Intersection Signal Evaluation Using Real-Time Traffic Digital Twins
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Solution Overview
Problem
Existing traffic simulation methods lack accuracy in predicting real-time traffic conditions, leading to inefficiencies in addressing traffic jams due to the reliance on outdated statistical information and the need for excessive manpower monitoring.
Innovation Solution
Implementing a real-time traffic situation as a digital twin and metaverse system that uses real-time traffic data to generate accurate simulations, allowing for the formulation and comparison of evaluation indices to identify the most effective signal system for alleviating traffic jams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional traffic simulation uses traffic statistical information collected during a certain analysis period, then the system is simple to operate, but the accuracy of traffic situation information is low compared to actual traffic conditions that change from time to time
Solution Approach 1:
The patent implements dynamic traffic simulation by continuously updating the digital twin with real-time traffic data from multiple sources (cameras, sensors, GPS). The simulation model adapts to changing traffic conditions by processing live information flows and recalculating traffic patterns, allowing the system to reflect actual dynamic traffic situations rather than relying on static historical statistics
Solution Approach 2:
The patent creates a digital twin copy of the physical traffic system that mirrors real-world intersections, vehicles, and traffic flows. This virtual replica is updated in real-time with actual traffic data, enabling accurate simulation and analysis without requiring complex physical monitoring infrastructure at every location
2Reliability
If a user continuously monitors traffic situation at the actual intersection, then the user can recognize traffic jams, but a plurality of vehicles move from time to time which inevitably causes traffic jams and deploying large number of manpower is a serious waste
Solution Approach 1:
The patent implements an automated monitoring system where the digital twin continuously tracks traffic conditions without human intervention. The system self-updates with real-time data from sensors and cameras, automatically detects traffic jams through algorithmic analysis, and generates alerts only when necessary, eliminating the need for continuous manual monitoring while maintaining high reliability
Solution Approach 2:
The patent establishes a feedback loop where traffic data from the physical world is continuously fed into the digital twin, which processes the information and provides feedback about traffic conditions. This automated feedback mechanism replaces manual monitoring by systematically analyzing traffic flows and identifying congestion patterns without requiring human observers
3Ease of operation
If the degree of traffic jam is formulated by finding indices that cause the traffic jam, then the traffic jam can be systematically alleviated by changing the indices, but it requires calculating and comparing multiple evaluation indices with various parameters to find the most effective signal system
Solution Approach 1:
The patent segments the complex traffic optimization problem into multiple evaluation indices, each measuring different aspects of traffic performance (congestion level, signal timing efficiency, vehicle throughput). By dividing the overall problem into measurable components, the system can systematically analyze and optimize each aspect separately while maintaining overall traffic flow management
Solution Approach 2:
The patent systematically varies parameters of evaluation indices (such as signal timing durations, priority levels for different traffic directions, speed limits) to identify optimal configurations. The digital twin simulates different parameter settings and compares their effects on traffic flow, enabling data-driven optimization of signal systems without requiring complex manual analysis
Data Source
AI summary
A method for calculating and comparing evaluation indices for a signal system of an intersection includes: a traffic statistical information generation step of receiving image information in real time through cameras to derive traffic object information including traffic volume for each driving direction and traffic volume for each lane on a corresponding road at a preset first cycle, and to generate traffic statistical information including the traffic object information and intersection environment information; a digital twin generation step of inputting the traffic statistical information to a simulator, and implementing a traffic situation of the intersection as a graphical digital twin; and a composite congestion index derivation step of deriving a composite congestion index from each of an actual digital twin and a virtual digital twin, in which the evaluation indices are derived based on a congestion time of a predetermined number of vehicles at the corresponding intersection.