Lateral Vehicle Control Using Swarm-Verified Lane Type Detection
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Solution Overview
Problem
Existing technologies face challenges in safely laterally controlling a motor vehicle when swarm data and sensor data diverge, particularly on roads with absent or obscured center lines, which can lead to collisions with oncoming traffic.
Innovation Solution
The method involves determining the lane type of roadway markings based on both sensor data and swarm data. If the lane types determined by both sources diverge, the lane type from the swarm data is prioritized, assuming an error in the sensor data, to ensure safe lateral control of the vehicle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor data is used to determine lane type, then real-time detection capability is improved, but reliability deteriorates when sensor data diverges from actual road conditions
Solution Approach 1:
The system uses feedback by comparing sensor data with swarm data from multiple vehicles to verify lane type determination. When sensor data diverges from swarm data, the system receives feedback indicating potential sensor error and switches to using swarm data for lane type determination, thereby maintaining reliability while preserving real-time detection capability.
Solution Approach 2:
Swarm data acts as an intermediary between individual sensor data and lateral control decisions. By introducing this intermediate verification layer that aggregates data from multiple vehicles, the system resolves the contradiction by using the intermediary to validate sensor readings and ensure reliable lane type determination even when individual sensors fail.
2Device complexity
If only sensor data is used for lateral control, then system complexity is reduced, but reliability deteriorates due to sensor errors on roads with absent or obscured center lines
Solution Approach 1:
The system implements self-service by having each vehicle contribute its sensor data to the swarm data set, which then serves all vehicles. This distributed approach allows the system to maintain high reliability through collective verification without requiring complex centralized processing infrastructure, as each vehicle independently uses the swarm data for its own lateral control.
Solution Approach 2:
The system merges sensor data from multiple vehicles into swarm data, combining individual measurements to create a more reliable collective dataset. This merging approach improves reliability by cross-validating lane type determinations across multiple vehicles while keeping individual system complexity low, as each vehicle only needs to process its own sensor data and the aggregated swarm data.
3Reliability
If swarm data is prioritized when sensor data and swarm data diverge, then reliability is improved, but loss of information occurs by discarding sensor data
Solution Approach 1:
The system converts the potential harm of sensor data loss into a benefit by using the divergence between sensor data and swarm data as an indicator of sensor error. When divergence occurs, the system interprets this as the sensor potentially being wrong and switches to swarm data, thereby converting what could be information loss into a safety mechanism that prevents incorrect lateral control based on erroneous sensor readings.
Data Source
AI summary
Technologies and techniques for laterally controlling a motor vehicle on a road, where a roadway marking assigned to a driver's side of the motor vehicle is assigned to a lane type based on sensor data. The lane type characterizes whether the roadway marking is assigned to an ego lane on which the motor vehicle is to be guided, or whether it is assigned to a neighboring lane adjacent to the ego lane. The roadway marking is also assigned to the lane type, based on swarm data, and the lane type assigned to the roadway marking is established as the lane type that is determined as a function of the swarm data when the sensor lane type and the swarm data lane type diverge. The motor vehicle is laterally controlled as a function of the established lane type of the roadway marking assigned to the driver's side of the motor vehicle.