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Case12B Monte Carlo Based Traffic Simulation in Baton Rouge

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Chapter 12 Monte Carlo Method and Applications in Urban Population and Traffic Simulations

Monte Carlo simulation provides a powerful computational framework for spatial analysis and has become increasingly popular with rising computing power. Some applications include data disaggregation, designing a statistical signifiance test and modeling individual behaviors. This chapter demonstrates the value of Monte Carlo technique in spatial analysis.

One case study uses the Monte Carlo method to simulate individual resident loca?tions by using the census and land use inventory data, and then aggregates population back to area units of any scale in any shape. Another case study demonstrates the value of applying the Monte Carlo technique in simulating urban traffic flows. The former generates individual points, and the latter derives linkages between points.
Both can benefit analysis that is prone to the scale and zonal effects. In case study 12A, the technique is applied to examine the role of such effects on urban population density functions. In case study 12B, one may use such a technique of simulating individual trips to improve accuracy in travel distance estimate (e.g., reducing uncer?tainty in measuring wasteful commuting based on area units).

CASE STUDY 12B: MONTE CARLO BASED TRAFFIC SIMULATION IN BATON ROUGE, LOUISIANA

This case study is developed to illustrate the application of Monte Carlo simulation in traffic simulation. The study focuses on East Baton Rouge Parish (EBRP) of Louisiana, the urban core of Baton Rouge MSA, but extends to include its eight neighboring parishes in traffic simulation in order to account for internal-external, external-internal, and through traffic.



Computational Methods and GIS Applications in Social Science - Lab Manual
Lingbo Liu, Fahui Wang

URL: GitHub for Geospatial Analytics https://github.com/spatial-data-lab/knime-geospatial-extension
URL: GitHub for Workbook Issue Report https://github.com/UrbanGISer/CGA-KNIME-Workbook/tree/main

Part 1Inter-zonal trip estimation Part 2Simualtion of origin and destination points Part 3Tripdistribution Part 4Tripassignmentand modelvalidation Revisions from the KNIME Lab Manual,Computational Methods and GIS Applications in Social Science- Lab Manual:When using the "Create Random Points" node, there is no need to specify the ID column. Ensure the "Replace" option is selected for geometry. Node 1Node 2Node 3Node 4Node 5Node 6Node 7Node 8Node 9Node 10Node 11Node 12Node 13Node 14Node 15Node 16Node 17Node 18Node 19Node 20Node 21Node 22Node 23Node 24Node 27Node 25Node 26Node 28Node 29Node 30Node 31Node 32Node 33Node 34Node 35Node 36 GeoFile Reader GeoFile Reader Road NetworkDistance Matrix Math Formula Joiner Joiner Math Formula Math Formula Python Script Row Filter Python Script GroupBy GroupBy Joiner Joiner Create RandomPoints Multipart ToSinglepart Create RandomPoints Multipart ToSinglepart Column Filter Column Appender Sorter Column Appender GeoFile Reader Python Script Math Formula ParallelChunk Start Parallel Chunk End GroupBy Joiner Missing Value GeoFile Reader Nearest Join Linear RegressionLearner Kepler.gl Geoview Timer Info Part 1Inter-zonal trip estimation Part 2Simualtion of origin and destination points Part 3Tripdistribution Part 4Tripassignmentand modelvalidation Revisions from the KNIME Lab Manual,Computational Methods and GIS Applications in Social Science- Lab Manual:When using the "Create Random Points" node, there is no need to specify the ID column. Ensure the "Replace" option is selected for geometry. Node 1Node 2Node 3Node 4Node 5Node 6Node 7Node 8Node 9Node 10Node 11Node 12Node 13Node 14Node 15Node 16Node 17Node 18Node 19Node 20Node 21Node 22Node 23Node 24Node 27Node 25Node 26Node 28Node 29Node 30Node 31Node 32Node 33Node 34Node 35Node 36 GeoFile Reader GeoFile Reader Road NetworkDistance Matrix Math Formula Joiner Joiner Math Formula Math Formula Python Script Row Filter Python Script GroupBy GroupBy Joiner Joiner Create RandomPoints Multipart ToSinglepart Create RandomPoints Multipart ToSinglepart Column Filter Column Appender Sorter Column Appender GeoFile Reader Python Script Math Formula ParallelChunk Start Parallel Chunk End GroupBy Joiner Missing Value GeoFile Reader Nearest Join Linear RegressionLearner Kepler.gl Geoview Timer Info

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Created by: Piant
Created at: 2023-03-31
On NodePit since: 2023-10-06
Last update: 2024-11-21
Created with KNIME version: v5.1.1
Tags: Geospatial AnalyticsSpatial Data LabHarvard CGA

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