Deceleration Location Prediction Using Dynamic Traffic Condition Indices
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing techniques for predicting vehicle energy consumption at intersections are inaccurate due to varying traffic conditions, leading to errors in energy consumption estimation.
Innovation Solution
A traveling state prediction device that acquires traffic condition indices and variation factors to predict deceleration locations based on relationships between different traffic conditions, using a processor and storage medium to analyze vehicle speed patterns and traffic volume, enabling accurate deceleration location prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If stop probability is calculated based on basic intersection attributes, then energy consumption can be estimated, but prediction accuracy deteriorates due to varying traffic conditions
Solution Approach 1:
The patent changes the parameters used for prediction from static intersection attributes to dynamic traffic condition indices. Specifically, it introduces traffic condition indices that reflect real-time traffic states (congestion levels, traffic flow patterns) and uses these varying parameters to calculate stop probabilities, thereby adapting the prediction model to different traffic conditions and improving accuracy.
Solution Approach 2:
The patent transforms the static prediction model into a dynamic one by continuously updating traffic condition indices based on current traffic data. The stop probability calculation is no longer based on fixed intersection attributes but on dynamically changing traffic conditions, allowing the system to adapt to varying traffic patterns and improve prediction accuracy across different scenarios.
2Measurement precision
If traffic condition indices and variation factors are acquired and analyzed, then deceleration location prediction accuracy improves, but device complexity increases
Solution Approach 1:
The patent segments the prediction system into distinct functional modules: a traffic condition index acquisition unit that collects traffic data, a variation factor acquisition unit that identifies factors causing traffic changes, and a deceleration location prediction unit that processes this information. This segmentation allows each module to perform a specific function, managing complexity through modular design while maintaining high prediction accuracy.
Solution Approach 2:
The patent introduces traffic condition indices as intermediary variables that mediate between raw traffic data and deceleration location predictions. These indices serve as processed intermediaries that capture essential traffic characteristics, simplifying the relationship between complex traffic conditions and prediction outcomes while improving accuracy.
Data Source
AI summary
A traveling state prediction device for predicting a traveling state of a host vehicle, includes an index acquisition unit that acquires a traffic condition index which is an index of a traffic condition on a planned travel route of the host vehicle, a variation factor acquisition unit that acquires a traffic variation factor which is a factor that causes variations in the traffic condition, and a deceleration location prediction unit that predicts a deceleration location of the host vehicle on the planned travel route based on the traffic variation factor and the traffic condition index. The deceleration location prediction unit predicts the deceleration location based on a relationship between the traffic condition indices in two different situations for a certain traffic variation factor, or a relationship between the traffic condition index corresponding to a certain traffic variation factor and the traffic condition index under an average traffic condition.