CLR Analytics


Operational improvement

1. High Priority Chokepoint Evaluation

Considering the limitations in using conventional static modeling approach, Paramics simulation model was used as an evaluation tool for cost-benefit analysis for 12 chokepoint improvement projects proposed by Caltrans District 12.

2. Paramics Simulation Support for I5/SR55 Project Study

The project aims to develop a micro-simulation model for he I-5/SR-55 interchange using Paramics. The baseline network and alternatives system was evaluated in terms of corridor travel time, speed, vehicle miles traveled, vehicle hours traveled, flows, weaving, and queue lengths.

*Map picture source: Google

3.Benefit analysis of selected Orange County Freeway improvement projects

The purpose of this study is to analyze the benefits from four highway improvement projects using microscopic simulation. The microscopic simulation model used in this study is Paramics, which is a scalable, ITS-capable, high-performance microscopic traffic simulation package developed in Scotland. These four projects include:

  1. Re-stripe left shoulder of I-5 between SR-55 interchange and SR-22/SR-57 interchange to add second HOV (High Occupancy Vehicle) lane (network size: 7 miles).
  2. Re-stripe left shoulder on I-5 between Tustin Ranch Road and SR-133 interchange to add continuous auxiliary lane (network size: 5 miles).
  3. Extend existing HOV lane on SR-55 from the I-405 to Victoria in both directions (network size: 5 miles).
  4. Add one general purpose lane on I-5 between the Orange/San Diego County line and Camino Capistrano or extend HOV lane on I-5 between the Orange/San Diego County line and Camino Capistrano (network size: 8 miles).

Performance measures used in the analysis include vehicle miles traveled, vehicle hours traveled, mainline and HOV speed and throughput etc. The overall procedure to conduct this study is as follows:

  • Extract the study network from the existing Orange County simulation network
  • Extract OD table from the OCTAM model
  • OD estimation using Paramics OD Estimator based on mainline and ramp traffic counts.
  • Calibrate simulation model in order to reproduce real-world traffic congestion of the target network.
  • Identify appropriate measures of effectiveness (MOEs) and setup data collection in simulation.
  • Simulation runs for the existing scenario (called “before” scenario).
  • Prepare the improved scenario (called “after” scenario) by applying improvement strategies.
  • Simulation runs for the improved scenario.
  • Result comparison and benefit analysis.