Anomalous Travel Location Detection Using Yaw Rate Divergence
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Solution Overview
Problem
Conventional devices for detecting anomalous travel locations due to lane deviations rely on costly on-board imaging devices, resulting in insufficient data collection and lack of generality when used across multiple vehicles.
Innovation Solution
A system utilizing a prevalent sensor, such as a yaw rate sensor, to detect anomalous travel locations by calculating divergence from average turning values and smoothing transitions to reduce outlier effects, allowing for robust and accurate identification of such locations across multiple vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If on-board imaging devices are used for detecting anomalous travel locations, then measurement precision is improved, but device cost increases and data collection coverage decreases
Solution Approach 1:
The patent replaces expensive on-board imaging devices with inexpensive prevalent sensors (GPS receivers, yaw rate sensors, accelerometers) that are already widely installed in vehicles. This substitution dramatically reduces device cost while maintaining sufficient detection capability through statistical processing of data from multiple vehicles
Solution Approach 2:
The patent makes the detection system universal by using prevalent sensors that are already present in most modern vehicles for other purposes (navigation, stability control). This multi-functionality approach eliminates the need for specialized expensive imaging equipment while enabling widespread data collection
2Measurement precision
If on-board imaging devices are used for detecting anomalous travel locations, then measurement precision is improved, but the quantity of data collection from multiple vehicles decreases
Solution Approach 1:
By using prevalent sensors already installed in most vehicles, the system enables universal participation in data collection. This dramatically increases the quantity of data from multiple vehicles, allowing statistical processing to overcome individual variability and achieve high detection accuracy
Solution Approach 2:
The patent merges data from multiple vehicles' prevalent sensors through statistical processing to achieve detection accuracy that compensates for the lower precision of individual sensors. The combined data volume from many vehicles overcomes the limitations of any single vehicle's sensor
3Adaptability or versatility
If turning values from multiple vehicles are collected and processed, then generality of information is improved, but computation load increases
Solution Approach 1:
The patent performs preliminary local processing at each vehicle to extract only essential turning value data and transmits it to the server. This preliminary action reduces the data volume requiring centralized computation while preserving the generality achieved through multi-vehicle statistics
Solution Approach 2:
The system extracts only the necessary turning value parameters from raw sensor data and transmits minimal essential information to the server. This extraction approach reduces computation load for statistical processing while maintaining the generality of the collected information
Data Source
AI summary
A turning value corrector corrects turning values contained in multiple pieces of travel history information. A reference turning value calculator uses multiple turning values that have been associated with the same calculation point to calculate a reference turning value. An anomalous travel location detector calculates the divergence from the reference turning value for each piece of travel history information subjected to detection of an anomalous travel location. Locations for which the deviation from the reference turning value is large are detected as anomalous travel locations.