Adaptive Movement Region Prediction for Mixed Traffic
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing movement region prediction systems struggle to accurately predict the movement regions of both normal and abnormal mobile bodies around a host vehicle, leading to increased collision risks and reduced safety and efficiency in mixed traffic environments.
Innovation Solution
A movement region prediction apparatus that detects mobile bodies, assesses their normality based on factors like weaving, compliance with traffic rules, and collision probability, and selects appropriate movement prediction models to tailor the prediction of their movement regions, allowing for individualized predictions and improved safety and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a uniform broad movement region is set for all mobile bodies, then the safety of the host vehicle is improved, but the travel efficiency deteriorates due to excessive collision risk warnings for normal vehicles
Solution Approach 1:
The patent applies local quality by differentiating the movement region prediction based on the type of mobile body. Normal vehicles receive a first movement prediction model with smaller movement regions, while abnormal vehicles receive a second movement prediction model with larger movement regions. This localized differentiation resolves the contradiction by providing appropriate safety margins only where needed (for abnormal vehicles) while maintaining travel efficiency for normal vehicles.
2Productivity
If a uniform small movement region is set for all mobile bodies, then the travel efficiency is improved, but the safety deteriorates due to inability to detect abnormal vehicles
Solution Approach 1:
The patent changes the parameter of movement region size based on the detected type of mobile body. By switching between different movement prediction models (first model for normal vehicles, second model for abnormal vehicles), the system dynamically adjusts the prediction parameters to balance safety and efficiency requirements for different vehicle types.
3Measurement precision
If multiple movement prediction models are maintained for different mobile body types, then the prediction accuracy is improved, but the system complexity increases
Solution Approach 1:
The patent implements a dynamic model selection mechanism that automatically chooses the appropriate movement prediction model based on real-time detection of mobile body type. This dynamic adaptation allows the system to maintain high prediction accuracy through multiple specialized models while managing complexity through automated selection logic rather than requiring manual configuration or complex integration of all models simultaneously.
Data Source
AI summary
A movement region prediction apparatus includes a mobile body detection device that detects a mobile body around a host vehicle; a prediction device that predicts a movement region of the detected mobile body; and a degree-of-normality acquisition device that acquires degree of normality of a situation of movement of the detected mobile body. The prediction device has a plurality of movement prediction models for predicting the movement region of the mobile body, and selects a movement prediction model from the plurality of movement prediction models based on the degree of normality acquired by the degree-of-normality acquisition device, and predicts the movement region of the mobile body using the selected movement prediction model.