Automatic Vehicle Classification via Acceleration Analysis
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Solution Overview
Problem
Existing vehicle control mechanisms, such as adaptive speed maintainers and overtaking support functions, rely on manual classification of target vehicles, which diverts the driver's attention and increases the risk of traffic accidents, and require multiple data points for accurate characterization.
Innovation Solution
A method and device that determine target vehicle characteristics solely based on acceleration and distance, using a speed determination unit, acceleration determination unit, and acceleration value processing unit to classify vehicles and deliver classification data to a regulating device, thereby simplifying the process and reducing the need for manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual classification of target vehicles is used, then driver input can provide accurate classification information, but driver attention is diverted from traffic leading to increased accident risk
Solution Approach 1:
The system enables automatic vehicle classification by having the vehicle itself reveal its characteristics through acceleration behavior. The classification is performed autonomously by processing acceleration data without requiring driver intervention, thus maintaining safety while achieving accurate classification.
Solution Approach 2:
The patent replaces manual classification methods with an automated electronic system that uses acceleration sensors and processing units. This substitution eliminates the need for driver input while maintaining or improving classification accuracy through objective measurement of vehicle acceleration characteristics.
2Measurement precision
If multiple data points are collected for target vehicle characterization, then more accurate vehicle classification can be achieved, but system complexity and data processing requirements increase
Solution Approach 1:
The patent extracts and focuses on a single critical parameter - acceleration - that is sufficient for vehicle classification. By taking out only the essential data point rather than collecting multiple parameters, the system achieves accurate characterization while minimizing processing complexity.
Solution Approach 2:
The system changes the approach from collecting multiple static parameters to measuring dynamic acceleration parameters over time. This parameter transformation allows accurate vehicle type identification through acceleration patterns, reducing the need for multiple simultaneous measurements and simplifying the data collection system.
Data Source
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AI summary
The present invention relates to a method, a device and a computer programme product for supporting a regulating strategy for the driving of a vehicle, and to a motor vehicle comprising such a device. According to the method, a number of acceleration values (a) for a target vehicle are determined (36) on the basis of input values (?v), which input values take the form of or are derived from detected distance values for the distance between the vehicle and the target vehicle. The acceleration values are thereafter processed (40) to obtain data (CD) which characterise the target vehicle. These data which characterise the target vehicle are thereafter delivered (42) for regulating (44) the driving of the vehicle.