Relationships between highway capacity and induced vehicle travel

The theory of induced travel demand asserts that increases in highway capacity will induce additional growth in traffic. This can occur through a variety of behavioral mechanisms including mode shifts, route shifts, redistribution of trips, generation of new trips, and long run land use changes that create new trips and longer trips. The objective of this paper is to statistically test whether this effect exists and to empirically derive elasticity relationships between lane miles of road capacity and vehicle miles of travel (VMT). An analysis of US data on lane mileage and VMT by state is conducted. The data are disaggregated by road type (interstates, arterials, and collectors) as well as by urban and rural classifications. Various econometric specifications are tested using a fixed effect cross-sectional time series model and a set of equations by road type (using Zellner’s seemingly unrelated regression). Lane miles are found to generally have a statistically significant relationship with VMT of about 0.3–0.6 in the short run and between 0.7 and 1.0 in the long run. Elasticities are larger for models with more specific road types. A distributed lag model suggests a reasonable long-term lag structure. About 25% of VMT growth is estimated to be due to lane mile additions assuming historical rates of growth in road capacity. The results strongly support the hypothesis that added lane mileage can induce significant additional travel.     

A planning tool for evaluating vehicles miles travelled and traffic safety forecasts of growth management scenarios: A case study of Baton Rouge and New Orleans

This study describes an adaptable planning tool that examines potential change in vehicle miles travelled (VMT) growth and corresponding traffic safety outcomes in two urbanized areas, Baton Rouge and New Orleans, based on built environment, economic and demographic variables. This model is employed to demonstrate one aspect of the potential benefits of growth management policy implementation aimed at curbing VMT growth, and to establish targets with which to measure the effectiveness of those policies through a forecasting approach. The primary objective of this research is to demonstrate the need to break with current trends in order to achieve future goals, and to identify specific policy targets for fuel prices, population density, and transit service within the two study regions. Models indicate based on medium growth scenarios, Baton Rouge will experience a 9 percent increase in VMTs and New Orleans will experience 10 percent growth. This translates to corresponding increases in crashes, injuries and fatalities. The paper provides forecasts for planners and engineers to consider an alternative future, based on desired goals to reduce VMTs and therefore improve safety outcomes. A constrained-forecast model shows a cap on VMTs and crash rates is achievable through policy that increases fuel prices, population density and annual transit passenger miles per capita at reasonable levels through a growth management approach.     

Estimating vehicle miles traveled (VMT) in urban areas using regression kriging

The recent increase in demand for performance‐driven and outcome‐based transportation planning makes accurate and reliable performance measures essential. Vehicle miles traveled (VMT), the total miles traveled by all vehicles on roadways, has been utilized widely as a proxy for traffic impact assessment, vehicle emissions, gasoline consumption, and crashes. Accordingly, a number of studies estimate VMT using diverse data sources. This study estimates VMT in the urban area of Bucheon, South Korea, by predicting the annual average daily traffic for unmeasured locations using spatial interpolation techniques (i.e., regression kriging and linear regression). The predictive performance of this method is compared with that of the existing Highway Performance Monitoring System (HPMS) method. The results show that regression kriging could provide more accurate VMT estimates than the HPMS method and linear regression, especially with a small sample size. Copyright © 2016 John Wiley & Sons, Ltd.     

VMT, energy consumption, and GHG emissions forecasting for passenger transportation

Globalization, greenhouse gas emissions and energy concerns, emerging vehicle technologies, and improved statistical modeling capabilities make the present moment an opportune time to revisit aggregate vehicle miles traveled (VMT), energy consumption, and greenhouse gas (GHG) emissions forecasting for passenger transportation. Using panel data for the 48 continental states during the period 1998-2008, the authors develop simultaneous equation models for predicting VMT on different road functional classes and examine how different technological solutions and changes in fuel prices can affect passenger VMT. Moreover, a random coefficient panel data model is developed to estimate the influence of various factors (such as demographics, socioeconomic variables, fuel tax, and capacity) on the total amount of passenger VMT in the United States. To assess the influence of each significant factor on VMT, elasticities are estimated. Further, the authors investigate the effect of different policies governing fuel tax and population density on future energy consumption and GHG emissions. The presented methodology and estimation results can assist transportation planners and policy-makers in determining future energy and transportation infrastructure investment needs.     

