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1
Intro
2
MOTIVATION AND BACKGROUND
3
PROBLEM FORMULATION
4
PROPOSED WORKFLOW
5
EDGE ASSIGNMENT ALGORITHM
6
IMPLEMENTATION
7
EXPERIMENTAL STUDY
8
CONCLUSION
Description:
Learn about an innovative approach to traffic simulation optimization in this 19-minute technical presentation that explores origin-destination (OD) matrix reduction techniques for urban mobility planning. Discover how researchers tackled the challenge of inferring travel demand patterns for Helsinki's core area using data from a larger extended region. Follow the development of an edge-based origin-destination assignment algorithm that maintains traffic flow accuracy while significantly reducing simulation time from 6 hours to 20 minutes. Examine the validation process using DigiTraffic data from Helsinki's traffic counting stations, which demonstrated strong accuracy with a 34% average MAPE between observed and simulated traffic counts. Explore the complete workflow from motivation and problem formulation through implementation and experimental results, gaining practical insights into optimizing large-scale urban traffic simulations using the SUMO (Simulation of Urban MObility) tool.

Simulation-Based Origin-Destination Matrix Reduction: A Case Study of Helsinki City Area

Eclipse Foundation
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