5G Traffic Data Collection via Photogrammetric Camera Triangulation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current traffic data collection methods are unreliable, inaccurate, costly, and inefficient, lacking real-time capabilities, and existing technologies fail to precisely measure vehicle, pedestrian, and object positions, leading to suboptimal traffic control and management.
Innovation Solution
A photogrammetric and triangulation-based method using high-speed, georeferenced cameras to capture and process images of road intersections, providing real-time data on traffic flows, positions, and densities, accessible through cloud computing and 5G networks, enabling precise and automatic data collection and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual counting method is used to collect traffic data, then data accuracy is improved, but time consumption and cost increase significantly
Solution Approach 1:
The patent replaces manual mechanical counting with an automated optical detection system using cameras and image processing algorithms. The system captures images of vehicles and uses computer vision to automatically count and measure traffic flows, eliminating the need for manual field counting while significantly reducing time consumption and labor costs.
Solution Approach 2:
The patent creates visual copies of traffic scenes through camera imaging. By capturing images and processing them through image recognition algorithms, the system generates accurate traffic data without physically interacting with the traffic flow, thereby maintaining measurement precision while dramatically reducing the time required for data collection.
2Speed
If permanent detectors or sensors are installed along roads to collect traffic data, then real-time data collection is improved, but device complexity and installation difficulty increase
Solution Approach 1:
The patent uses standard cameras and general-purpose computing devices that can be deployed in multiple locations without specialized installation infrastructure. These universal devices can capture traffic data across different road types and conditions, reducing installation complexity while maintaining real-time data collection capabilities.
Solution Approach 2:
The patent introduces image processing algorithms and photogrammetric methods as intermediaries between the camera and the traffic data. This intermediary processing layer simplifies the hardware requirements by using software-based measurement techniques rather than complex sensor arrays, reducing overall system complexity while enabling real-time measurements.
3Area of stationary object
If data from mobile devices and GPS navigation systems are used, then data coverage is improved, but latency and privacy issues worsen
Solution Approach 1:
The patent segments the traffic data collection into localized camera stations distributed across the road network. Each camera captures data independently and processes it locally, eliminating the need for centralized collection from mobile devices. This segmentation reduces transmission latency by processing data at the source while maintaining broad coverage through multiple distributed measurement points.
4Ease of manufacture
If gray scale values of video pictures are used to estimate traffic conditions, then data processing simplicity is improved, but measurement precision deteriorates
Solution Approach 1:
The patent replaces simple gray scale analysis with advanced image processing and photogrammetric techniques. By using computer vision algorithms that analyze image geometry, perspective, and object recognition, the system achieves precise vehicle position measurement while maintaining automated processing simplicity through software-based solutions.
Solution Approach 2:
The patent transitions from one-dimensional gray scale intensity analysis to multi-dimensional image processing that considers spatial coordinates, perspective geometry, and object features. This dimensional enhancement enables precise measurement of vehicle positions, speeds, and trajectories while maintaining processing efficiency through algorithmic approaches.
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 method offers real-time, accurate, and cost-effective traffic data collection, allowing for dynamic traffic management, improved traffic light system optimization, and enhanced traffic studies, reducing manual counting and data processing costs while providing precise vehicle and object positioning.
Implementation Method 1
A method for collecting and measuring real-time traffic data and to make them accessible through the cloud computing comprising the following steps: a) choose a series of high speed Internet Protocol (IP) geo-referenced cameras, b) install at least two cameras at portions of the road, intersection or road section, for shooting pictures at a high speed frequency of vehicles, pedestrians, cyclists, animals, objects moving at said portion
Implementation Method 2
These pictures are transferred to a server by the 5G or any other fast and secure technology for processing. They can also be processed on site with the 'edge computing' approach. Pictures processing is carried out by photogrammetric, triangulation and picture recognition approaches in order to extract the position of each vehicle, pedestrian, cyclist or any object and identify its x, y, z coordinates
Implementation Method 3
Pictures processing is carried out by photogrammetric, triangulation and picture recognition approaches in order to extract the position of each vehicle, pedestrian, cyclist or any object and identify its x, y, z coordinates in a local or global referencing system
Data Source
AI summary
The present method permits to get real-time traffic data by the mean of pictures took by a series of georeferenced and synchronized high speed cameras installed on the portions of the road. These pictures and these data will be transferable by a secure means such as 5G or any other fast and secure technology on a server and accessible by cloud computing. Picture processing is carried out by photogrammetric, triangulation and picture recognition approaches in order to extract the position of each vehicle, pedestrian, cyclist or any object and identify its x, y, z coordinates in a local or global referencing system. This method permits to count the flow of traffic (vehicles, pedestrians, etc.) passing through these roads portions, to reproduce the real movements of vehicles, pedestrians and any object moving on a road, make simulations with a computer and intervene remotely in real-time to manage traffic.