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VMT Validity and Alternative Measures of Motorization


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VMT Validity and Alternative Measures of Motorization

  1. 1. VMT Validity and Alternative Measures of Motorization Prepared by: Amy Tzu-Yu Chen University of California, Los Angeles Instructor: Martin Wachs June 2015
  2. 2. Introduction There has been growing interest among economists, policy makers, environmentalists, and transportation researchers in investigating the trend and effects of the total volume of vehicle travel in the United States. The issue of vehicle travel pattern intrigues economists because it has long been observed that the aggregate vehicle travel in America correlates with economic growth, though the causality between the two is yet to be confirmed. Politicians want to reduce the total mileage of vehicles in order to bring down greenhouse gas emissions, lessen traffic congestion, and promote the use of public transportation. Environmentalists are certainly the greatest supporter for this new direction in transportation policy and they expect to see a gradual decrease in the use of vehicles. Among the many discussions of aggregate vehicle travel for either economic or political purposes, VMT, or vehicle miles of travel, is the most widely used way of measuring the gross mileage of vehicle travel. The Federal Highway Administration (FHWA) under the U.S. Department of Transportation regularly compiles and publishes monthly and annual VMT reports on the web. These reports play a crucial role in numerous studies of U.S. motorization because they are almost the only source that researchers referred to in order to understand current and historical vehicle travel patterns. While economists propose potential causality between VMT and GDP and transportation policy makers rely on VMT data to formulate future policies, it is important to validate the statistical processes of VMT data collection and compilation. Anyone can access current and historical VMT data through FHWA’s official website and the data come in friendly formats for statistical analysis. The procedure of
  3. 3. VMT data formulation, however, is not widely discussed. Few mention the fact that VMT data are collected separately by local departments of transportation and FHWA is responsible for final compilation and supervision of data reports. FHWA published general guidelines called Traffic Monitoring Guide, which can also be freely accessed online, to local transportation researchers. The practical data collection and compilation processes, however, can hardly be as consistent as FHWA intended them to be. There are alternative ways to comprehend the national and local travel trends other than VMT. Some researchers have integrated other sources of data in order to have an objective view of travel patterns. These alternative sources could often reflect more detailed or more accurate travel patterns in the U.S. than VMT. For example, National Household Travel Survey collects means and purposes of daily travel of people from different age groups. The intuitive measure of the number of registered vehicles can also imply changes in travel behaviors as well as economic and societal environments. By substituting VMT data from FHWA with alternative measures of travel trends, researchers could sometimes prompt disparate conclusions. Why Is VMT Important? The relationship between VMT and economic growth is often studied. GDP, or gross domestic products, is a simple indicator of economic growth. When researchers paired VMT and GDP together, there exists observable similarities in which VMT and GDP grew. The aggregate measures of GDP and VMT appear to be closely correlated since 1936 and it was not until 2003 that people started to see the measures diverging. It is tempting to simply say there existed a linear relationship between VMT and GDP so
  4. 4. that people could use current VMT or GDP to predict one another. Nevertheless, the causality between the two measures is yet to be determined. One could argue that decline in mobility discouraged economic activities, but one could also say that the decline in mobility is a consequence of economic recession. The causality is difficult to prove so whether the similar patterns in VMT and GDP have far-reaching meaning to our society is still questionable. Nonetheless, further studies of the relationship between VMT and economic growth requires dependable VMT data before researchers continue exploration of the relationship between VMT and GDP. Figure 1. Total Auto and Truck VMT (trillions) and GDP (trillions of $2005), 1936-2011 ! Note: VMT axis on left; GDP on right Graph Source: Liisa Ecola, Martin Wachs, and The RAND Corporation, “Exploring the Relationship between Travel Demand and Economic Growth”, December 2012. Figure 1. Data sources: VMT: FHWA,1995 (Table VM-201); FHWA, 2012; BTS, 2012 (Table 1-35); GDP: BEA, 2012 (Current-dollar and “real” GDP file as of February 29, 2012)
