Behavior-Model Traffic Simulation for Dynamic Route Selection
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Solution Overview
Problem
Existing traffic simulation methods fail to accurately account for dynamic states of transportation modes, such as congestion degrees, which affects the selection of travel routes by individuals.
Innovation Solution
A computer program that simulates traffic using a behavior model to predict route selection based on features indicating transportation mode states, allowing for the simulation of multiple travel routes and updating these features based on movement results to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional traffic simulation methods are used, then the simulation process is simple, but the simulation accuracy is insufficient because dynamic states of transportation modes are not properly accounted for
Solution Approach 1:
The patent applies dynamics by making the transportation mode states dynamic rather than static. The behavior model continuously updates features indicating transportation mode states (such as congestion degrees) based on simulated movement results, allowing the simulation to reflect real-time dynamic conditions that affect route selection, thereby improving simulation accuracy without requiring overly complex infrastructure
Solution Approach 2:
The patent implements feedback mechanisms where the behavior model uses updated features from movement results to continuously refine route selection predictions. The simulation process feeds back the actual movement outcomes into the behavior model, which then adjusts the features indicating transportation mode states for subsequent iterations, creating a closed-loop system that progressively improves accuracy
2Measurement precision
If multiple travel routes are simulated with behavior model predictions, then the simulation accuracy improves, but the computational complexity increases
Solution Approach 1:
The patent changes parameters by using a behavior model that predicts route selection based on features indicating transportation mode states rather than evaluating all possible routes exhaustively. The behavior model uses parameters such as congestion degrees and other state features to probabilistically determine route selections, reducing computational power requirements while maintaining prediction accuracy
Solution Approach 2:
The patent applies partial action by having the behavior model predict and select only the most relevant travel routes based on current transportation mode states, rather than simulating all possible routes equally. The system focuses computational resources on predicting the actual selected route and its alternatives, rather than exhaustively analyzing every possible path
Data Source
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AI summary
A computer searches for a plurality of travel routes along which a person moves from a departure point to a destination using one or more transportation modes among a plurality of transportation modes, the one or more transportation modes being different from each other among the plurality of travel routes, predicts a first travel route to be selected by the person from the plurality of travel routes by using a behavior model for predicting a selection behavior based on features indicating states of the plurality of transportation modes, simulates a first movement of the person along a time axis using the first travel route, and updates the features using a result of the first movement.