Dashboard Camera VRU Detection for Low-Complexity Collision Prediction
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Solution Overview
Problem
Many vehicles lack environment monitoring systems to detect vulnerable road users (VRUs) due to high complexity and cost, making it infeasible to integrate complex sensor systems, which compromises safety and efficiency in preventing collisions with pedestrians and cyclists.
Innovation Solution
A vehicle environment monitoring device that uses a dashboard camera system to capture video data, process it to detect and track VRUs, predict potential collisions, and alert drivers or management systems, reducing the complexity and cost compared to traditional systems while maintaining accuracy and improving scalability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex sensor systems (RADAR, LIDAR) are integrated to detect VRUs, then detection reliability is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent uses a dashboard camera to capture video frames that serve as a visual copy of the road environment, replacing the need for complex physical sensor systems. The computer vision model processes this visual copy to detect VRUs, achieving reliable detection through image analysis rather than expensive sensor arrays.
Solution Approach 2:
The patent replaces mechanical sensor systems (RADAR, LIDAR) with a software-based computer vision approach. Instead of using physical sensors to detect VRUs, the system uses a trained machine learning model to analyze video frames and identify vulnerable road users, substituting hardware complexity with computational intelligence.
2Measurement precision
If complex sensor systems are integrated to detect VRUs, then detection precision is improved, but manufacturing cost increases
Solution Approach 1:
The patent employs a dashboard camera, a relatively inexpensive and widely available component, to capture video data for VRU detection. This approach replaces expensive specialized sensors with a cost-effective consumer-grade camera, significantly reducing manufacturing costs while maintaining detection capability.
Solution Approach 2:
The patent changes the detection parameter from physical sensor measurements (radio waves, light pulses) to visual image analysis. By transforming the detection task into image processing, the system achieves precise VRU detection using standard camera technology rather than expensive specialized sensors.
3Measurement precision
If video data is processed to detect and track VRUs, then detection accuracy is improved, but computing resource consumption increases
Solution Approach 1:
The patent performs preliminary actions by capturing and storing video frames at regular intervals before full processing is needed. The system pre-processes frames to identify potential VRUs, so when detection is required, the computational workload has already been partially reduced, minimizing real-time energy consumption.
Solution Approach 2:
The patent applies partial processing by focusing computational resources only on frames where VRUs are detected or suspected. Instead of processing every frame at full resolution, the system selectively intensifies analysis only when necessary, reducing overall computing resource consumption while maintaining detection accuracy.
Data Source
AI summary
In some implementations, a device may receive video data associated with video frames that depict an environment of a vehicle. The device may identify an object depicted in the video frames, wherein an object detection model indicates bounding boxes associated with the object. The device may determine, based on the bounding boxes, a configuration of the bounding boxes within the video frames. The device may determine, based on the configuration of the bounding boxes, that the object is a vulnerable road user (VRU) that is in the environment. The device may determine a trajectory of the VRU based on a change in the configuration between video frames of a set of the video frames. The device may determine, based on the trajectory, a probability of a collision between the VRU and the vehicle. The device may perform, based on the probability, an action associated with the vehicle.