Roadside Vision 3D Modeling for Vehicle Navigation Range
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Solution Overview
Problem
Current vehicle imaging systems require complex and costly installations in each vehicle to create a 3D model of the environment, which is inefficient and limits the range of detection due to the need to account for the vehicle's movement and identify both static and moving objects.
Innovation Solution
A stationary vision system with cameras and radar sensors installed along roads captures and processes image data to create a 3D model of the environment, which is then wirelessly transmitted to vehicles, allowing them to navigate using this pre-generated model and reducing the need for onboard object detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If complex onboard imaging systems are installed in each vehicle to create a 3D model of the environment, then the vehicle can independently identify both static and moving objects, but the system complexity and cost increase significantly
Solution Approach 1:
A stationary roadside imaging system acts as an intermediary between the environment and moving vehicles. This fixed system captures images of the roadway environment and transmits them to vehicles, eliminating the need for each vehicle to have complex onboard imaging systems while maintaining the ability to identify both static and moving objects
Solution Approach 2:
Instead of each vehicle creating its own 3D model of the environment, the stationary system creates a comprehensive environmental model that is then copied and transmitted to multiple vehicles. This allows vehicles to receive pre-processed environmental information without duplicating the complex imaging and processing hardware
2Measurement precision
If each vehicle creates its own 3D model of the environment, then the vehicle has complete control over its navigation data, but the detection range is limited by the vehicle's movement and sensor positioning
Solution Approach 1:
The roadway environment is divided into multiple zones, each monitored by stationary imaging systems positioned at different locations. This segmentation allows each fixed system to maintain a stable, high-quality view of its specific zone while collectively covering a much larger area than any single moving vehicle could monitor
3Speed
If vehicles continuously capture and process images to identify objects in real-time, then the navigation response is immediate, but the energy consumption and processing load increase
Solution Approach 1:
The stationary roadside systems perform image capture and environmental analysis in advance, before vehicles arrive at specific locations. By pre-processing the environmental data and identifying objects of interest, the system reduces the real-time processing burden on moving vehicles while maintaining fast navigation response
Solution Approach 2:
The stationary imaging systems serve themselves and multiple vehicles simultaneously by continuously monitoring the environment and making the processed data available to all passing vehicles. This eliminates the need for each vehicle to independently perform energy-intensive image capture and processing
Data Source
AI summary
A stationary vision system at a road along which vehicles travel includes an imaging sensor disposed at the road and having a field of view that encompasses a portion of the road. A wireless communication device is operable to wirelessly communicate with vehicles traveling along the road. A control includes a data processor operable to process image data captured by the image sensor. The control is operable to communicate with vehicles traveling along the road via the wireless communication device. The control, responsive to processing of image data captured by the imaging sensor, generates a three dimensional (3D) model of the portion of the road encompassed by the field of view of the imaging sensor. The control transmits the 3D model to vehicles traveling along the road.