Impact of fuel price on vehicle miles traveled (VMT): do the poor respond in the same way as the rich?

The effects of fuel price on travel demand for different income groups reveal the choices and constraints they are faced with. The first purpose of this study is to understand these underlying choices and constraints by examining the variation of fuel price elasticity of vehicle miles travelled (VMT) across income groups. On the other hand, the rebound effect—increase in VMT as a result of improvement in fuel efficiency may offset the negative effect of fuel price on VMT. The second purpose of this study is to compare the relative magnitudes of the fuel price elasticity of VMT and the rebound effect. A system of structural equations with VMT and fuel efficiency (MPG, miles per gallon) as endogenous variables is estimated for households at different income levels from 2009 National Household Travel Survey. Higher income households show greater fuel price elasticity than lower income households. Fuel price elasticities are found to be ?0.41 and ?0.35 for the two highest income groups, while an elasticity of ?0.24 for the lowest income group is identified. The rebound effect is found to be only significant for the lowest income households as 0.7. These findings suggest the potential ability of using fuel price as a tool to affect VMT. The study results also suggest possible negative consequences faced by lower income households given an increase in fuel price and call for more studies in this area.     

Are we successful in reducing vehicle miles traveled in air quality nonattainment areas?

An important planning and policy question in the transportation, energy, and environment areas is whether or not air quality control and the associated funding preference and mitigation efforts to attain air quality conformity have indeed led to traveler behavior changes such as reduction in vehicle miles traveled (VMT) or VMT growth rates. In this research, we develop statistical models to analyze the relationship between air quality nonattainment designation and VMT between 1966 and 2004 based on observed data. These models employ different statistical methods, including hypothesis testing and simultaneous equations. Findings from these statistical models and datasets are consistent, and suggest there is a statistically significant negative correlation between nonattainment designation and VMT/VMT growth. For instance, the simultaneous equation model in this research, suggests that if a nonattainment area and an attainment area that are similar in all other aspects (population composition, socio-economics, urbanization, fuel price, vehicle stock, etc.) are compared, the VMT in the nonattainment area will be 1.80% less than that in the attainment area in the short run, and 7.61% less in the long run. While these results show strong statistical evidence that efforts in reducing VMT in nonattainment areas have been successful, future research should be conducted to attribute the VMT reduction effects to specific policy instruments for decision-making (e.g. the Congestion Management and Air Quality Improvement program, the conformity regulation in the transportation planning process, etc.).     

Influence of housing development designs on household vehicle miles traveled: A case of Iskandar Malaysia

Demand for housing in Malaysia grew noticeably in 1960s and expanded rapidly in the late 1980s and beyond as a result of rapid urbanization. The same scenario repeats itself in Iskandar Malaysia, a southern development corridor located in Johor, Malaysia where close to three hundred housing developments have been launched from pre-1980s to 2000s. These housing developments are believed to have undergone a layout design evolution affecting land use distribution, road network design, density and many other neighborhood metrics. Thus, this study investigates the impact of housing development designs on vehicle miles traveled (VMT) as they evolve over the decades. Evolution in layout design is discussed in terms of the 4Ds of urban form factors: density, diversity, design (street connectivity and intersection density) and destination accessibility (proximity). Twenty four housing areas developed within decades of pre-1980s to the 2000s were selected and travel diaries of their randomly selected households were recorded. The results obtained show that urban form and demographic factors explain almost 87% of the variances in household VMT and the three main design factors influencing VMT are housing density, proximity index (destination accessibility) and diversity index. The findings of the study show that there is a decreasing trend in density, (land use) diversity, connectivity and destination accessibility of the housing areas. While the results obtained confirm the prevalent theory on the relationship between neighborhood design and VMT, unfortunately for the study area the average VMT has been increasing with the recent housing areas.     

