Transportation Border Working Group Ottawa: November 7, 2012

Pembina - Emerson Port of Entry Study David Lettner: Manitoba Infrastructure and Transportation

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Project Steering Committee (PSC)

The Pembina - Emerson Study Partnership

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Manitoba Infrastructure and Transportation (MIT) David Lettner, Project Manager and PSC Chair Walter Burdz (P. Eng.), Executive Director Highway Engineering Brett Wareham (P. Eng.), Director of Regional Operations (Region 1)

North Dakota Department of Transportation (NDDOT) Jack Olson, Assistant Division Director, Planning and Programming Les Noehre (P.E.), Grand Forks District Engineer

Transport Canada (TC) Susan Zacharias, Policy Coordinator (Prairie and Northern Region)

Canada Border Services Agency (CBSA) Blair Downey, Chief of Operations (Southern Manitoba District)

Customs and Border Protection (CBP) Jason Schmelz, Assistant Port Director (Pembina)

General Services Administration (GSA) Bryan Sayler, Property Manger (North Dakota Field Ofice)

Acknowledgements: Project Steering Committee

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TBWG: Bi-national institutional support

Policy context and alignment of planning strategies Sharing of best practices / experiences Technology applications, studies and data sources Peer network (agency subject matter experts) and agency perspectives Timely exposure to emerging funding opportunities TBWG website (past plenary session archives)

NDDOT: Previous regional level initiatives

FHWA Coordinated Border Infrastructure Grant application (1999) NDDOT lead agency (with Manitoba / Saskatchewan participation + funding) Initial regional level work / study on border infrastructure coordination issues

Acknowledgements

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Project Background and Context Existing Situation / Historical Activity

Planning Principles / Best Practices

Key Study Methodologies

Proposed Port Concept / Measures of Effectiveness

Presentation Overview

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2009 Initial inter-agency meeting (precursor to project steering committee - PSC) GBCF Application to TC

2010 GBCF Contribution Agreement (CA) signed between MIT and TC MOU and CA signed between MIT and NDDOT

2011 PSC formed ESP registry / TOR finalized / RFP process / ESP retained (study start date Oct 5)

2012 Phase 1-Concept Planning completed (broad agency consensus for concept) Phase 2-Functional Design mobilized (MIT: transportation infrastructure)

Generalized Project Milestones (2009-2012)

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40+ stakeholders

Phase 1-Conceptual Planning (Project Governance)

30+ agency specialists

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Primary Study Objectives: At a conceptual level of detail: to prepare a long-range concept plan

for the P-E POE that identifies the general level of transportation infrastructure and border services facility improvements required to meet anticipated demand to the year 2035.

To gain consensus on the recommended long-range concept plan for the P-E POE from all transportation agency funding partners (TC, MIT, NDDOT) and bi-national border service agencies (CBSA, CBP, GSA)

To develop and implement a long-term collaborative mechanism for maintaining stewardship for the P-E POE concept plan and working collaboratively toward implementation of the recommended concept

Phase 1-Conceptual Planning (Study Objectives)

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Generalized Project Delivery Process

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Policy Context (Canada)

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Policy Context (United States)

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Historical Activity (2-way truck-based trade)

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Historical Activity (Vehicle Movements: 2005-2011)

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Existing Situation: (study area)

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Existing Situation (functional flows + operational analysis)

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Existing Situation (SB improvements 2011-2012)

SB improvements:$1.7M $525K for VMS $1.2M for pavements

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Optimize Public Investments: CBP 1997 $14.5M CBSA 1999 $10.5M MIT 1996 / 2012 $7.0M + Utilize appropriate methodologies to justify future transportation / port improvements

and expenditures (demand-capacity analysis / benefit-cost)

Hierarchical Land Assignment Strategies: Essential transportation and border service functions take priority over non-essential

functions Locate non-essential port functions further from Canada-USA border wherever possible

(ex: duty free operations)

Operational and Phasing Considerations: Integrate and optimize advance notification, channelization and lane assignment

strategies to facilitate vehicle throughput Phasing considerations related to impact on businesses, project delivery implications for

public agencies (6-10 year project delivery cycle)

Planning Principles | Best Practices

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Best Practices (TDM / TSM thinking)

Transportation Demand Management (TDM) TDM strategies are intended to reduce demand on facilities and

infrastructure during peak periods by modifying travel behaviour Providing access to delay and congestion data for port users Using ITS applications like BIFA to provide real time traveller information Promoting uptake of trusted traveller / trader programs (NEXUS / FAST)

