Vehicle Camera Positioning for Traffic Light Occlusion Control
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Solution Overview
Problem
In autonomous driving, traffic lights can be shielded from view by preceding vehicles, leading to unnecessary control measures that increase inter-vehicle distance and discomfort for passengers, as existing systems struggle to balance view obstruction and safe following distance.
Innovation Solution
A method that calculates an imaging-enabled area based on camera angle of view and map information to determine if the vehicle is positioned to capture traffic lights, allowing for controlled adjustments in inter-vehicle distance and lateral positioning to prevent view obstruction by preceding vehicles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the own vehicle maintains a large inter-vehicle distance to prevent the traffic light from being shielded, then the traffic light recognition reliability is improved, but the passenger comfort deteriorates due to unnecessary large spacing
Solution Approach 1:
The system performs preliminary determination of the imaging-enabled area using map information and camera parameters before actual traffic light recognition. This allows the vehicle to proactively adjust its position only when necessary to maintain the traffic light within the camera's field of view, rather than constantly maintaining large distances. The preliminary calculation of imaging conditions enables selective application of shielding avoidance control.
Solution Approach 2:
The system applies shielding avoidance control selectively based on the determined imaging-enabled area. When the vehicle is within this area, normal following distance is maintained. When outside this area, the system adjusts position to restore imaging capability. This localized application of control measures optimizes both recognition reliability and passenger comfort by avoiding unnecessary distance maintenance.
2Reliability
If the own vehicle maintains sufficient inter-vehicle distance to ensure the traffic light is not shielded, then the traffic light visibility is improved, but the vehicle productivity deteriorates due to reduced lane changing frequency and increased travel time
Solution Approach 1:
The system calculates the imaging-enabled area in advance using map information and camera parameters, enabling proactive determination of when position adjustment is necessary. This preliminary action allows the vehicle to maintain normal following distance during conditions where imaging is already sufficient, thereby preserving productivity while ensuring visibility when needed.
Solution Approach 2:
The system dynamically adjusts the inter-vehicle distance based on the vehicle's position relative to the imaging-enabled area. When the vehicle enters or exits this area, the control system activates or deactivates shielding avoidance measures. This dynamic adjustment optimizes both traffic light visibility and vehicle productivity by applying distance maintenance only when imaging conditions require it.
3Reliability
If the system constantly adjusts inter-vehicle distance to prevent shielding, then the traffic light recognition is improved, but the device complexity increases due to continuous monitoring and adjustment mechanisms
Solution Approach 1:
The system performs preliminary calculation of the imaging-enabled area using pre-stored map information and fixed camera parameters before actual driving. This upfront determination creates a reference framework that simplifies ongoing control decisions. Instead of continuously analyzing complex imaging conditions, the system compares current position against the pre-calculated area boundaries, reducing computational complexity while maintaining recognition reliability.
4Measurement precision
If the own vehicle maintains large inter-vehicle distance to avoid shielding the traffic light, then the traffic light detection accuracy is improved, but the time to reach destination deteriorates due to extended travel distance
Solution Approach 1:
The system determines the imaging-enabled area in advance using map information and camera characteristics, creating a reference zone where traffic lights are naturally visible. This preliminary determination allows the vehicle to maintain normal following distance within this zone, preserving travel time efficiency while ensuring detection accuracy is maintained through strategic position maintenance at zone boundaries.
Solution Approach 2:
The system applies shielding avoidance control locally only when the vehicle approaches boundaries of the imaging-enabled area. Within the area, normal following distance is maintained for time efficiency. At boundaries, position adjustment is applied locally to restore imaging conditions. This localized control strategy optimizes both detection accuracy and travel time by avoiding unnecessary distance maintenance throughout the entire journey.
Data Source
AI summary
A method for controlling a vehicle including: based on map information including information of an installation position of a traffic light and information of a lane controlled by the traffic light and a range of the angle of view of a camera mounted on the own vehicle, calculating an imaging-enabled area in which an image of the traffic light can be captured on the lane by the camera; determining whether or not the own vehicle is positioned in the imaging-enabled area; and when the own vehicle is positioned in the imaging-enabled area, controlling the own vehicle in such a way that the traffic light is not shielded from the range of the angle of view of the camera by a preceding vehicle of the own vehicle.