Estimating potential increases in travel with autonomous vehicles for the non-driving,elderly and people with travel-restrictive medical conditions

Automated vehicles represent a technology that promises to increase mobility for many groups, including the senior population (those over age 65) but also for non-drivers and people with medical conditions. This paper estimates bounds on the potential increases in travel in a fully automated vehicle environment due to an increase in mobility from the non-driving and senior populations and people with travel-restrictive medical conditions. In addition, these bounding estimates indicate which of these demographics could have the greatest increases in annual vehicle miles traveled (VMT) and highlight those age groups and genders within these populations that could contribute the most to the VMT increases. The data source is the 2009 National Household Transportation Survey (NHTS), which provides information on travel characteristics of the U.S. population. The changes to light-duty VMT are estimated by creating and examining three possible travel demand wedges. In demand wedge one, non-drivers are assumed to travel as much as the drivers within each age group and gender. Demand wedge two assumes that the driving elderly (those over age 65) without medical conditions will travel as much as a younger population within each gender. Demand wedge three makes the assumption that working age adult drivers (19–64) with medical conditions will travel as much as working age adults without medical conditions within each gender, while the driving elderly with medical any travel-restrictive conditions will travel as much as a younger demographic within each gender in a fully automated vehicle environment. The combination of the results from all three demand wedges represents an upper bound of 295 billion miles or a 14% increase in annual light-duty VMT for the US population 19 and older. Since traveling has other costs besides driving effort, these estimates serve to bound the potential increase from these populations to inform the scope of the challenges, rather than forecast specific VMT scenarios.     

Quantifying the relative contribution of factors to household vehicle miles of travel

Household vehicle miles of travel (VMT) has been exhibiting a steady growth in post-recession years in the United States and has reached record levels in 2017. With transportation accounting for 27 percent of greenhouse gas emissions, planning professionals are increasingly seeking ways to curb vehicular travel to advance sustainable, vibrant, and healthy communities. Although there is considerable understanding of the various factors that influence household vehicular travel, there is little knowledge of their relative contribution to explaining variance in household VMT. This paper presents a holistic analysis to identify the relative contribution of socio-economic and demographic characteristics, built environment attributes, residential self-selection effects, and social and spatial dependency effects in explaining household VMT production. The modeling framework employs a simultaneous equations model of residential location (density) choice and household VMT generation. The analysis is performed using household travel survey data from the New York metropolitan region. Model results showed insignificant spatial dependency effects, with socio-demographic variables explaining 33 percent, density (as a key measure of built environment attributes) explaining 12 percent, and self-selection effects explaining 11 percent of the total variance in the logarithm of household VMT. The remaining 44 percent remains unexplained and attributable to omitted variables and unobserved idiosyncratic factors, calling for further research in this domain to better understand the relative contribution of various drivers of household VMT.     

The net effects of the built environment on household vehicle emissions: A case study of Austin,TX

Growing concerns over climate change have led to an increasing interest in the role of the built environment to reduce transportation greenhouse gas (GHG) emissions. Many studies have reported that compact, mixed-use, and well-connected developments reduce vehicle miles traveled (VMT). Others, however, argue that densification and mixture of land uses can slow down vehicle movements, and consequently generate more driving emissions. Methodologically, VMT is only a proxy, not an exact measure of emissions. This study quantifies the net effects of the built environment on household vehicle emissions through a case study of Austin, TX. The study employed structural equation modeling (SEM) techniques and estimated path models to improve understanding of the relationship between the built environment and vehicle emissions. The results show a rather complex picture of the relationship. Densification can reduce regional vehicle emissions despite its secondary effect of reduced vehicle travel speed. A 1% increase in density was found to reduce household vehicle emissions by 0.1%. However, intensification of the design feature of the built environment in developed areas may work in the opposite direction; the modeling results showed a 1% increase in grid-like network being associated with 0.8% increase in household vehicle emissions. Based on the results, the study addressed the potential of and the challenges to reducing vehicle emissions through modifying the built environment in local areas.     

