Traffic-Flow Simulation Parameter Matching for Congestion Prediction
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Solution Overview
Problem
Existing traffic congestion prediction methods, such as those relying on expert knowledge and traffic-flow simulations, fail to accurately reproduce real-world traffic conditions due to variations in vehicle velocities and behaviors, leading to poor accuracy in predicting future congestion.
Innovation Solution
An information processing apparatus and method that utilizes a traffic-flow theoretical model to set parameter sets, run simulations, and determine the most similar simulation data to actual traffic-flow measurements, enabling high-accuracy traffic-flow prediction by selecting parameter sets that accurately reproduce current traffic conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traffic-flow simulation is performed under the assumption that all vehicles travel at the measured mean velocity, then the simulation can be simplified and executed efficiently, but the degree of reproduction of real traffic conditions deteriorates due to ignoring velocity differences and various vehicle behaviors
Solution Approach 1:
The patent changes the velocity parameter from a single mean value to multiple individual velocity values for each vehicle. The simulation assigns different velocities to different vehicles based on their positions and traffic conditions, allowing the model to reproduce realistic velocity distributions and vehicle behaviors while maintaining computational feasibility through systematic parameter assignment rules.
2Reliability
If expert knowledge and experience are used to predict traffic congestion, then the prediction can incorporate human judgment and pattern recognition, but the training time and experience requirements increase significantly
Solution Approach 1:
The patent replaces the mechanical system of human expert judgment with an automated information processing system that uses traffic-flow simulation and objective comparison methods. The system automatically analyzes traffic data, runs simulations with different parameters, compares results with actual measurements, and determines optimal predictions without requiring human experts to accumulate years of experience, thereby eliminating training time while maintaining prediction quality.
3Measurement precision
If multiple parameter sets are tested through traffic-flow simulation to find the one that best reproduces actual traffic conditions, then the accuracy of traffic-flow prediction improves, but the computational time and complexity increase
Solution Approach 1:
The patent applies partial action by testing a limited but sufficient number of parameter sets rather than exhaustively testing all possible combinations. The system identifies key parameters that have the most significant impact on traffic-flow reproduction and focuses simulation efforts on varying these parameters within reasonable ranges, achieving accurate reproduction without the computational burden of complete parameter space exploration.
Solution Approach 2:
The patent implements feedback by comparing simulation results with actual traffic-flow measurements and using this comparison to select and refine parameter sets. The system continuously adjusts parameters based on how well the simulation reproduces observed conditions, creating a closed-loop optimization process that efficiently converges on accurate parameter values without requiring excessive computational resources.
Data Source
AI summary
Disclosed is an information processing apparatus including a setting unit for setting parameter sets of a traffic-flow theoretical model to be used in traffic-flow simulation that applies the traffic-flow theoretical model, a simulation unit for running the traffic-flow simulation for each of the parameter sets, and a determining unit for selecting traffic-flow simulation data, similar to traffic-flow measurement data actually measured, from the traffic-flow simulation data as a result of the traffic-flow simulation, and determining a parameter set corresponding to the selected similar traffic-flow simulation data for a parameter set to be used in traffic-flow prediction.