Multi-Scale Road Network Traffic Reckoning With Weighted Indexes
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Solution Overview
Problem
Existing methods struggle to analyze and calculate traffic operation states in urban road networks across different sizes, structures, and scales, limiting their applicability and effectiveness in intelligent transportation systems.
Innovation Solution
A digital road network traffic state reckoning method that normalizes traffic operation state evaluation indexes using traffic weight coefficients, enabling unified evaluation across various spatial scales and structures by calculating traffic operation and delay indexes for lanes, sections, intersections, and zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional traffic operation state evaluation methods are used to calculate indexes for one evaluation object within different evaluation periods, then comparison can be performed to obtain evaluation conclusions, but the method is difficultly applicable to analysis and calculation on various evaluation objects in different sizes, with different structures, and at different scales in a road network
Solution Approach 1:
The patent applies parameter changes by introducing traffic weight coefficients that transform the evaluation approach. Instead of using fixed evaluation methods for different objects, the system dynamically adjusts parameters (traffic weight coefficients) based on object characteristics such as free-flow driving times, enabling a unified evaluation framework that adapts to various sizes, structures, and scales of road network objects
Solution Approach 2:
The patent implements universality by creating a unified evaluation index system that can be applied across multiple evaluation objects (lanes, sections, intersections, roads, sub-zones, and the entire road network) using the same fundamental methodology. The traffic weight coefficients serve as a universal mechanism that enables this single evaluation framework to function across diverse evaluation objects with different characteristics
2Measurement precision
If traffic operation state evaluation indexes are calculated for different evaluation objects at different scales, then comprehensive analysis can be performed, but normalization processing is needed to unify calculation methods across various sizes and structures
Solution Approach 1:
The patent uses parameter changes to achieve normalization by adjusting traffic weight coefficients based on free-flow driving times. This parameter adjustment enables precise evaluation across different scales while maintaining computational feasibility, as the coefficients normalize the data without requiring complex transformation processes
3Adaptability or versatility
If deepening development of intelligent transportation technology is pursued to enable analysis from macro-view road network to lane and single vehicle, then new requirements for research and judgment are met, but a unified digital road network traffic state reckoning method needs to be constructed
Solution Approach 1:
The patent applies preliminary action by calculating and storing traffic weight coefficients based on free-flow driving times before performing the actual evaluation. This preliminary computation of normalization factors enables subsequent multi-scale analysis to proceed efficiently without needing to reprocess raw data, thus preventing information loss while supporting comprehensive analysis across all scales from macro to micro levels
Data Source
AI summary
A digital road network traffic state reckoning method includes: S1, acquiring traffic weight coefficients of vehicles; S2, calculating traffic weight coefficients of evaluation objects in the road network at different spatial scales; S3, reckoning traffic operation indexes of the different evaluation objects in the road network; S4, reckoning delay time indexes and average delay times of the different evaluation objects in the road network; S5, reckoning indexes of the numbers of times of stopping and average numbers of times of stopping of the different evaluation objects in the road network; and S6, reckoning indexes of mileages of congested roads and proportions of mileages of heavily congested roads of the different evaluation objects in the road network by using the mileages of the heavily congested roads and the traffic weight coefficients of the vehicles.