Tools and Methodology for CorridorLevel Traffic Operations Planning

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Tools and Methodology for Corridor-Level Traffic
Operations Planning

• California Center for Innovative Transportation,
  November 2007

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About CCIT

• The California Center for Innovative
  Transportation (CCIT) accelerates the
  implementation of research results and the
  deployment of technical solutions by
  practitioners to enable a safer, cleaner and more
  efficient surface transportation system.

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CCITs Vision
CCIT envisions a world where
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Acknowledgments

• Hamed Benouar (CCIT)
• R. Jayakrishnan (UC Irvine)
• Steve Hague (Caltrans)
• Fred Dial (Caltrans)
• Henry Liu (UMN)

• Tarkek Hatata (SMG)
• Jeff Ban (CCIT)
• Erik Alm (CCIT)
• Lianyu Chu (CCIT)
• Jeff Ban (CCIT)

System Metrics Group Inc.
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A picture speaks a thousand words
Source Performance Measurement System (PeMS)
October 2001 Vphpl volume per lane per hour
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Outline

• The CCIT Corridor Management Project
• The Case for Micro-Simulation
• Selected Results and Outcomes
• Additional Takeaways

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The Corridor Management Modeling Project

• 3-year project 2004-2007
• Major Tool Microscopic Traffic Simulation
  (Paramics)
• Outcome
• 3 Corridor Studies Lessons Learned
• I-880 near San Francisco
• SR-41 in Fresno
• I-5 in Orange County
• A template for corridor traffic operations
  planning

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I-5 Corridor
30 miles of I-5 and nearby arterials 200
signals 70 ramp meters
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I-880 Corridor
30 miles of I-880, parallel arterials 190
signals 69 ramp meters
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SR-41 Corridor
16 miles of SR-41, 2 parallel arterials 90
signalized intersection 15 ramp metering
controllers
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Large Network/Corridor Applications

• Evaluate traffic management strategies and
  operational improvements
• Calibrate / optimize operational parameters of
  ITS strategies
• Develop / test new models, algorithms, control
  strategies
• Can even be used for project selection, including
  capital projects

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Overall Approach
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Corridor Studies as part of a Global Systems
Management Framework
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Outline

• The CCIT Corridor Management Project
• The Case for Micro-Simulation
• Selected Results and Outcomes
• Additional Takeaways

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Why Micro Simulation?

• Analysis of traffic flows
• Reasonable representation of queues and resulting
  traffic congestion
• Focus on bottlenecks
• Ability to analyze operational projects
• Integration of planning and operations
• Micro-simulation-based presentations/visuals
  effective tools for discussions with stakeholders

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MicroSim vs. Travel Demand Model
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Micro Simulation Validation Criteria
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Calibration Validation Issues

• The OD estimation step is most important in model
  validation
• The time resolution used in the OD estimation is
  crucial
• For instance, if observed data and speed plot
  have one-minute resolution, estimating OD tables
  at 5 min resolution may be OK, but certainly not
  more than 15 min
• Any OD estimation scheme that uses multiple time
  period static assignments within the iterative
  scheme is troublesome
• Also, some of the ad-hoc and supposedly pragmatic
  schemes such as adjusting the vehicle flows
  during the simulation to match the observed
  counts are very questionable
• The effect of the initial seed matrix could be
  significant in the OD estimation process
• Matching counts with hourly GEH values is
  questionable
• Maybe insufficient if the intent is to model with
  5-minute accuracy
• No reasonable current criteria on how speed-plots
  are to be matched
• What traffic condition (representative day) to
  calibrate against?
• Calibrating against averaged conditions is
  dangerous and may be impossible
• Travel time calibration Usually floating car
  data is expensive, and the variation of observed
  travel time on a section-basis is very high

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Calibration Observed day-to-day Variation
An analysis of two years of data on I-880 showed
ONE day without any accidents reported by the
California Highway Patrol. What is the
representative conditions to calibrate against?
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Calibration Average Data?
Averaged observed conditions may lead to
infeasible conditions (i.e., No OD matrix can
cause such traffic Forward growing queue etc!)
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Outline

• The CCIT Corridor Management Project
• The Case for Micro-Simulation
• Selected Results and Outcomes
• Additional Takeaways

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Speed contours from simulation
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SR-41Scenarios

• Planned Improvements

• Scenarios

• Add auxiliary lanes
• On-ramp widening
• Ramp metering systems
• Left-turn lanes at intersections
• Add new traffic signals
• Expand freeway from 6 to 8 lanes
• HOV lane (optional)

• The Short-term Improvements Alternative (year
  2005)
• The Medium-term Improvements Alternative (year
  2010)
• The Long-term Improvements Alternative (year
  2025), and
• The Long-term Improvement Alternative with HOV
  lanes (year 2025)

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SR-41 Scenarios (2)

• Average Network Speeds

• Average Freeway Speeds

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Corridor Systems Management Plan Template
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Outline

• The CCIT Corridor Management Project
• The Case for Micro-Simulation
• Selected Results and Outcomes
• Additional Takeaways

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I-880 Average Daily Delays
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Congestion by Cause
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Bottleneck Analysis
NORTHBOUND I-880 AVERAGE SPEED (mph) 10/1/04
10/31/04 (TUE-THUR)
Recurrent traffic congestion
bottleneck location
23rd Avenue
SR-238
length of congestion
Tennyson
DIRECTION OF TRAVEL
Fremont
period of congestion
Auto Mall Pkwy
5 AM
11 AM
5 PM
11 PM
12 AM
TIME OF DAY
SPEED COLORS (mph)
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30
35
40
45
50
55
60
65
70
75
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Bottleneck Variations
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Bottleneck Variations (B)
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Bottleneck Variations (C)
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Conclusions

• Micro-Simulation is EXPENSIVE and RISKY
• Considerable work involved
• Calibration and validation issues
• Priorities reversed modeling takes over
  objectives
• Remains the holy grail for operations planning
• A corridor-wide, system-level approach goes a
  long way
• Systematic data collection
• Root-cause analysis
• Project prioritization
• Tools are available
• Performance Measurement System (PeMS)
• CSMP Template associated Cookbook

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Tools and Process for Corridor-Level Traffic
Operations Planning
QA

• California Center for Innovative Transportation
• November 2007