I-70 Mountain Corridor Freight CDOT (Tim Baker, Mehdi Baziar, - - PDF document

I-70 Mountain Corridor Freight Forecasting Project

A Partnership of CDOT, DRCOG And University of Colorado Denver

Project Team and Panel

• UCD (Bruce Janson and Susi Marlina)
• CDOT (Tim Baker, Mehdi Baziar, Bernie

Guevara, Scott Hoftiezer, Peter Kozinski, Brian Pinkerton, Juan Robles, Saeed Sobhi, Liz Stolz, Steven Abeyta, David Reeves)

• DRCOG (Erik Sabina)
• Region 1 (I-70 Corridor, from Denver to Grand Junction) plus the DRCOG

planning region (Denver Metro Area)

Study Area

3

Corridor Definition

• Regional and National Significance for

commerce and recreation

• Daily volumes of over 50,000, and hourly

volumes of close to 5,000

• Difficult mountainous terrain with four major

inclines and declines

• Home to world class skiing during the winter
• Every hour of closure during the winter causes

more the $800,000 of loss

The Issue

• In 2002, an estimated 87% of freight to, from and

within Colorado was carried by trucks.

• By 2035, this percentage is estimated to grow to

95%.

• I-70 West is a major route for commerce.
• Commercial truck trips both contribute to and are

greatly impacted by our highway congestion and access problems.

The Issue

The Solution: Active Management

Incident Mgt, Closures, Stickers, Coord. mtgs. Heavy & Light Duty Courtesy Patrols, Vendors Downhill Warning Systems, RWIS, Speed Radar ITS, Fiber Optics Travel Time, CCTV’s, 511, CoTrip.Org Chain Stations Variable Speed Limits Truck Maps, Parking Sites, Food Services, Demand Management Strategies

Where Freight Demand Forecasting Fits?

• Answer questions and support decisions on:

– Freight movement sensitivity to both operational and demand management strategies and policies. – Range of economic impacts. – Location and operation of truck parking facilities. – Ability to communicate with policy makers and stakeholders such as the trucking industry groups (CMCA), truck parking operators, ski industry, and local communities.

Study Objective

Develop Freight Trip Forecasting Methods for CDOT and DRCOG that assist the identification and analysis

• f regional transportation alternatives.
• Incorporate data on land uses, truck counts and

classifications, and origin–destination surveys.

• Integrate methods with DRCOG/CDOT models to

achieve truck trip generation, distribution, and route choice consistent with these models.

Challenges

• Develop a cost-effective approach to

improve the estimates of truck travel in the transportation planning process.

• Design model that best uses both existing

and new survey data to avoid excessive cost for data gathering, data validation, and its use within the model.

Study Process

1. Produce an assessment of potential freight forecasting methods pertinent to truck travel forecasting in Region 1 and the DRCOG region. 2. Formulate freight forecasting model and data gathering plan to predict truck trip generation, distribution, and path choice at the zonal level. 3. Based on finding of Tasks 1 and 2, collect and assemble the data needed and feasible for the freight forecasting model chosen.

Study Process

• 4. Develop, implement, calibrate, and validate

the freight forecasting model chosen.

• 5. Analyze impacts of example traffic

management alternatives to reduce congestion delays.

• 6. Summarize findings of the scenario

evaluations and document the use of the model.

Freight Forecasting Project Flowchart

Status of Progress

Task 1 (Dec, 2008 – Feb, 2009):

• Literature Review from previous studies
• Four steps modeling: Trip Generation, Trip

Distribution, Modal Split, and Route Assignment.

• Assessed approached implemented by

Baltimore and Atlanta using Direct Estimation as being most relevant to what we sought to accomplish.

Status of Progress

Task 2 (Feb – April, 2009)

• Identify data sources and locations

CDOT 48-hour count :1176 locations (949 with GPS coordinates) ATR: 106 sites (54 axle and 32 length classification, 4 radar, and 16 WIM) DRCOG 120 Sites

Find Locations on Study Network

• 339 locations from 48-hour count sites
• 69 locations from ATR sites
• 115 locations from DRCOG count sites

523 total locations where truck classification counts were taken in recent years that are on our study network.

Disaggregated Vehicle Types

• 1. Commercial Vehicle: light/medium duty

vehicles used for business

• 2. Single Unit Truck (SUT): 2 axle, 6 tires
• 3. Large Combination Vehicle (LCV): 3 axle

plus

On Going

• Developed factor from ATR counts to

adjust CDOT 48-hour counts and DRCOG counts for: a.Time of day b.Day of week c.Month of year d.Time since count taken

Next

• Develop truck trips (O-D) including EE, EI,

and IE trips (E = external, I = internal).

• Calibration
• Model Validation
• Model Application evaluate scenarios

with performance measures