Transportation impacts of center-based telecommuting: Interim findings from the Neighborhood Telecenters Project

The transportation impacts of center-based telecommuting for 24 participants (representing 69 person-days of travel and 295 trips) in the California Neighborhood Telecenters Project are analyzed. Comparing non-telecommuting (NTC) day to telecommuting (TC) day travel shows that person-trips did not change significantly, whereas vehicle-trips increased significantly (by about one trip) on TC days. Both PMT and VMT decline significantly on TC days: by an average of 68 miles (74%) and 38 miles (65%), respectively. When these savings are weighted by the frequency of telecommuting, overall reductions in PMT and VMT come to 19% and 17%, respectively, of total weekday travel. Commute trips increase slightly (by 0.5 trips) but significantly, mainly due to lunch-time trips made home from the telecenter. Total non-commute travel does not increase, but there is a significant shift from other modes to driving alone on TC days. Commute mode split on NTC days is not affected by telecommuting. Travel on TC days tends to be compressed into fewer hours. Higher numbers of return home, eat meal, shopping, and social/recreational trips are made on TC days, in exchange for a reduction (to zero) in the number of change mode trips.     

How much can trip chaining reduce VMT? A simplified method

Trip chaining represents a way to reduce vehicle miles traveled (VMT) that does not require people to shift away from driving private automobiles. While the existing literature on trip chaining acknowledges this potential, little has been done by way of quantifying this. This research seeks to fill this gap by using a large travel survey from the San Francisco Bay area to model the VMT generated by automobile tours as a function of tour composition (i.e., the number and type of destinations on that tour). The model results indicate that many tours involving trips chains (i.e., those tours with more than one destination) generate significantly less VMT than would occur if the destinations in these tours were split into multiple tours with single destinations. Tours that combine a work and non-work destination (which are the most common types of trip chains) particularly demonstrate potential for VMT reduction. Adding a non-work destination to a work tour is usually (depending on the specific type of destination) predicted to result in a reduction of 6–11 VMT, or about 20–30 %. Adding two non-work destinations to a work tour is usually predicted to result in a reduction of 10–22 VMT, or about 25–50 %.     

The role of VMT reduction in meeting climate change policy goals

This article evaluates the case for vehicle miles traveled (VMT) reduction as a core policy goal for reducing greenhouse gases (GHGs), concluding the economic impacts and social consequences would be too severe given the modest potential environmental benefits. Attempts to reduce VMT typically rely on very blunt policy instruments, such as increasing urban densities, and run the risk of reducing mobility, reducing access to jobs, and narrowing the range of housing choice. VMT reduction, in fact, is an inherently blunt policy instrument because it relies almost exclusively on changing human behavior and settlement patterns to increase transit use and reduce automobile travel rather than directly target GHGs. It also uses long-term strategies with highly uncertain effects on GHGs based on current research. Not surprisingly, VMT reduction strategies often rank among the most costly and least efficient options. In contrast, less intrusive policy approaches such as improved fuel efficiency and traffic signal optimization are more likely to directly reduce GHGs than behavioral approaches such as increasing urban densities to promote higher public transit usage. As a general principle, policymakers should begin addressing policy concerns using the least intrusive and costly approaches first. Climate change policy should focus on directly targeting greenhouse gas emissions (e.g., through a carbon tax) rather than using the blunt instrument of VMT reduction to preserve the economic and social benefits of mobility in modern, service-based economies. Targeted responses are also more cost effective, implying that the social welfare costs of climate change policy will be smaller than using broad-brushed approaches that directly attempt to influence living patterns and travel behavior.     

Estimating vehicle miles traveled combined with ITS data

‘Vehicle miles traveled’ (VMT) is an important performance measure for highway systems. Currently, VMT [or ‘annual average daily traffic’ (AADT)] is estimated from a combination of permanent counting stations and short-term counts done at specified locations as part of the Highway Performance Monitoring System (HPMS) mandated by the US Federal Highway Administration. However, on some roadway sections, Intelligent Transportation Systems (ITS) such as detectors and cameras also produce traffic data. The question addressed in this paper is whether and under what conditions ITS systems data could be used instead of HPMS short-term counts (called ‘coverage counts’)? This paper develops a methodology for determining a threshold number of missing daily traffic counts, or alternatively, the number of valid ITS data observations needed, in order to confidently replace the HPMS coverage counts with ITS data.

