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Chattanooga-Hamilton County-North Georgia (CHCNGA) Transportation Planning Organization Travel Model Peer Review Report

3.0 Travel Demand Model

This section briefly describes the history of the CHCNGA-TPO travel model and the current version of the model.

3.1 Previous Model Versions

The original CHCNG-TPO travel model was built and run on the MINUTP platform. The model utilized a simple "stick" roadway network and had a course zone system. In 2002 a major data collection effort was performed that included a household survey and an external roadside intercept survey. Data from these sources along with imported data from other regions were used in the early 2000s to convert the travel model to a TransCAD platform with a base year of 2000 and a horizon year of 2030.

The 2000 / 2030 model included a trip generation cross-classification scheme and auto occupancy factors for a highway only mode choice model. Trip rates from the national Quick Response Freight Manual were used for generation of truck trips. The external survey was determined to have been fundamentally flawed by not interviewing mainline vehicles. As such, data from the MINUTP model was adjusted and used for the 2000 / 2030 model. The updated model also included numerous traffic analysis zone (TAZ) splits, resulting in a total of 450 zones, 420 internal and 30 external. The model also had a true shape network with additional detail. The model was a daily model, but included an optional time-of-day model based on temporal distribution data from the household survey. This version of the model was used to produce the 2030 Long Range Transportation Plan (LRTP).

3.2 Current Model Version

In the late 2000s the travel demand model was updated again to a 2007 base year and 2035 horizon year. This model version included additional TAZ splits resulting in a total of 628 zones, 590 internal and 38 external. The socioeconomic data inputs were completely updated. An air quality post processor was implemented using Mobile 6 inputs. This version of the model was used to prepare the 2035 LRTP and was the subject of this peer review.

The 2007 / 2035 model utilizes the same trip production rates that were used in the 2000 / 2030 model. Trip attraction rates were borrowed from the Knoxville Regional Transportation Planning Organization travel demand model. Special generators were used for the airport along with key recreational, educational, and retail facilities.

In the trip distribution module, K-factors are utilized for trips crossing the Tennessee River and the Tennessee / Georgia state line. These K-factors and travel time penalties on Tennessee River bridges were utilized to match observed data. An attempt was made to use household survey data results to develop friction factors, but ultimately it delivered unsatisfactory results.Instead friction factors from the MINUTP model were modified to match average trips lengths.

Mode choice in the CHCNGA model does not include a transit component. Instead, the mode choice module has a vehicle occupancy allocation component that disaggregates vehicles trips by single occupancy vehicles, high occupancy vehicles (HOV), and heavy vehicles. This allows for the analysis of HOV or truck-only lanes.

The highway assignment module is very similar to that of the 2000 / 2030 model. However, the number of locations with count data increased such that nearly 10% of all links had traffic counts associated with them. Adjustments to centroid locations, speeds, capacities, K-factors, and other trip distribution parameters were adjusted to calibrate and validate the model.

3.3 Data Collection to Support the Model

Over the last few years the CHCNGA-TPO has collected a lot of data that will be useful in updating the travel model. Recent data collection activities include:

A brief summary of each data collection activity follows.

3.3.1 Employment Data

One of the questions posed by the CHCNGA-TPO was regarding available sources for employment data. They compared the number of businesses among data obtained from the Quarterly Census of Employment and Wages (QCEW), the U.S. Postal Service, InfoUSA (private data source), and Dun & Bradstreet (private data source). Compared to the QCEW they found the other three data sources to be two to four times higher. This discrepancy in employment data was of concern to the CHCNGA-TPO.

3.3.2 Bicycle and Pedestrian Data

The CHCNGA-TPO has been collecting bicycle and pedestrian data for about 10 years.This data has been obtained via various methods, including automated counters.The data collection effort has been focused on key corridors that have a lot of non-motorized traffic, which is predominantly in recreation areas. The CHCNGA-TPO would like to know how to improve non-motorized data collection that will support travel modeling.

3.3.3 On-Board Transit Survey Data

The transit on-board survey was conducted in November 2010 and included all of the fixed route and dial-a-ride service with the exception of the free downtown circulator.With this data in hand, the CHCNGA-TPO was looking for guidance on how best to expand the survey results to facilitate route level analysis and forecasting.

3.3.4 Travel Time / Speed Data

Travel time / speed data was collected by a third-party firm that was able to track individual cell phones through the roadway system.This was done by using a series of relatively small grid cells to keep track of individual phones.A limitation of this approach was data contamination by traffic on nearby parallel facilities that fell within the same grid cell.The raw data had to be statistically post-processed to resolve the contamination issue.

3.3.5 External Origin / Destination Data

External origin / destination data was collected in much the same manner as the travel time / speed data.Cell phone data was used to track external movements.The region was divided into grid cells (larger than those used for the travel time / speed) and the movements of individual cell phones were tracked through the network.The resulting matrix will need data manipulation before it is ready for use in the travel model.

3.3.6 Traffic Volume Data

The CHCNGA-TPO has been actively collecting additional roadway volume data for use in model calibration and validation.In addition to gathering available data from the Tennessee and Georgia DOTs, they have collected their own supplemental data at 140 locations.These counts have also supplied valuable vehicle classification data.

3.3.7 Freight / Heavy Vehicle Data

The freight study took a closer look at the quantity of heavy vehicle movements through the region and their impact on the highway system.Over 75% of the freight that moves through the region does so via trucks.Heavy vehicle volumes are particularly high on I-75 where over 60% of the trucks appear to be through trips.These large truck volumes affect the capacity of the roadway system.

Updated: 3/25/2014
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