Case12B Monte Carlo Based Traffic Simulation in Baton Rouge

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

External resources

• GitHub for Workbook Issue Report
• GitHub for Geospatial Analytics