Sound Sensor Array for ADAS Sensing Envelope
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Solution Overview
Problem
Existing Advanced Driver Assistance Systems (ADAS) face challenges due to the high costs, complexities, and limitations of standard camera, radar, lidar, and ultrasonic sensors, including hardware expenses, sensing limitations, and computational costs, which hinder effective detection and classification of hazardous road conditions, especially in adverse weather or obstructed environments.
Innovation Solution
Incorporating a sound sensor array to create a sound-enhanced sensing envelope around vehicles, which passively captures sound signals to augment the sensing capabilities, providing additional information and redundancy, and processing this data in real-time to enhance driver safety and autonomous driving decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If standard camera, radar, lidar, and ultrasonic sensors are used for ADAS, then detection and classification of hazardous road conditions is improved, but hardware costs and device complexity increase significantly
Solution Approach 1:
The patent combines multiple sensor types (camera, radar, ultrasonic, and sound sensors) into a unified sensor fusion system that processes data from all sources together. This merging approach allows the system to leverage the strengths of each sensor type while sharing processing infrastructure, thereby improving overall detection capability without proportionally increasing complexity.
Solution Approach 2:
The sensor system is designed to perform multiple functions using the same hardware infrastructure. The sensor fusion algorithm processes data for various ADAS functions including hazard detection, classification, and multiple driving assistance features simultaneously, reducing the need for dedicated hardware for each function.
2Measurement precision
If active sensors such as radar and lidar are used, then sensing range and capability are improved, but computational costs and processing complexity increase
Solution Approach 1:
The patent divides the sensing environment into different zones and assigns appropriate sensor types to each zone based on requirements. Sound sensors are used for long-range acoustic event detection, while other sensors handle closer-range detailed classification. This segmentation allows the system to use computationally intensive sensors only where necessary.
Solution Approach 2:
The sensor fusion algorithm acts as an intermediary that processes and integrates data from multiple sensor sources. It reconciles the different data formats and processing requirements of active sensors (radar, lidar) with passive sensors (sound, camera), reducing the overall computational burden by handling processing in a unified manner rather than separately for each sensor type.
3Reliability
If multiple orthogonal and complementary sensors are used for fully automated ADAS, then safety and redundancy are improved, but hardware costs and system complexity increase
Solution Approach 1:
The patent merges multiple sensor types into a unified system where each sensor provides complementary information. The sensor fusion architecture combines data from camera, radar, ultrasonic, and sound sensors to create a comprehensive view of the environment, achieving redundancy and safety improvements while sharing processing resources across all sensor inputs.
Solution Approach 2:
The system dynamically adjusts the weighting and processing parameters of different sensor inputs based on operating conditions. In certain scenarios, the system may rely more heavily on sound sensors for acoustic event detection, while in other scenarios it may prioritize visual or radar data. This dynamic parameter adjustment optimizes safety and redundancy while reducing processing complexity by focusing computational resources on the most relevant sensor data for each situation.
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
The sound-enhanced system improves detection and classification of hazardous conditions, reduces hardware and computational costs, and provides effective redundancy, especially in scenarios where other sensors fail, enhancing safety and operational efficiency in various weather and environmental conditions.
Implementation Method 1
sound sensor array which are deployed to generate a sound enhanced sensing envelope around the vehicle... passively capturing sound signal from the driving environment
Data Source
AI summary
A method, system, apparatus, and architecture are provided for generating a sound-enhanced sensing envelope. A plurality of sensors and one or more passive sound sensors of a vehicle are used to collect and process sensor data signals characterizing an exterior environment of the vehicle, thereby generating a sensing envelope around the vehicle using direct sensing data signals and a sound-enhanced sensing envelope around the vehicle using indirect sensing data signals. The sound-enhanced sensing envelope is used to evaluate advanced driver assistance system commands for the vehicle with respect to safety-related events identified by the indirect sensing data signals.