Image Processing Filters for Fast Vehicle Speed Convergence
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Solution Overview
Problem
Existing object detection systems in vehicles face significant errors in distance and speed calculations immediately after the start of detection, particularly for distant or oncoming vehicles with high relative speeds, which can lead to delayed filter convergence and inaccurate vehicle control.
Innovation Solution
An image processing device that performs a parallel filter process using multiple filters with different initial speed values, selecting the filter with the smallest accumulated observation residual value to quickly converge on accurate distance and speed estimates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single filter process is used for distance and speed measurement, then the device complexity is low, but the measurement precision is poor immediately after detection start
Solution Approach 1:
The filter processing is segmented into multiple parallel filter processes (first filter process and second filter process) that operate simultaneously. Each filter uses different initial speed values to handle different detection scenarios, improving measurement precision without requiring complex sequential processing
Solution Approach 2:
The system dynamically switches between different filter processes based on detection conditions. The selection unit chooses which filter to use based on real-time observation residual values, allowing the system to adapt to changing detection scenarios and maintain high precision across different situations
2Reliability
If the filter process is started immediately with arbitrary initial values, then the productivity is high, but the reliability is low due to large errors in initial measurements
Solution Approach 1:
Multiple filter processes are prepared in advance with different initial speed values before detection begins. This preliminary preparation ensures that when detection starts, the system can immediately use an appropriate pre-configured filter, reducing convergence time while maintaining reliability
Solution Approach 2:
The system changes the initial speed value parameter across different filter processes. By providing multiple filters with varied initial parameters (different speed values), the system increases the probability that at least one filter will have appropriate initial conditions, reducing error and convergence time
3Measurement precision
If multiple filter processes are executed in parallel, then the measurement precision improves, but the use of energy increases
Solution Approach 1:
The system dynamically selects one filter process from multiple parallel filters based on real-time performance evaluation. By using the selection unit to choose the most appropriate filter based on observation residual values, the system maintains high measurement precision while avoiding the continuous energy consumption of running all filters simultaneously
Solution Approach 2:
The selection unit extracts and selects only the most suitable filter process from the parallel group based on performance metrics. This extraction approach allows the system to benefit from multiple parallel filters for precision while consuming energy equivalent to running a single selected filter
Data Source
AI summary
An image processing device includes: a distance calculation unit that calculates a distance to a detection target searched from an acquired image; a speed calculation unit that calculates a speed of the detection target; and a filter processing unit that performs a filter process on the calculated distance and speed. Here, the filter processing unit performs a plurality of filter processes for a predetermined period of time and then selects one of the plurality of filter processes.