  5. 5. In response to the environmental concerns about global warming and air pollution, the direction in transportation policy has been shifting towards reducing VMT in order to bring down greenhouse gas emissions from vehicles. These policies generally include charging drivers fees based on VMT data, promoting public transportation ridership, and also control of fuel consumption. As transportation departments usually rely on VMT reports as the primary source for understanding current travel patterns, the validity of VMT data could largely influence the decisions on the country’s transportation system. VMT Measurement Process FHWA is responsible for the publication of monthly and annual VMT measures. These reports often provide grounds for researchers and policy makers to generate conclusions about changes in travel behaviors. However, few queried the actual processes in which these data are assembled before using them for academic and political purposes. FHWA is widely referred to as the data source provider, however, the agency does not assemble VMT data all by itself. Instead, the agency serves as the supervisor and distributor of the VMT data and states report the latest local VMT measures to FHWA, thus, the actual data collection is done at state level. FHWA dispenses an official documentation on VMT estimation, which is called Travel Monitoring Guide on Highway Statistics website, and states are liable for preparing the VMT estimates based on the manual. This hierarchical structure of VMT collection process has the potential weakness that the data can be inconsistent or deficient. Although FHWA gives states instructions
  6. 6. on the statistical method for gathering, calculating, and reporting VMT, the actual processes of data collection can still vary between states. For example, states use counting stations in various locations to collect traffic counts; however, it is difficult to have a consistent method of setting up the machines considering the differences in geographical constraints and residents’ travel behaviors between states. Also, the maintenance of counting machines can influence the quality of data. If a machine suddenly breaks down and does not return the VMT data in time, the quality of state’s VMT data would decrease yet the aggregate VMT report from FHWA does not include incidents of malfunctioning counting stations. While FHWA claims that the method of VMT data collection in each state is consistent and reliable, it evades the effects of the erratic nature of having not-uniformly-trained data collectors to collect data across geographically and socially diverse regions. It is crucial to sustain sampling variability when local departments of transportation collect data. This requires states to strategically and routinely change locations of counting machines so that the data can be reflexive of the actual travel patterns of the entire state. However, it is unclear how local transportation researchers decide when and how the rotations among counting machines occur. Thus, the validity of VMT data reported by FHWA is under suspicion, which requires in-depth comparisons of how each state obtains the data in order to substantiate itself to be a dependable source for travel behavioral studies. After investigations of states’ VMT reports and interviewing some local transportation researchers, concerns regarding the validity of VMT data collection were confirmed. From California’s monthly VMT reports, one can observe that many of the counting stations used in VMT calculations were often unavailable hence were not able
  7. 7. to supply data. In most months, there were at least three counting stations, out of the total of twenty counting stations used in VMT calculations, were not available for use and the data were left in blank. FHWA often replaced these missing counts by the average count of the entire state or nearby state, however, this may potentially ascribe an average value to a location with abnormally high or low VMT or vice versa. Also, an administrator at U.S. Department of Transportation admitted that, “States sometimes report estimates that are out of the range of reasonableness, and do not necessarily provide corrections when unreasonable numbers are reported” (Schmitt). FHWA cannot be certain whether these abnormal data are statistically significant and it is likely that these data are included in the historical VMT reports regardless. In addition, the VMT measure is usually split into urban and rural sections thus an up-to-date division of urban and rural areas could have a significant impact on the accuracy of VMT data. Nonetheless, FHWA has not updated urban boundaries while the urban areas could have extended into previously rural area a long time ago. The comparisons of VMT between urban and rural could not be accurate without correctly defining the borderline. As travel behavioral analyses commonly compare and contrast travel patterns in and outside of the city, FHWA should provide VMT data that can reflect ongoing urbanization.