Because ITS counts, coverage counts, and actual ground counts (e.g. continuous counts) cannot be found coexisting on a roadway section, it is hard to compare them directly. In this paper, the Monte Carlo simulation method is employed to generate synthetic ITS counts and coverage counts from a set of relatively complete traffic counts collected at a continuous count station. Comparisons are made between simulated ITS counts, coverage counts, and actual ground counts. The simulation results indicate that when there are<330 daily traffic counts missing in a set of ITS counts in a year, that is, when there are at least 35 days of valid data, ITS counts can be used to derive a better AADT than using coverage counts. This result is applied to calculate the VMT for the Hampton Roads region in Virginia. The comparison between the VMTs derived with using and not using the threshold number indicates that these two VMTs are significantly different.     

Fuel price elasticities for single-unit truck operations in the United States

This paper provides fuel price elasticity estimates for single-unit truck activity, where single-unit trucks are defined as vehicles on a single frame with either (1) at least two axles and six tires; or (2) a gross vehicle weight greater than 10,000 lb. Using data from 1980 to 2012, this paper applies first-difference and error correction models and finds that single-unit truck activity is sensitive to certain macroeconomic and infrastructure factors (gross domestic product, lane miles expansion, and housing construction), but is not sensitive to diesel fuel prices. These results suggest that fuel price elasticities of single unit truck activity are inelastic. These results may be used by policymakers in considering policies that have a direct impact on fuel prices, or policies whose effects may be equivalent to fuel price adjustments.     

Does telecommuting reduce vehicle-miles traveled? An aggregate time series analysis for the U.S.

. This study examines the impact of telecommuting on passenger vehicle-miles traveled (VMT) through a multivariate time series analysis of aggregate nationwide data spanning 1966–1999 for all variables except telecommuting, and 1988–1998 for telecommuting. The analysis was conducted in two stages. In the first stage, VMT (1966–1999) was modeled as a function of conventional variables representing economic activity, transportation price, transportation supply and socio-demographics. In the second stage, the residuals of the first stage (1988–1998) were modeled as a function of the number of telecommuters. We also assessed the change in annual VMT per telecommuter as well as VMT per telecommuting occasion, for 1998. The models suggest that telecommuting reduces VMT, with 94% confidence. Together with independent external evidence, the results suggest a reduction in annual VMT on the order of 0.8% or less. Even with impacts that small, when informally compared to similar reductions in VMT due to public transit ridership, telecommuting appears to be far more cost-effective in terms of public sector expenditures.     

CO2 emissions: Are land-use changes enough for California to reduce VMT? Specification of a two-part model with instrumental variables

With vehicle miles of travel increasing at a faster pace than population, one strategy being actively pursued by both state and local governments is compact development. California recently passed legislation that aggressively promotes sustainability by endorsing and rewarding compact development. Likewise, the California Air Resources Board has set a statewide reduction target of 5MMT of greenhouse gas reductions from land use, based largely on achieving compact development patterns. In this paper, we use a multivariate two-part model with instrumental variables, which corrects for residential location self-selection bias. We use a much larger and more geographically representative travel survey on household travel patterns and socio-economic characteristics than represented in previous California studies; this allows us to robustly consider other influences on travel. Our results indicate that, all else equal, a 10% in residential density would reduce VMT by 1.9%. This elasticity is larger than the reported in previous econometric studies for the US, and specifically for California. However, as we show, the magnitude of this impact is still low considering reasonable ranges for policies aimed to increase residential density.     

