Vehicle Telematics Inference of ADAS Operation for Risk Assessment
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Solution Overview
Problem
The operational state of Advanced Driver Assistance Systems (ADAS) features in vehicles is not consistently known, affecting driving risk assessment and insurance considerations, as this information is often not exposed to mobile devices or telematics applications.
Innovation Solution
A computer-implemented method and system that processes telematics information from sensors to determine the probability of ADAS feature operation during a trip by comparing vehicle movement data against known benchmarks, using machine learning and other analytical models to assess the likelihood of features like adaptive cruise control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If telematics information is processed to determine ADAS operational status, then measurement precision of ADAS state is improved, but device complexity increases
Solution Approach 1:
The patent uses telematics information as an intermediary to indirectly determine ADAS operational status. Instead of directly accessing ADAS system states, the system processes telematics data (acceleration, braking, steering patterns) that reflect ADAS operation, thereby achieving detection without direct system integration
Solution Approach 2:
The patent replaces direct mechanical/system-level ADAS status detection with computational analysis of telematics data. Machine learning models analyze patterns in sensor data to infer ADAS operational states, substituting physical system access with information processing
2Reliability
If vehicle movement information is analyzed to determine ADAS probability, then reliability of risk assessment is improved, but loss of time in data processing increases
Solution Approach 1:
The patent performs preliminary processing of telematics information during normal vehicle operation, preparing and organizing data before risk assessment is needed. This allows the system to have pre-processed movement information ready for rapid analysis when risk scoring is required
Solution Approach 2:
The patent transforms raw telematics data into meaningful parameters that indicate ADAS operational probability. By changing the form of data representation (from raw sensor values to processed movement characteristics), the system enables faster and more reliable risk assessment
Data Source
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AI summary
A system can include a mobile device that includes one or more sensors for sensing information during a trip in a vehicle. A hardware processor can execute operations including receiving telematics information produced by one or more sensors during a trip in a vehicle; processing, by a hardware processor, the received telematics information to identify vehicle movement information for the vehicle during the trip; determining, by the hardware processor, a probability that an advanced driver assistance system (ADAS) feature of the vehicle was operational during the trip based, at least in part, on the vehicle movement information for the vehicle during the trip; and determining, by the hardware processor, a risk score for the vehicle or a driver of the vehicle based, at least in part, on the probability that the ADAS feature was operational.