  8. 8. Alternative Measurements There are data sources other than VMT that can reflect travel behavior patterns in the United States. National Household Travel Survey emphasizes other aspects of travel behaviors, such as means and purposes of a trip. VMT, in comparison, does not offer such diverse and detailed insights about travel patterns. Another example of reflective measure of travel behavior is simply the number of registered cars. The data bypasses the miscellaneous possibilities of creating statistical error in data collection since every driver is required to register their car and truck near their residence. Many researchers have already incorporated them into their studies or cross validated them with VMT measures. National Household Travel Survey (NHTS), also prepared by FHWA, aims to provide information that can comprehensively assist transportation researchers and policy makers on travel patterns in the United States. The survey does not estimate travel patterns by mileage counts, instead, it extensively inspects other components in each trip of a household as well. Specifically, states request a sample of households to record their daily travels, including purposes of the trip, means of transportation, time and duration, and ridership statistics if it is a private vehicle trip. These questions are designed to understand travel behaviors from a more humane perspective. Instead of piling up aggregate mileage of travels, the survey is interested in how and why people take the trip. Another advantage about NHTS is that it also contains demographic information about the travelers. Researchers can thus interpret travel behaviors in relation to the background of the travelers, which the rigid mileage data of VMT cannot offer. The NHTS data can supply transportation planners with information about travel
  9. 9. modes. As the paradigm in urban planning shifts towards developments in public transit and zero emission travels, records of trips that are as comprehensive as NHTS are more practical than VMT reports for assessing topics such as effectiveness of public transportation. However, unlike VMT measures which are published monthly, NHTS is conducted almost every six or eight years. Since NHTS requires collaboration with sample households and classification of answers from a multilevel survey, it is time- consuming and demands more social resources than VMT. Moreover, similar to VMT data collection, states could have different ways of administrating NHTS survey even with a manual. For example, the sizes of samples among states and the choice of households may differ, which will result in inconsistent data quality and inability to have a credible conclusion about national travel patterns. Figure 2. Registered light-duty vehicles, 1984-2011. ! Graph Source: Michael Sivak, “Has Motorization in the U.S. Peaked?”, June 2013, Figure 1. Data source: Registered Light-duty Vehicles: FHWA,2013.
  10. 10. Michael Sivak from Transportation Research Institute at University of Michigan proposed a rather intuitive approach to the analysis of travel behavior in the United States. In “Has Motorization in the U.S. Peaked?”, Sivak discussed the possibility of examining recent trends in motorization based on the absolute numbers of registered light-duty vehicles, which include cars, pick-up trucks, SUVs, and vans. According to Figure 2, the change in the number of light-duty vehicles has a steadily increasing trend, which is almost analogous to the VMT change in Figure 1. The number of light-duty vehicles in 1984 was 156.8 million and the number climbed up to the maximum of 236.4 million in 2008. After 2008, an observable decrease in registered vehicles as a result of economic recession, and the number went down to 233.8 million in 2011. Sivak did not try to tie the economic status and motorization. He observed that the decrease in car usage occurred prior to 2008, thus he suspected that other societal changes drove the demand of cars to go down before economic downturn. By using the social and economic event to try to make sense of the fluctuations in the number of registered cars, researchers could also discuss the change in travel behaviors. Compared to VMT, the data of registered cars are less likely to be erratic because all drivers are required to register their cars by their residence. The downside of this measurement is that it does not provide detailed information as NHTS and offer only an aggregate counts that can often be too conclusive to show changes in travel behaviors. Conclusion The accessibility and transparence of the VMT makes validation of data quality seem unnecessary. However, as researchers and policy makers frequently rely on VMT
  11. 11. as the primary source for understand current trends of travel behavior, whether VMT is a credible data source that was compiled strictly based on statistical principles becomes an important issue. There are possibilities of substituting or cross validating VMT with alternative measures of travel patterns, such as NHTS and the total of registered cars.
  12. 12. References Ecola, Liisa., Wachs, Martin., & The RAND Corporation. (2012). Exploring the Relationship between Travel Demand and Economic Growth. Sivak, Michael. (2013). Has Motorization in the U.S. Peaked? University of Michigan, Ann Arbor, Michigan: Transportation Research Institute (UMTRI).