RF-Augmented Driver Vehicle Tracking Through Occlusion
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Solution Overview
Problem
Existing vehicle tracking systems for autonomous vehicles struggle to detect vehicles that become occluded by other vehicles, leading to increased safety risks and inefficiencies.
Innovation Solution
The system employs a combination of sensors and radio frequency receivers on autonomous vehicles to detect and generate predictive drive patterns for occluded vehicles by analyzing radio frequency signals emitted by other vehicles, allowing for continuous tracking even when vehicles are not directly visible.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are used to detect vehicles, then vehicle detection capability is improved, but vehicles that are occluded by other vehicles cannot be detected
Solution Approach 1:
The patent introduces radio frequency signals as an intermediary to detect occluded vehicles. The system uses RF receivers to capture signals from vehicles that are not directly visible to sensors, creating a complementary detection channel that penetrates occlusions and provides information about hidden vehicles.
Solution Approach 2:
The patent transitions from purely visual/sensor-based detection (2D image space) to incorporating radio frequency detection (3D electromagnetic space). This dimensional shift allows the system to detect vehicles through occlusions by utilizing a different physical domain where line-of-sight requirements are less stringent.
2Reliability
If radio frequency signals are used to detect occluded vehicles, then tracking of occluded vehicles is improved, but processing complexity increases
Solution Approach 1:
The system performs preliminary association between RF signals and vehicles using drive characteristics before full tracking is needed. By pre-linking signals to specific vehicles based on characteristics like speed and direction, the system reduces the computational burden during active tracking of occluded vehicles.
Solution Approach 2:
The system uses feedback from sensor data to validate and refine RF-based predictions. When a vehicle becomes unoccluded, sensor data provides feedback to confirm the predicted position and characteristics, allowing the system to correct and improve its tracking accuracy while managing processing loads.
3Reliability
If predictive drive patterns are generated for occluded vehicles, then safety is improved, but processing demands increase
Solution Approach 1:
The system generates predictive drive patterns selectively for occluded vehicles rather than continuously for all vehicles. By applying predictive modeling only when necessary (when vehicles are occluded), the system improves safety for critical cases while avoiding unnecessary processing demands for vehicles already fully visible and trackable.
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
Enhances safety and efficiency by enabling the autonomous vehicle to anticipate and re-identify occluded vehicles, reducing processing demands and maintaining accurate tracking capabilities.
Implementation Method 1
receiving at least one radio frequency signal from at least one of the driver vehicle or at least one electronic device
Data Source
AI summary
Systems for augmenting the tracking of driver vehicles are disclosed. The systems include a plurality of sensors positioned on an autonomous vehicle, and a radio frequency receiver(s) positioned on the autonomous vehicle. The system also includes a computing system(s) in electronic communication with the plurality of sensors and the radio frequency receiver(s). The computing system(s) is configured to augment tracking of a driver vehicle by performing processes including detecting object data for the driver vehicle, and receiving at least one radio frequency signal from the driver vehicle(s) and/or an electronic device(s). The process also includes determining drive characteristics relating to the received radio frequency signal(s) and determining if the received radio frequency signal(s) is associated with the driver vehicle. In response to determining the received radio frequency signal(s) is associated with the driver vehicle, generating a predictive drive pattern for the driver vehicle.