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«Technical Report Documentation Page 1. Project No. 2. Government Accession No. 3. Recipient's Catalog No. SWUTC/11/161127-1 4. Title and Subtitle 5. ...»

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The results are presented in Table 1. From 1990 to 2000, changes in the total number of commuters and the number of inter-metropolitan commuters within the Texas Triangle Area varied in the four major metropolitans. Although the number of commuters who lived in counties outside the four major metropolitan areas only increased 15%, the number of commuters who commuted to the four major metropolitan areas increased 91%. The huge difference between the two growth rates signals strong social-economic activities within the four major metropolitans in the Triangle Area. In both Houston and San Antonio regions, the growth of the intermetropolitan commuters was much faster than the growth of the total commuters, which indicates that more commuters traveled outside of their residence metro regions to work. Then, the detailed commuting flows between regions presented in Table 1 show that for San Antonio region, the largest group of inter-metropolitan commuters were commuting to the Austin region, with the percentage increased from 59% to 74% from 1999 to 2000. The changes in the total number of commuters and the number of inter-metropolitan commuters from 1990 to 2000 in the Dallas-Fort Worth region were about the same. And Austin is the only region where the growth of the total number of commuters were much faster than that of the number of inter-metropolitan commuters from 1990 to 2000; meanwhile Austin region attracted more inter-metropolitan commuters from all other areas in the Texas Triangle during the ten-year period, especially commuters from San Antonio.

Table 1: Percentage Changes of Total and Interregional Commuters from 1990 to 2000

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The strongest message delivered by the CTPP data is the rapid growth of commuters from other counties to the four metropolitan regions, and the increasingly tightened connection between Austin and San Antonio.

5.4. The Analysis of the NHTS data The 2001 and 2009 NHTS data are used to examine the long distance commuting patterns in the US. The most current NHTS data (2009 data) were collected in year 2008. There are a total of 150,147 household samples (324,184 persons) in the survey, among which 22,255 household samples (49,172 persons) were collected in Texas. Prior to the 2009 NHTS is the 2001 NHTS. In the 2001 NHTS, 69,817 household samples (160,758 persons) were collected nationwide with 5543 household samples (12,938 persons) in Texas.

The analysis was concentrated on two geographical levels - national level and Texas level. The variable of reported distance to work was used to identify long distance commuters. Since the NHTS data do not provide detailed origins and destinations of each commute, it is difficult to distinguish interregional commute from commutes within one region. Yet, the 50-mile one-way distance can be used as the criterion to identify commutes across the boundary of a metropolitan region. In addition, the NHTS does not include survey questions to distinguish weekly commuters, thus, in this analysis, weekly commuters were separated out by assuming that workers who travel 100 miles or more to work will commute weekly. At the national level, a descriptive analysis of the two NHTS data (2001 and 2009) were performed, and binary logit models were developed for commuters who traveled at least 50 miles and 100 miles, respectively.

At the Texas level, detailed work flow directions were examined based on the home and work address that respondents reported.

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Since the 2001 NHTS is a national survey, it collected data from a nationally representative sample of households to derive statistically reliably travel estimates at the national level. The nationwide sample data will not be adequate to provide statewide, or area-specific estimates. Yet, the NHTS provided an “add-on” program, which allowed a state or a local jurisdiction which wants to develop travel estimates for a specific area to purchase additional households in their jurisdiction to be interviewed and included in the NHTS. The state of Texas participated in the “add-on” program in the 2001 NHTS to add more than 3,000 samples in Texas, which can serve as a rich resource for understanding the intercity travel in Texas.

5.5. Long Distance Commute in the Nation

The NHTS data show that from 2001 to 2009, the total number of workers in the US increased 4% while the total number of workers in Texas increased 13% during the same period. In the US, 2.8% of all workers were long distance commuters in 2001, and the percentage increased to 2.9% in 2009. As shown in Table 7, Northeast and West regions had higher percentage of long distance commuters than other regions in 2001, but the percentage dropped to below other regions in 2009. On the contrary, the percentage of long distance commuters increased from 2001 to 2009 in Midwest and South regions. In 2009, the South region had the highest percentage of long distance commuters.

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3.1% 2% 2.9% 3.1% 2.9% 2.9% 3.1% 2.5% Table 8 and Table 9 present the composition of long distance commutes in 2001 and in 2009.

Overall, among the long distance commutes, more than 80% of the commutes were shorter than 100 miles one way and less than 3% of the commutes were longer than 300 miles. The long distance commute composition varied among the four Census regions. The South region had the highest share of commute with distance between 100 miles and 300 miles, although this share dropped from 17% in 2001 to 13% in 2009. The Northeast region had the second highest share of commute with distance between 100 mile and 300 miles but had the lowest share of commute with distance longer than 300 miles. The long distance commute composition in the Midwest region remained stable during the approximately 10-year period, and the share of commute with distance less than 100 miles were highest in the US in both years. In the West region, the share of commute with distance less than 100 miles experienced the largest drop from 2001 to 2009 while the share of commute with distance between 100 and 300 miles increased the most.





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87.17% 92.17% 78.17% 91.91% 85.9% 50-100 12.59% 6.68% 17.12% 5.72% 11.52% 100-300 0.24% 1.15% 4.72% 2.37% 2.58%

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The main travel means for long distance commuters was private car. As shown in Table 10, more than 90% of long distance commuters drove private cars to work and more than 80% of them drove alone.