Transportation System Management (TSM) TSM strategies are intended to optimize the use of existing or

proposed facilities and infrastructure through better management and operational practices Data collection Advance notification, channelization, lane assignment strategies Optimizing flexibility & cross-over functions of PIL infrastructure

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Vehicle Demand Forecasts Hourly arrivals by vehicle category (autos, trucks) Hourly data: Synchro-Sim Traffic and undertake LOS analysis

Synchro-Sim Traffic Simulation Model 30th highest hour: establish design parameters (ex: # PIL booths) Establish trigger points for phasing in improvements

Level of Service (LOS) Framework Sensitivity analysis to verify and refine phasing of improvements Capability to assess various processing / infrastructure scenarios Verification of Synchro-Sim queue lengths

Key Study Methodologies (Methodology Integration)

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Vehicle Forecasts

LOSAnalysis

Synchro Sim

Hourly traffic volumes to 2035

Sensitivity analysis to assess various processing / infrastructure scenarios

30th highest hour / 99th percentile to establish facility design requirements

Methodology Integration | Best Practices

LOS and Synchro-Sim corroboration / cross-validation

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Objective: To develop custom algorithms which take annual forecasts (to 2035) by vehicle type and distribute this data on an hourly and daily basis to uncover peaking characteristics and patterns for the two primary vehicle classes (trucks / autos)

Needs: Historical hourly data by vehicle type (trucks / auto) needed to develop algorithms which replicated historical patterns. CBSA and CBP provided excellent historical data (hourly volumes by vehicle type) over a 7-10 year period for the P-E POE

Benefits: Ability to assess daily and hourly peaking impacts on port facilities and determine requirements for key infrastructure components such as PIL booths with greater degree of statistical confidence (+ / - .5% standard deviation)

Rationale for Forecasting Approach

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Vehicle Forecasts: Compilation of three vehicle categories

Buses (ex: 2011: 2,250 vehicles / 0.2% of total traffic) Trend line analysis (exponential trend line decrease from 1993-2010)

Autos (ex: 2011: 642,348 vehicles / 62.3% of total traffic) Trend line analysis (linear trend line increase of 3.5% from 1993-2010) Custom algorithms developed to distribute annual forecast data for:

Every hour of every day (to 2035) based on custom expansion factors

Trucks (ex: 2011: 385,725 vehicles / 37.5% of total traffic) NFFI data for top 30 commodity groups converted into truck movements Custom algorithms developed to distribute annual forecast data for:

Every hour of every day (to 2035) based on custom expansion factors FHWA vehicle classes / Gross vehicle weight / volume route splits (I-29 and I-94) / traffic splits (SB / NB) Percentage of empty backhauls

Forecast Methodology & Demand Scenarios

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Forecasts: Buses

0

500

1,000

1,500

2,000

2,500

3,000

1990 2000 2010 2020 2030 2040

SB Buses

BUSES Proxy

0

500

1,000

1,500

2,000

2,500

3,000

1990 2000 2010 2020 2030 2040

NB Buses

BUSES Proxy

•NB and SB bus traffic exhibited an exponentially decreasing trend-line between 1993 and 2010

• From 2012 to 2035 a “bottom” equilibrium value was established that reflected 40% of mid-1990 values

•As buses were such a small amount of the traffic stream (< 0.2%), and in declining numbers, bus traffic was removed from the forecast projections

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Forecasts: Autos

0200,000400,000600,000800,000

1,000,0001,200,0001,400,0001,600,0001,800,0002,000,000

Annual Autos Bi-Directional

• From 1993 to 2010, auto traffic increased by 3.5% for both NB and SB directions

• A 3.5% annual growth rate (Med) was applied to autos for the 2012 to 2035 forecast period

Medium

High +1%

Low -1%

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Forecasts: Trucks

Annual Trucks Bi-Directional

• NFFI commodity data used to establish truck forecasts from 2012-2025

• NFFI data was extrapolated for the 2025-2035 forecast period

Medium

High +1%

Low -1%

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0

2000

4000

6000

8000

10000

12000

14000

0.0

2000.0

4000.0

6000.0

8000.0

10000.0

12000.0

14000.0

0 20 40 60 80 100 120

Traffic Volume

Forecast Period

Annual Growth Forecast Trendline

Algorithms were developed to translate annual forecasts into daily and hourly forecasts to more accurately capture peaking patterns and characteristics necessary to assess facility and infrastructure requirements

Capturing Forecast Peaks

The Rationale Behind Developing Algorithms

9 million data pointswere required to obtain hourly arrival rates to the year 2035

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Vehicle Forecasts (2012-2035)

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Historical and Forecast Trade Value

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Synchro-Sim (SB volume / capacity analysis)

