Vehicle Position Detection Using Conditional Probability Indices
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Solution Overview
Problem
The existing free state determination mechanism in navigation devices is complex and requires optimization of multiple thresholds, making it difficult to achieve precise determination, especially when considering various vehicle positions, and adding or deleting thresholds does not result in optimal conditions.
Innovation Solution
A vehicle position detection device that includes a vehicle information acquisition part, a conditional probability information storage part, a probability index calculation part, and a state determination part, which uses conditional probability information to calculate probability indices for matching and free states, simplifying the determination process by converting vehicle information into probabilities for each state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple thresholds are combined to increase determination precision, then free state determination precision is improved, but determination processing complexity increases
Solution Approach 1:
The patent transforms the determination mechanism from a multi-threshold conditional system to a probability-based parameter system. Instead of combining multiple thresholds (position error threshold, direction error threshold, GPS reception state threshold), the system calculates a single probability value representing the likelihood of being in a free state. This probability is computed by integrating multiple factors (position error, direction error, GPS reception state) into a unified probabilistic parameter, thereby maintaining determination precision while reducing processing complexity.
2Adaptability or versatility
If new determination conditions are added or deleted, then adaptability is improved, but threshold optimization complexity increases
Solution Approach 1:
The patent enables flexible addition or deletion of determination conditions by transforming the system into a probability-based framework. New conditions can be incorporated by adding corresponding probability factors to the calculation, and existing conditions can be removed by eliminating their probability contributions. This approach maintains adaptability while avoiding the complex threshold optimization required in traditional multi-threshold systems, as each probability factor independently contributes to the overall free state probability without requiring coordinated threshold adjustments.
Data Source
AI summary
Free state determination at a high precision is made by using a simpler mechanism. A vehicle position detection device is configured to: store conditional probability information which associates each of values to be taken in vehicle information on a state of an own vehicle, a matching conditional probability that the value occurs in a matching state, and a free conditional probability that the value occurs in a free state; use the conditional probability information to acquire the matching conditional probability and the free conditional probability corresponding to the acquired value of the vehicle information; calculate a probability index in the matching state and a probability index in the free state based on the conditional probabilities; and determine which state is to be selected based on the probability index in the matching state and the probability index in the free state.