Analysis of induced travel in the 1995 npts



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ANALYSIS OF INDUCED TRAVEL

IN THE 1995 NPTS

James G. Strathman

Kenneth J. Dueker

Thomas Sanchez

Jihong Zhang

Anne-Elizabeth Riis


June 2000

Center for Urban Studies

College of Urban and Public Affairs

Portland State University

Portland, OR 97207



ANALYSIS OF INDUCED TRAVEL IN THE 1995 NPTS
Abstract

In this paper we estimate the relationship between road capacity and vehicle miles of travel (VMT) from a sample of 12,000 respondents from 48 urban areas in the 1995 Nationwide Personal Transportation Survey (NPTS). Our approach seeks to account for the effects of residential location, employment location, and commute mode choice in estimating the effect of capacity on VMT. VMT is found to be directly related to road capacity, as well as indirectly related through the influence of road capacity on residential and work place densities.



Introduction

Induced travel responses to changes in road capacity have been recognized by transportation planners and economists since the first applications of cost-benefit analysis to road projects in the 1930s (Prest and Turvey, 1965). However, interest in determining the magnitude of induced travel responses has grown in recent years in response to policy concerns about the links between highway construction, air quality and urban development patterns, and the desire to ensure efficient resource allocation through more detailed evaluation of highway projects. It has also been suggested that induced travel responses have become more substantial as a result of worsening traffic congestion (Hansen, 1998).

Efforts to estimate induced travel effects of road capacity expansions are complicated by the need to distinguish capacity-related effects from a variety of other determinants (Dunphy, 1998). In addition to capacity-related changes, the growth in vehicle miles of travel (VMT) over time can be attributed to changes in household demographics and economic status as well as spatial changes in urban residential and economic structure. Urban development patterns, in turn, may reflect long run adjustments to changes in transportation system capacity.

In this paper we seek to estimate the effects of road capacity on VMT using person and household data from the 1995 Nationwide Personal Transportation Survey (NPTS), and road capacity data from the Texas Transportation Institute (TTI). Our focus is limited to a sample of 12,000 NPTS worker respondents from 48 urban areas in the U.S. Our intent is to distinguish the effects of road capacity on VMT from effects associated with personal and household characteristics, as well as effects associated with residential, work place and commute mode choices. The cross section of urban areas in the sample implies a long run adjustment process to changes in road capacity.

The remainder of the paper is organized as follows. In the next section we review the concept of induced travel and summarize empirical findings from earlier studies. We then describe the process used to construct the data set for the present study. The underlying framework relating locational and travel activities guiding our analysis is discussed, and the associated specification of the empirical model is presented. The estimation of the model and the empirical results are then reported. The paper concludes with a discussion of the findings and their implications.
Background

Researchers have sought to understand travel responses to roadway capacity improvements since the advent of automobile use, long before congestion became a national concern (Levinson, 1996). Now that heavy traffic conditions are being experienced on most major urban U.S. highways during both peak and non-peak times, examining the potential impact of added roadway capacity has become especially relevant, and related research is becoming more plentiful. Capacity induced travel has important implications for infrastructure, land use, and environmental policies (Dyett, 1991; Suhrbier, 1991).

By definition, induced travel implies a direct or indirect causal relationship between a stimulus (road capacity increase) and a response (increased travel). This relationship is realized where a new or expanded facility results in decreased travel cost to the point that either trip frequency or trip distance increases. An increase in travel activity can only be attributed to a capacity increase if all other conditions before and after the increase are controlled for. Typically, travel responses are not solely dictated by travel cost reductions; rather, they are determined endogenously as a function of many supply and demand factors (Lee, 1999).

In addition to detectable changes in travel demand levels resulting from capacity increases, the concept of induced travel also implies an overall net increase in travel demand. Behavioral responses to changes in congestion can have impacts on the road network that may or may not involve increases in trips or miles. These forms of travel substitution are discussed later. The notion of latent demand is associated with net increases in travel. While latent demand cannot be easily measured, it has been assumed that a net increase in travel activity resulting from capacity increases is an expression of unused travel time budgets (Litman, 1999).

There is evidence to suggest that expanding highway capacity may be an ineffective way to relieve congestion (Arnott and Small, 1994; Stopher, 1991). Downs’ (1962) “triple convergence principle” characterizes this phenomenon as follows: subsequent to increases in roadway capacity, travel activity changes may mitigate the effect of lowering congestion levels. Downs’ three types of travel adjustments are categorized as route, time, and mode-convergence, together describing the tendency for highway improvements providing new capacity to attract travelers from other routes, other times of day, and other modes.

The phenomenon of convergence is often confused with induced travel. For instance, new capacity can be quickly absorbed by redistributed rather than generated traffic. Thus, the benefits of a new facility, in the short run, are travel time and cost, and actual reductions of motorists converging, and should not be calculated from congested to free-flow conditions. Similarly, benefits in the long run should include the effect of generated traffic on travel time and costs. Examples of studies indicating that increased capacity leads to increased traffic are the following:



  • Hansen (1995) found that a 1 percent increase in lane miles generated a 0.9 percent increase in VMT within 5 years.

  • According to Dowling and Colman (1998), congestion-relieving projects were likely to induce a 3 to 5 percent increase in trip generation.

  • Goodwin’s study (1996) indicated that average road improvements induce an additional 10 percent of base traffic in the short term and 20 percent in the long term.

  • A synthesis by Pells (1989) showed a wide range of results, with estimated induced traffic as high as 76 percent of observed increases in traffic flows.

  • Hansen and Huang (1997) reported that a 2 percent increase in state highway lane miles caused a 2.0 to 3.5 percent increase in VMT.

Depending upon methodologies and data sources, analyses of induced travel provide differing results. Because these results directly affect planning for new and improved roadways, it is important that they properly control for natural growth, possible latent travel demand, and feedback (Williams and Yamashita, 1992; Johnston and Ceerla, 1996). It has been shown that conventional forecasting methods can overestimate benefits while underestimating the increases in VMT that will accompany expanded capacity (Brand, 1991; Litman, 1999; Noland and Cowart, 1999). These increases in vehicle travel have associated environmental, social, and economic costs that are not easily quantified. Considering these externalities, some argue that the critical issue is not simply the resulting induced travel, but rather the net societal benefits of the investment (DeCorla-Souza and Cohen, 1998).





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