Passive Automotive Camera ToF Depth Sensing
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Solution Overview
Problem
Existing vehicle systems lack efficient methods to perform time of flight (ToF) determinations using passive sensors and existing onboard light sources, limiting their ability to provide depth information for autonomous driving and other operations without the power-intensive dedicated sensors like LIDAR.
Innovation Solution
The integration of passive automotive cameras with various onboard light sources, such as taillights, headlights, and turn signals, to construct a ToF camera system by synchronizing the cameras with light sources, allowing for distance calculations using the time of flight principle, and enhancing the system with high dynamic range imaging and adjustable light source configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dedicated active sensors like LIDAR are used for ToF determinations, then depth detection capability is improved, but power consumption increases significantly
Solution Approach 1:
The patent applies universality by enabling passive automotive cameras to perform both their original imaging function and ToF depth detection function. The existing camera hardware is repurposed to detect reflected light from vehicle light sources, allowing a single component to serve multiple purposes: standard image capture and distance measurement, thereby eliminating the need for separate active sensors like LIDAR.
Solution Approach 2:
The system applies self-service by using the vehicle's own existing light sources (headlights, taillights, turn signals) as the illumination source for ToF measurements. Instead of requiring an external or dedicated active sensor system, the vehicle leverages its existing lighting infrastructure to provide the necessary light emission, and the passive cameras detect the reflected light, making the system self-sufficient.
2Adaptability or versatility
If multiple dedicated sensors are installed for different functions, then sensing capability is improved, but device complexity increases
Solution Approach 1:
The patent reduces system complexity by making passive cameras universal components that can perform both standard imaging and ToF depth detection. This multi-functionality eliminates the need for separate dedicated sensors for each function, thereby reducing the overall number of components and simplifying the system architecture while maintaining versatile sensing capabilities.
Solution Approach 2:
The system merges the ToF detection function with the existing passive camera system. By combining depth detection capabilities with standard imaging hardware and integrating light source control with camera operation, the patent consolidates multiple functions into unified subsystems, reducing device complexity while preserving adaptability.
3Use of energy by moving object
If passive cameras are synchronized with light sources for ToF calculations, then power consumption is reduced, but measurement precision may be affected
Solution Approach 1:
The system applies periodic action by synchronizing the emission of light from vehicle light sources with the capture timing of passive cameras. The light sources are activated in periodic pulses, and the cameras are triggered to capture images at corresponding intervals, allowing ToF calculations based on the known emission and reception timing. This periodic synchronization enables accurate depth measurement while using passive components.
Solution Approach 2:
The system uses feedback mechanisms to maintain measurement precision despite using passive components. The controller monitors the synchronization between light source activation and camera capture, adjusting timing parameters as needed to ensure accurate ToF calculations. This feedback control compensates for any timing variations and maintains measurement accuracy.
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
This approach enables improved power consumption, data transmission, and data processing efficiencies, allowing vehicles to perform ToF calculations using existing components, expanding the effective field of view and providing depth information for enhanced autonomous and semi-autonomous driving capabilities.
Implementation Method 1
measures the elapsed time between light emission and the sensor receiving back the reflected light. Based on the elapsed time between sending out the light pulses and receiving the reflected light pulses, the distance between the ToF camera and a reflecting target can be calculated based on the speed of light
Data Source
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AI summary
A vehicle may perform time of flight (ToF) calculations or determinations using passive sensors (e.g., passive image sensors) with existing onboard vehicle light sources to generate depth data and a depth image of a scene surrounding the vehicle. For example, the vehicle may use an automotive camera (e.g., a passive sensor that does not emit light) and may pair the camera with one or more light sources on the vehicle to construct a ToF camera. To accomplish this construction of a ToF camera using existing automotive cameras and existing light sources, a controller of the vehicle synchronizes the passive automotive cameras to the onboard light sources. In some examples, the vehicle can enable a high dynamic range (HDR) for the ToF cameras by varying properties of the light emitted from the light sources.