Optical Road-Speed Sensor Using Temporal Shifted Signal Sequences
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing sensor devices for detecting relative motion between a vehicle and a road surface are prone to accuracy distortions due to interference frequencies from road surfaces, particularly at low speeds and on critical road conditions, and have high sensitivity to noise.
Innovation Solution
A sensor device with an optical system featuring two photoreceptors arranged at a photoreceptor angle, generating measurement signals that are processed by an algorithm to create phase-shifted temporal sequences, allowing for the determination of vehicle speed and sideslip angle based on temporal shifts of these sequences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If measurement signals from photoreceptors are used to calculate vehicle speed, then speed detection accuracy is improved (≤ ±0.2% FSO), but sensitivity to interference frequencies from road surface structure increases, distorting detected speed and sideslip angle
Solution Approach 1:
The patent introduces an intermediary processing layer between the photoreceptor signals and the final speed calculation. This includes generating multiple temporal sequences from each photoreceptor's measurement signals, applying temporal shift analysis, and using correlation-based methods to identify genuine vehicle motion patterns while filtering out road surface interference frequencies. The intermediary processing transforms raw measurement signals into processed temporal sequences that distinguish between valid motion signals and interference.
Solution Approach 2:
The patent changes the parameter of signal processing by transforming single measurement signals into multiple temporal sequences with different temporal characteristics. By analyzing temporal shifts between these sequences and applying frequency-based filtering, the system modifies how speed is calculated—from direct frequency analysis to a multi-sequence temporal correlation approach that is less sensitive to road surface interference frequencies.
2Measurement precision
If high sensitivity detection method is used, then speed measurement accuracy reaches ≤ ±0.2% FSO, but detection accuracy is distorted by interfering frequencies from road surface structure (asphalt, concrete, water, ice)
Solution Approach 1:
The patent introduces an intermediary processing layer between the photoreceptor signals and the final speed calculation. This includes generating multiple temporal sequences from each photoreceptor's measurement signals, applying temporal shift analysis, and using correlation-based methods to identify genuine vehicle motion patterns while filtering out road surface interference frequencies. The intermediary processing transforms raw measurement signals into processed temporal sequences that distinguish between valid motion signals and interference.
Solution Approach 2:
The patent converts the harmful effect of road surface structure interference into a beneficial filtering mechanism. By analyzing the temporal patterns and frequency characteristics of signals from multiple photoreceptors, the system identifies and exploits the difference between genuine vehicle motion signals and road surface interference. The interference frequencies, while harmful in direct measurement, become identifiable patterns that can be filtered out through temporal sequence analysis and correlation methods, ultimately improving detection reliability across different road conditions.
3Device complexity
If traditional photoreceptor arrangement is used, then device structure is simple, but accuracy at low speeds and noise reduction is insufficient
Solution Approach 1:
The patent transitions from spatial arrangement analysis to temporal sequence analysis by introducing a time dimension to the measurement process. Instead of relying solely on the spatial configuration of photoreceptors, the system generates multiple temporal sequences from each photoreceptor's signals and analyzes temporal shifts between these sequences. This temporal dimension provides additional information that improves low-speed detection accuracy without requiring complex spatial arrangements of photoreceptors.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution provides improved accuracy and reduced sensitivity to interference frequencies, enabling precise speed detection and sideslip angle calculation even on challenging road surfaces.
Implementation Method 1
The optical system has at least two photoreceptors... Each of the two photoreceptors has a plurality of photodiodes. A portion of the road surface is imaged onto each of the plurality of photodiodes and thus detected by the plurality of photodiodes.
Data Source
Figure 1~2
Figure 3
Figure 4~5
AI summary
The invention relates to a sensor device (10) for detecting relative movement between a vehicle (1) and a roadway (FB); with an optical system (11) attached to the vehicle (1), which optical system (11) has at least two photoreceptors (12, 14) arranged at a photoreceptor angle (α) to each other, onto which a part of the roadway (FB) can be imaged and with which the imaged part of the roadway (FB) can be detected, which photoreceptors (12, 14) generate measurement signals (S12, S14) for the detected part of the roadway (FB); and with an evaluation device (20) comprising at least one algorithm (22', 24', 26') for determining at least one vehicle speed (V);wherein the algorithm (22', 24', 26') is configured to form at least two temporal sequences (Σ120, Σ12P, Σ140, Σ14P) from the measurement signals (S12, S14) from each of the two photo receivers (12, 14) and to determine the vehicle speed (V) based on a temporal shift (Δt) of the two temporal sequences (Σ120, Σ12P, Σ140, Σ14P) relative to each other.;