A PERSPECTIVE ON APPLICATION OF A PAIR OF PLANNING AND MICRO SIMULATION MODELS: EXPERIENCE FROM I-405 CORRIDOR STUDY PROGRAM

Murli K. Adury Youssef Dehghani Cathy Strombom Parsons Brinckerhoff Quade & Douglas, Inc.

Seattle, WA, USA

Project Context

 I-405 Corridor Program: » I-405 was built in 70s to alleviate congestion along I-5 » Experiencing unexpectedly high high levels of congestion rate of growth from high tech sector (e.g., Microsoft) within I-405 corridor – resulting in » Undertaking comprehensive alternatives analysis

Project Area Map

Why Micro Simulation?

 Be able to evaluate realty checks on capacity enhancement elements of the preferred alternative – balancing capacity needs on arterials vs. I-405 thru better diversion mechanism   Be able to refine enhancement and/or modify capacity elements of the preferred alternative Be able to highlight potential deficiencies e.g., lid concept thru downtown Bellevue –

Why Integration?

 WSDOT undertook a rigorous evaluation the existing micro simulation software programs of  Integration most suited because of its capabilities for: » Micro simulation analysis at corridor level » Equilibrium route diversion analysis » State-of-the-art methodology analysis for traffic simulation » Being able to interface with the existing regional planning model databases

Model Development Process

 Network preparation/calibration  Data collection » » » Details of network geometry Signal timings Traffic counts  Trip table development  Model validation analysis  Model application

Network Development

 Included only: » » I-405 & major parallel arterials (3000 links) Major intersections (100 signalized intersections)  Initially used default parameters & refined further during validation process  Most difficult tasks: » » Developing a network to fit INTEGRATION limits Data input for microsimulation – lane geometry, signal data, turn pockets, physical attributes of roadway system

Trip Table Development

 Regional model produced PM peak (hour) vehicle trip tables for HOVs and Non-HOVs  Post regional modeling procedure: » Direction peak-hour base year counts were seeded on designated links on I-405 and arterials » Matrix adjustment macro DEMADJ.MAC

developed Heinz Spiess was used to update original matrix » Resulting O-D matrix was imported into the Integration model environment

Model Validation Analysis

 Initial analysis indicated that study area network needed to be streamlined : » » Secondary arterials were removed Secondary signalized intersections were also removed   Hourly counts exhibited wide variations weekdays and months: » Overall average and max/min limits were established across Attempts were made to “ optimize ” signal timing coordination

Model Validation Analysis - Continued -

 Prepared summary system-wide measure: » » » » Peak-hour demand input as % of total demand % vehicles reached destinations VMTs/VHTs Total delays & stop delays  Prepared link-level summaries: » » » Total flow Travel time Queue length

6000 5000 4000 3000 2000 1000 0 0

Model Validation Analysis - Continued -

Model Flow Rate vs Average Peak Hour Count (I-405 NB between SR 167 and SR 169)

90 Min Count Max Count Avg Count Model 15 30 45 60 75

Simulation Time (Time = 0 to 90 minutes)

Model Validation Analysis - Continued -

 Comparative analysis of queue build-up against recurring bottleneck areas posted on the WSDOT website  Performed additional network refinement accordingly  Accomplished reasonable base year validation results

Model Validation Analysis - Continued -

Model Application

 In I-405 EMME/2 Model » Developed 2020 network for the preferred alternative » » Prepared 2020 Travel Forecasts Developed 2020 peak-hour trip table – Prepared base year to 2020 zone-to-zone growth rates – Applied implied zone-to-zone growth rate to the base year adjusted peak-hour trip table

Model Application - Continued -

 Provided insights analysis process into the alternatives  Highlighted initially proposed improvement plan/conceptual design deficiencies within the project corridor  Identified potential bottleneck areas  Integration modeling achieved purpose its

Lessons Learned

 Allow adequate time to: » Define objectives for why needing to do micro simulation and for what purpose » Identify appropriate software its limits accordingly program and  Identify study area carefully for: » Boundaries » Network details (no. of links & intersections)

Lessons Learned - Continued

 Assess potential interface with other tools (e.g., regional model databases, network editing, etc.)  Trip matrices need to go through an adjustment process reflecting actual counts  Assess data needs carefully  Micro simulation consuming model is data hungry & time