Driving Behavior Prediction Platform for Autonomous Vehicles
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Solution Overview
Problem
Current navigation systems for autonomous vehicles are limited in their ability to predictively adjust driving behavior in advance of encountering specific locations or scenarios due to insufficient data from onboard sensors.
Innovation Solution
A prediction platform that determines driving characteristic information for vehicles and processes it to identify response and behavior types associated with specific segments of a travel path, linking this data with mapping information and behavior connection link-chains to enable predictive driving decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If onboard sensors are used to gather real-time data, then data collection capability is improved, but predictive accuracy deteriorates due to insufficient data
Solution Approach 1:
The patent combines real-time sensor data from onboard sensors with historical driving behavior data and mapping information to create a comprehensive data set. This merging of multiple data sources resolves the contradiction by providing sufficient data for accurate predictions while maintaining real-time measurement capabilities.
Solution Approach 2:
The system performs preliminary analysis of historical driving behavior data and mapping information before real-time decision making. By pre-processing and storing relevant patterns and characteristics, the system enables accurate predictions without relying solely on real-time sensor data, thus resolving the data insufficiency problem.
2Speed
If real-time sensor data is used for navigation decisions, then response speed is improved, but prediction capability deteriorates due to lack of anticipatory information
Solution Approach 1:
The system pre-analyzes historical driving behavior data and mapping information to identify patterns and characteristics before they are needed for real-time decisions. This preliminary action enables the system to make fast real-time responses while having already processed and stored predictive information from historical data.
Solution Approach 2:
The patent introduces behavioral data and mapping information as intermediary elements between real-time sensor data and navigation decisions. These intermediaries provide anticipatory information that enhances prediction capability without slowing down the real-time response mechanism.
3Reliability
If more data sources are integrated for prediction, then predictive accuracy is improved, but system complexity increases
Solution Approach 1:
The patent segments the data processing system into distinct modules: real-time sensor data processing, historical driving behavior data analysis, mapping information processing, and integration/decision-making components. This segmentation manages complexity by organizing multiple data sources into manageable, independent modules that can be processed separately and then integrated.
Data Source
AI summary
An approach is provided for predicting driving behavior. A prediction platform determines driving characteristic information for one or more vehicles in association with a segment of a travel path navigated by each of the one or more vehicles. The prediction platform also processes driving characteristic information to determine one or more response types, one or more behavior types, or a combination thereof associated with the segment of the travel path and associates the one or more response types, the one or more behavior types, or a combination thereof with mapping information for specifying the segment of the travel path, a behavior connection link-chain, or a combination thereof.