Vehicle Message Filtering by Road Type and Driving Context
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Solution Overview
Problem
Existing vehicle communication systems fail to efficiently filter vehicle messages based on driving situations, particularly road type, leading to inefficient processing and resource utilization.
Innovation Solution
A communication device and vehicle control device that utilize an RF communication device and a processor to filter vehicle messages based on road type information, receiver sensitivity, wheel direction, and speed information, setting message passing zones and priority levels to optimize message handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If filtering is performed on all received vehicle messages, then processing accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent segments the filtering process into multiple stages: initial filtering based on message type and basic parameters, followed by more complex filtering based on driving situation and road type. This hierarchical segmentation allows the system to quickly eliminate irrelevant messages before applying computationally intensive filtering criteria, thereby maintaining high filtering accuracy while reducing overall processing time.
Solution Approach 2:
The patent performs preliminary classification of vehicle messages into categories (e.g., basic information messages, control messages, sensor data) before detailed filtering. By pre-organizing messages into structured groups with associated metadata, the system prepares data in advance for faster processing during actual filtering operations, reducing latency while maintaining comprehensive filtering accuracy.
2Device complexity
If filtering is performed without considering road type information, then device complexity is reduced, but filtering effectiveness deteriorates
Solution Approach 1:
The patent implements a universal filtering framework that can adapt to different road types (highway, urban, rural, curved roads) using the same base processing architecture. The system maintains a library of road type-specific filtering parameters and dynamically selects appropriate parameters based on current road conditions, allowing the filtering system to handle diverse scenarios without requiring separate dedicated systems for each road type, thus balancing complexity and effectiveness.
Solution Approach 2:
The filtering system dynamically adjusts its parameters and thresholds based on detected road type and driving situation. For example, on curved roads, the system increases filtering sensitivity for lateral acceleration data, while on straight highways, it focuses on speed and longitudinal acceleration. This dynamic adaptation allows the same filtering device to optimize effectiveness for varying road conditions without requiring hardware changes, maintaining low complexity while achieving high productivity.
3Loss of information
If all vehicle messages are processed equally, then information completeness is maintained, but resource utilization efficiency decreases
Solution Approach 1:
The patent applies local quality by assigning different processing priorities and resource allocations to different message types based on their importance and relevance to current driving situations. Critical safety-related messages receive full processing resources and guaranteed delivery, while less critical telematics or entertainment messages receive reduced processing priority. This differentiated approach ensures that essential information is completely processed while non-essential information uses minimal resources, optimizing the balance between information completeness and energy consumption.
4Device complexity
If message filtering is not performed, then device complexity is minimized, but processing efficiency deteriorates
Solution Approach 1:
The patent extracts and removes redundant or irrelevant information from vehicle messages before further processing. The filtering system identifies and discards duplicate messages, obsolete data, and information not relevant to current driving conditions, allowing the core processing system to focus only on essential data. This extraction approach maintains relatively simple device architecture while significantly improving processing efficiency by reducing the volume of data requiring comprehensive analysis.
Data Source
AI summary
A communication device and a vehicle control device including the same according to an embodiment of the present disclosure include: an RF communication device configured to receive vehicle messages from a plurality of adjacent external vehicles based on an RF signal; and a processor configured to perform filtering of the vehicle messages based on road type information, receiver sensitivity information of the RF signal, wheel direction information, and speed information. Accordingly, the vehicle messages received from the adjacent vehicles may be efficiently filtered.