Calc for Max hourly theoretical PIL capacity:(3 different auto dwell time scenarios)

120 sec PIL dwell time = 30 veh /hr / PIL(30 veh x 6 PILs = 180 veh / hr)

90 sec PIL dwell time = 40 veh / hr / PIL(40 veh x 6 PILS = 240 veh / hr)

60 sec PIL dwell time = 60 veh / hr / PIL(60 veh x 6 PILS = 360 veh / hr)

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Synchro-Sim (NB volume / capacity analysis)

Calc for Max hourly theoretical PIL capacity: (3 different auto dwell time scenarios)

120 sec PIL dwell time = 30 veh /hr / PIL(30 veh x 4 PILS = 120 veh / hr)

90 sec PIL dwell time = 40 veh / hr / PIL(40 veh x 4 PILS = 160 veh / hr)

60 sec PIL dwell time = 60 veh / hr / PIL60 veh x 4 PILS = 240 veh / hr)

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Synchro-Sim Outputs (PIL requirements analysis)

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Frequency: Number of occurrences Magnitude: Delay to individual vehicles Duration: length of delay period

Day and Date: Holidays (day of the week or fixed date) Vehicle Type: Truck / Auto peaking characteristics

Delay Factor Analysis (Synchro output + LOS framework)

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Level of Service (LOS) Framework

LOS Framework Criteria

Magnitude of delay:Delay to individual vehicles

Duration of delay:Delay period for queued vehicles

Volume / Capacity Ratio:Ratio of hourly arrivals to max. theoretical processing capacity

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Develop custom algorithms that calculate:

Average wait times per vehicle for each forecast hour based on the “state” of demand (unsaturated, build-up, saturated, dissipation)

Wait times converted to LOS categories (A to F) based on custom service time parameters stipulated in LOS framework

Total number of hours in each LOS category (A, B, C, D, E, F) aggregated by forecast year

Approach to Populating LOS Output Tables

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Graphical Representation of LOS Algorithms

TYPICAL PEAKING SCENARIOState 1: Unsaturated – No delayState 2: Build-up – Arrivals exceed processing capacityState 3: Saturated – Arrivals and / or queue exceed processing capacityState 4: Dissipation – Arrivals and queue less than processing capacity

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Flexibility of custom algorithms that calculate LOS:

The algorithms (once developed) have unlimited simulation capability to test infrastructure and service level parameters based on the LOS framework

PIL dwell time: Impact of processing protocols / technologies Number of PILS: Impact of built infrastructure / staffing levels

This is the distinct advantage of the LOS framework over models like Synchro-Sim which would require simulation runs for every hour in a year (8,760 hourly runs) to obtain the same result for any given forecast year

Approach to Interpreting LOS Output Tables

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LOS Applications: SB (PIL’s: dwell time / # / staffing)

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LOS Applications: NB (PIL’s: dwell time / # / staffing)

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LOS Analysis: Southbound (SB)

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LOS Analysis: Northbound (NB)

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Conceptual Elements

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Proposed Concept (overall)

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Proposed Concept (northern component detail)

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Proposed Concept (port area detail)

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Southbound and Northbound Utilize PTH 75 and I-29 for passenger vehicle traffic approach to PIL plaza Construct 2 new dedicated commercial lanes (FAST / non-FAST)

Southbound Convert all CBP commercial PILS to high / low booths New secondary commercial inspection facility

Northbound New CBSA commercial plaza (4 PILS, VACIS, secondary) New commercial service road connection to PTH 75

Access Management New Emerson Access Road at PTH 75 / PR 243 junction

Key Southbound and Northbound Elements

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Preliminary Order of Magnitude Cost Estimates $47.4M 24-1 benefit-cost ratio for full concept build-out

Canada (NB and SB) $3M: MIT (transportation infrastructure) $30.5M: CBSA (border service facilities)

United States (NB and SB) $1.7M: NDDOT ( transportation infrastructure) $12.2M: CBP (border service facilities)

Preliminary Cost Estimates

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Synchro-Sim MOE Output (delay: SB frequency)

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Synchro-Sim MOE Output (delay: NB frequency)

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Synchro-Sim Traffic Simulation: MOE Output

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David E. Lettner, BA, MPA, MCIP

Project Manager: Pembina-Emerson Port of Entry Transportation Study

Senior Transportation Planning Consultant

Manitoba Infrastructure and Transportation

Transportation Systems Planning Branch

CONTACT:

215 Garry Street, Winnipeg, Manitoba, Canada, R3C 3P3

T: 204.945.5270

E: david.lettner@gov.mb.ca

Presented by: