradiction detection, then detection accuracy improves, but computational requirements increase
Solution Approach 1:
The transformer model machine learning algorithm is pre-trained offline to learn patterns of contradictory information from large datasets. This preliminary action allows the model to be deployed in the vehicle's controller with reduced computational requirements during real-time operation, as the heavy lifting of learning contradiction patterns has already been completed during the training phase.
Data Source
AI summary
A system for resolving information contradictions in information received by a vehicle includes a plurality of vehicle sensors for receiving the information and a controller in electrical communication with the plurality of vehicle sensors. The controller is programmed to receive a first piece of information from a first of the plurality of vehicle sensors and receive a second piece of information from a second of the plurality of vehicle sensors. The controller is further programmed to determine a contradiction status between the first piece of information and the second piece of information. The controller is further programmed to resolve a contradiction between the first piece of information and the second piece of information using a third piece of information from a third of the plurality of vehicle sensors in response to determining that the contradiction status is a contradicting status.