Vehicle Entry Prediction Using Turning Radius and Front Space
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Solution Overview
Problem
Existing vehicle behavior prediction systems fail to accurately determine if a target vehicle can enter a host lane from an adjacent road region due to insufficient consideration of space and turning radius, leading to incorrect predictions and unnecessary driving support.
Innovation Solution
A vehicle behavior prediction device that utilizes the length of an empty space in front of the target vehicle, its turning radius, lateral position, and inclination to predict entry into the host lane, incorporating turning radius estimation based on tire steered angle and stored vehicle type information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If prediction is performed simply based on turn signal lamp or lighting state, then prediction process is simple, but prediction accuracy deteriorates when space in front of target vehicle is insufficient
Solution Approach 1:
The system changes the parameters used for prediction from simple lighting states to include front distance and turning radius. By incorporating these additional parameters, the system achieves more accurate prediction of whether a target vehicle can enter the host lane, resolving the contradiction between simple prediction process and accurate prediction results.
2Measurement precision
If turning radius estimation based on tire steered angle is implemented, then entry prediction accuracy is improved, but measurement and detection difficulty increases
Solution Approach 1:
The system replaces direct mechanical measurement of turning radius with estimation based on tire steered angle detection. This substitution allows the system to infer turning capability through angular measurement rather than direct physical measurement, improving accuracy while managing detection complexity through sensor-based approaches.
3Measurement precision
If multiple parameters (front distance, turning radius, lateral position, inclination) are used for prediction, then prediction accuracy is improved, but device complexity increases
Solution Approach 1:
The system segments the prediction process into distinct functional units: front distance acquisition, turning radius estimation, lateral position detection, and inclination detection. Each unit handles a specific parameter independently, allowing the system to incorporate multiple parameters for high accuracy while managing complexity through modular architecture.
Solution Approach 2:
The system employs a multi-functional prediction device that simultaneously processes multiple parameters (front distance, turning radius, lateral position, inclination) to achieve comprehensive entry prediction. This universal approach allows a single system to handle diverse input parameters and provide accurate predictions across various driving scenarios.
Data Source
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Figure 3A~3C
AI summary
A vehicle behavior prediction device includes a target vehicle detection unit configured to detect a target vehicle existing in a road region, a distance acquisition unit configured to acquire a front distance that is a distance between the target vehicle and an obstacle existing in front of the target vehicle, a turning radius estimation unit configured to estimate a turning radius of the target vehicle, and an entry prediction unit configured to predict whether or not the target vehicle is able to enter a host lane while avoiding an obstacle.