Braking Data Mapping for Roadway Event Detection
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Solution Overview
Problem
Current navigation systems are imprecise in identifying events of interest on roadways, such as accidents or traffic, due to the lack of utilization of vehicle control data like brake information, which can provide valuable insights into vehicle behavior.
Innovation Solution
A system that analyzes vehicle control data, specifically panic braking events, to identify events of interest on roadways by receiving and processing braking data from multiple vehicles, determining the location, and transmitting notifications to other vehicles, allowing for predictive analytics and proactive route adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional navigation systems are used to identify events of interest, then the system complexity remains low, but the measurement precision and reliability of event identification deteriorate
Solution Approach 1:
The patent combines multiple data sources (brake sensors, location sensors, network access devices) and merges them with existing navigation systems to create a comprehensive event identification system. This integration allows the system to achieve high measurement precision by analyzing correlated data from multiple vehicles while maintaining reasonable system complexity through modular architecture.
Solution Approach 2:
The system makes vehicle control data (brake information, location data) serve multiple functions: not only for vehicle control but also for identifying events of interest, predicting traffic conditions, and providing navigation assistance. This multi-functionality improves event identification precision without proportionally increasing system complexity.
2Reliability
If vehicle control data is collected and analyzed from multiple vehicles, then the reliability of event identification improves, but the quantity of data processing and system complexity increase
Solution Approach 1:
The system extracts only the essential and relevant features from vehicle control data (brake pressure values, location coordinates, timestamps) rather than processing all available vehicle data. This extraction approach maintains high reliability by focusing on critical panic braking indicators while reducing data processing complexity.
Solution Approach 2:
The system performs preliminary filtering and preprocessing of vehicle control data at the source (in individual vehicles) before transmission to the server. Data is pre-processed to identify panic braking events locally, which reduces the complexity of centralized data analysis and improves reliability by ensuring only relevant data is analyzed for event identification.
3Measurement precision
If panic braking events are used to identify events of interest, then the measurement precision improves, but the loss of information about other vehicle behaviors increases
Solution Approach 1:
The system focuses on collecting and analyzing only the specific subset of vehicle control data relevant to panic braking events (brake pressure above threshold, location, timestamp) rather than all vehicle behaviors. This partial action approach achieves high measurement precision for event detection while managing information loss by intentionally excluding irrelevant vehicle behavior data.
Solution Approach 2:
The system applies different data collection and analysis strategies to different aspects of vehicle behavior: detailed analysis for panic braking events (high precision) and aggregated or simplified processing for other vehicle behaviors. This local quality approach maintains high measurement precision for event detection while minimizing information loss for other purposes through selective processing.
Data Source
AI summary
A system for monitoring vehicle behavior based on vehicle control data includes a network access device configured to receive braking data from multiple vehicles, the braking data corresponding to vehicle braking events having a brake pressure that is equal to or greater than a threshold brake pressure and including a corresponding location. The system further includes a processor coupled to the memory and configured to determine an event of interest on a roadway by analyzing the braking data and the corresponding location, and to transmit a notification of the event of interest to at least one vehicle.