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91.3% 80.0% 91.5% 83.0% Because of the long commute distance, long distance commuters need to spend longer time on road. Table 11 compares the percentage of long distance commuters who left home before 7am and returned home after 6pm to that of shorter distance commuters. More than 50% of long distance commuters left home before 7am and returned after 6pm while less than 30% of short distance commuters left home before 7am and less than 40% returned home after 6pm.

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The NHTS data also show that the Vehicle Mile Traveled (VMT) by the 3% long distance commuters accounted for 16% of VMT by all commuters in 2001 and 13% in 2009. Table 12 lists the VMT for commuting in 2001 and 2009. The overall VMT by commutes drops 0.05%;

VMT by short distance commuters increased 2.8% while VMT for long distance commuter decreased 15%.

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Binary logit models were developed separately for long distance commute with trip length of more than 50 miles and trip length more than 100 miles, and for year 2001 and 2009.

Table 13 lists variables included in the models.

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The results of the models, as shown in Table 14, contain findings within expectation as well as surprises. Five variables have consistent effects in all four models. The first variable is gender.

As found by other researchers, these models also prove that males are more likely to commute long distance than female. The second variable is income. The models show that workers with highest level of salary are more likely to commute long distance, which is expected since higher level of pay is an incentive for long distance commute and is often needed to compensate the cost associated with long distance travel. The third variable is number of workers in a household.

The models indicate that individuals are less likely to commute long distance when the number of workers in a household increases. This result brings a little surprise. Several researchers have found that having two earners in a household can encourage long distance commute since there exist more obstacles to an optimized commute for both workers in a household (Ma & Banister, 2006). Yet, the result can also be explained because people may have more time to search for job opportunities closer to home with financial support of other household members. The fourth variable is home location. The models found out that workers living in urban areas are less likely to commute long distance. This result is as expected since urban areas provide more jobs. The last variable consistently affects the four models is the option of working at home. When people have the option to work at home occasionally, the probability of conducting long distance commute increases. This result indicates that flexible work policy would encourage people to travel further for better job opportunities.

Then, surprisingly, education, occupation, and house ownership are not significant for all four models. Based on literature in long distance commuting, the hypothesis for these three variables is that workers with higher level of education, workers in professional fields, and workers who own a house tend to commute long distance. However, the hypothesis is not supported by the NHTS data.

In additional to the above mentioned variables, other variables show different effects across models. The hypothesis about life cycle is that workers with small children are less likely to commute long distance, which is supported by the models for 2009, but not by the models for

2001. Then, workers in different Census regions exhibit different tendency for long distance commute in the first three models. Moreover, internet use has a negative effect on long distance commuting in model 1. It can be explained by the assumption that internet brings more local job information to people and thereby reduces long distance commute, even though internet technology provides people the opportunity to work remotely and may encourage people to take jobs far away. Finally, people's views on travel price exhibit a positive effect on long distance commute, that is people who have concerns over travel cost tend to commute long distance. The result sounds controversial. However, it seems that this variable is more of an effect of long distance commuting instead of a cause - people who commute long distance are more concerned about travel price.

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5.6. Long Distance Work Flow Directions in Texas The next step of this study is to narrow the geographical scope and focuses on the state of Texas, which is the largest state in the South region where the percentage of long distance commuting is the highest in 2009. In this step, the origins and destinations of long distance commutes were mapped based on the home and work locations respondents reported.

Figure 3 and 4 are two illustrations of long distance commuting flows in Texas in 2001 created using different methods. The origins and destinations were located at the tract level of reported home and work locations. In Figure 3 the long distance commuting were identified by the reported distance to work of 50 miles or longer; in Figure 4, the long distance commuting were identified by the calculated commuting distance based on the reported home and work locations.

TrasCAD GIS was used to calculated the distance between home and work based on FAF3 network. The second method has captured more long distance commuting.

By examining the detailed work flows, it proves that 50-mile is a good criterion to capture LDC/TRC commuting. About 70% of the commutes with distance of 50 miles or longer were interregional. In addition, it can also be found that the Texas Triangle area is the core which attracted LDC/TRC commuting in Texas. More than 70% of the long distance commuting destinations were located within the Texas Triangle area.

Figure 3: Long Distance Commute Flow Directions in Texas (2001a)

Figure 4: Long Distance Commute Flow Directions in Texas (2001b) The long distance commuting flows were also mapped for 2009 using the first method, as shown in Figure 5. As the sample size increased in the 2009 NHTS, a clearer "Triangle Pattern" that represents the commuting flows between the four major metropolitans in the Triangle area can be seen. In 2009, more than 60% of the commutes with distance of 50 miles or longer were interregional, and about 80% of the long distance commuting destinations were located within the Texas Triangle area.

Figure 5: Long Distance Commute Flow Directions in Texas (2009)

5.7. Limitation of Using Secondary Travel Survey Data Analyzing the CTPP data and the NHTS data is the first step in this research to gather knowledge about the LDC/TRC commuters and their work trips. The results generate an overall awareness of the interregional commuting flow patterns in the Texas Triangle Area, the long distance commuting changes across the nation, and some basic characteristics of the long distance commuters. However, the survey questions on journey-to-work trip in the Census survey and in the NHTS, as well as the characteristics of survey data limit their ability to clearly answer the questions asked in this research.



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