Policy innovations of the US intermodal surface transportation efficiency act and clean air act amendments

In combination, the Intermodal Surface Transportation Efficiency Act of 1991 (ISTEA) and the Clean Air Act Amendments of 1990 (CAAA) are innovative and aggressive efforts to move US cities toward integrated transportation and air quality planning. Under these complementary laws, air quality has become a major national transportation goal. In areas with serious air pollution, air quality will be a major consideration in determining the future shape of urban transportation.This paper considers how the CAAA and ISTEA combine to provide an innovative national policy approach of interest to countries seeking to encourage sustainable development in urban centers. The CAAA mandates measurable and enforceable air quality targets. Nation-wide standards are set for acceptable levels of carbon monoxide, ground level ozone, and small particulates. ISTEA includes directions for transportation planners and decision-makers to follow to reach air quality and other goals — transportation planning must emphasize system efficiency, and for cities with severe air pollution, transportation projects are expected to contribute to cleaner air. Each urban area has flexibility in how it applies this framework to reflect its priorities and solve its problems. Strict federal sanctions provide incentives for compliance with both laws.Enactment of these laws has produced a period of transition and uncertainty as well as of challenge and opportunity for planners and elected officials. The next several years, the US will provide one national laboratory and over 100 different urban laboratories for innovative approaches to integrate transportation and environmental policies to resolve major urban problems.Abbreviations CAAA Clean Air Act Amendments of 1990 - CO Carbon monoxide - ECO Employee Commute Option - EPA US Environmental Protection Agency - HC Transportation hydrocarbons - I/M Inspections and maintenance program - ISTEA Intermodal Surface Transportation Efficiency Act of 1991 - MPO Metropolitan planning organizations - NO_x Nitrogen oxides - PPM Parts per million - PM₁₀ Small particulate matter - SIP State Implementation Plan - TIP Transportation Improvement Program - TCM Transportation control measures - VMT Vehicle miles traveled     

Electric vehicle park-charge-ride programs: A planning framework and case study in Chicago

In suburban areas, combining the use of electric vehicles (EV) and transit systems in an EV Park-Charge-Ride (PCR) approach can potentially help improve transit accessibility, facilitate EV charging and adoption, and reduce the need for long-distance driving and ensuing impacts. Despite the anticipated growth of EV adoption and charging demand, PCR programs are limited. With a focus on multi-modal trips, this study proposes a generic planning process that integrates EV infrastructure development with transit systems, develops a systematic assessment approach to fostering the PCR adoption, and illustrates a case implementation in Chicago. Specifically, this study develops a Suitability Index (SI) for EV charging locations at parking spots that are suitable for both EV charging and transit connections. SI can be customized for short-term and long-term planning scenarios. SI values are derived in Chicago as an example for (1) commuter rail stations (for work trips), and (2) shopping centers near transit stops as potential opportunities for additional weekday parking and EV charging (for multi-purpose trips/MPT). Furthermore, carbon emissions and vehicle miles travelled (VMT) across various travel modes and trip scenarios (i.e., work trips and MPT) are calculated. Compared to the baseline of driving a conventional vehicle, this study found that an EV PCR commuter can reduce up to 87% of personal VMT and 52% of carbon emissions. A more active role of the public sector in the PCR program development is recommended.     

The revenue and environmental benefits of new off-peak commuter rail service: the case of the Pascack Valley line in New Jersey

Although researchers have long argued in favor of off-peak transit service, studies that have empirically estimated its benefits regarding revenue generation, trip diversions, and greenhouse gas (GHG) emission are rare. This study provides important evidence about the benefits of off-peak commuter rail service by focusing on the Pascack Valley line in New Jersey, where off-peak service was introduced in October 2007. The research involved two focus groups and an onboard survey of passengers. Benefits were estimated regarding additional revenue generation and reduction in vehicle miles traveled (VMT) and GHG emission. The research shows that the new off-peak service potentially reduced VMT by more than 12 million annually due to diversions from other modes. Although diversions from other modes resulted in a substantial reduction in GHG emissions, due to the additional diesel fuel used by the new trains, the net GHG savings were in the range of 28–49 %. The research further shows that both peak period and off-peak riders benefited from the new off-peak service. Evidence is found about an increase in new transit riders and a modest increase peak period usage because of the off-peak service.