Highway capital expenditures and induced vehicle travel

We investigate the effects of public capital investment on the demand for travel. We define capital stock as a productive flow that accounts for the physical deterioration of infrastructure over time. We present a framework where additions to capital stock only cover a portion of the long-run equilibrium level, and where policy decisions are dictated by expectations of economic and travel growth. To the extent that these investments increase productivity, they generate induced travel. Using a panel dataset at the state level for the period 1982-2005, we find that the elasticity of travel demand with respect to changes in state highway capital stock is equal to 0.041in the short run, while the long-run is 0.237. Our results show that changes in capital expenditures in response to past levels of traffic are characterized by a three-year lag, suggesting that the investment response to changes in travel is slow to converge to the desired long-run levels

Highway capital expenditures and induced vehicle travel

We investigate the effects of public capital investment on the demand for travel. We define capital stock as a productive flow that accounts for the physical deterioration of infrastructure over time. We present a framework where additions to capital stock only cover a portion of the long-run equilibrium level, and where policy decisions are dictated by expectations of economic and travel growth. To the extent that these investments increase productivity, they generate induced travel. Using a panel dataset at the state level for the period 1982-2005, we find that the elasticity of travel demand with respect to changes in state highway capital stock is equal to 0.041in the short run, while the long-run is 0.237. Our results show that changes in capital expenditures in response to past levels of traffic are characterized by a three-year lag, suggesting that the investment response to changes in travel is slow to converge to the desired long-run levels

The Interaction Between Urban Form and Transit Travel

This study presents an analytical model of the interaction between urban form and the demand for transit travel, in which residential location, transit demand, and the spatial dispersion of non-work activities are endogenously determined. In this model, travel demand is considered a derived demand brought about by the necessity to engage in out-ofhome activities whose geographical extent is affected by urban form. In a departure from the urban monocentric model, residential location is defined as a job-residence pair in an urban area in which jobs, residences, and non-work activities are dispersed. Transit demand is then determined by residential location, work trips, non-work trip chains, and goods consumption. Theoretically derived hypotheses are empirically tested using a dataset that integrates travel and land-use data. There is evidence of a significant influence of land-use patterns on transit patronage. In turn, transit demand affects consumption and non-work travel. Although much reliance has been placed on population density as a determinant of transit demand, it is found here that population density does not have a large impact on transit demand and, moreover, that the effect decreases when residential location is endogenous. To increase transit use, urban planners have advocated a mix of residential and commercial uses in proximity to transit stations. In this study, it is found that the importance of transit-station proximity is weakened by idiosyncratic preferences for residential location. In addition, when population density and residential location are jointly endogenous, the elasticity of transit demand with respect to walking distance to a transit station decreases by about 33 percent over the case in which these variables are treated an exogenous. The research reported here is the first empirical work that explicitly relates residential location to trip chaining in a context in which individuals jointly decide residential location and the trip chain. If is found that households living farther from work use less transit and that trip-chaining behavior explains this finding. Households living far from work engage in complex trip chains and have, on average, a more dispersed activity space, which requires reliance on more flexible modes of transportation. Therefore, reducing the spatial allocation of non-work activities and improving transit accessibility at and around subcenters would increase transit demand. Similar effects can be obtained by increasing the presence of retail locations in proximity to transit-oriented households. Although focused on transit demand, the framework can be easily generalized to study other forms of travel

Synthesis of research on value of time and value of reli

The objective of this study is to compile and synthesize current and past research on the value of time (VOT) and the value of reliability of time (VOR). Findings are summarized into an application-oriented document to provide practitioners with applicable ranges of estimates that can be used in project evaluations

Integrating Transit and Urban Form

This study develops an integrated behavioral model of transit patronage and urban form. Although herein focused on transit, the framework can be easily generalized to study other forms of travel. Advanced econometric methods are used to test specific behavioral hypotheses developed in the theoretical models. Findings are then summarized in a succinct fashion showing relevance and magnitude of the impact of land use on transit demand. The empirical models also quantify these relationships in the form of point elasticity estimates that can be used as indicators of the relevance of transit supply measures. This work summarizes the study results, an exposition of the methodology and tables that lay out the findings in a readily accessible format

The Effect of Density and Trip-Chaining on the Interaction between Urban Form and Transit Demand

It is unclear whether policies designed to reduce auto and increase transit usage achieve their objective. Evidence is mixed because most empirical research on these policies use ad hoc specifications, whereas our models are drawn from economic theory. Three models of increasing generality show how endogenizing relevant variables changes results obtained by others. The theoretical hypotheses are empirically tested using a dataset that integrates travel and land use. Our main findings are (1) population density has a small impact on transit demand, which decreases when residential location is endogenous; (2) households living farther from work use less transit, a result of trip-chaining; and (3) reducing the spatial allocation of non-work activities, improving transit accessibility at and around subcenters, and increasing the presence of retail locations in proximity to transit-oriented households would increase transit demand

Quantifying the Net Social Benefits of Vehicle Trip Reductions: Guidance for Customizing the TRIMMS© Model

This study details the development of a series of enhancements to the Trip Reduction Impacts of Mobility Management Strategies (TRIMMS©) model. TRIMMS© allows quantifying the net social benefits of a wide range of transportation demand management (TDM) initiatives in terms of emission reductions, accident reductions, congestion reductions, excess fuel consumption and adverse global climate change impacts. The model includes a sensitivity analysis module that provides program cost-effectiveness assessment. This feature allows conducting TDM evaluation to meet the Federal Highway Administration Congestion and Air Quality (CMAQ) Improvement Program requirements for program effectiveness assessment and benchmarking. This document provides guidance to help TDM professionals to use the model by selecting the appropriate cost parameters, providing referenced sources where to obtain such parameters, and by offering general guidance on how to incorporate data already at their disposal

Estimating Costs and Benefits of Emissions Reduction Strategies for Transit by Extending the TRIMMS Model

This study details the development of a series of improvements to the Trip Reduction Impacts of Mobility Management Strategies (TRIMMS™) model. TRIMMS now estimates a wider range of emission pollutants and incorporates a new module that evaluates the impact of land use strategies on transit patronage. TRIMMS uses the emission inventory of the Environmental Protection Agency Motor Vehicle Emission Simulator (MOVES2010a), which makes it suitable to run official State implementation air quality plan (SIP) and regional emissions analyses for transportation conformity purposes. This model enables the Florida Department of Transportation (FDOT), transit agencies, Metropolitan Planning Organizations (MPO) and local communities to conduct cost-benefit assessments for most of the strategies identified in the FDOT-sponsored Transit Ozone-Reduction Strategies Toolbox, without the cost and expertise required by more sophisticated models

Economics of Travel Demand Management: Comparative Cost Effectiveness and Public Investment

The 2006 Congestion Mitigation and Air Quality Improvement (CMAQ) Program Interim Guidance provides explicit guidelines to program effectiveness assessment and benchmarking by calling for a quantification of benefits, as well as disbenefits, resulting from emission reduction strategies for project selection and evaluation. The objective of this study is to develop a methodology that combines academic and practitioner experiences within a theoretical framework that truly captures consumers’ price responsiveness to diverse transportation options by embracing the most relevant trade-offs faced under income, modal price and availability constraints. The development of the theoretical model leads to the design and implementation of TRIMMS (Trip Reduction Impacts for Mobility Management Strategies), a practitioner oriented sketch planning tool. TRIMMS permits program managers and funding agencies like the Florida Department of Transportation (FDOT) to make informed decisions on where to spend finite transportation dollars based on a full range of benefits and costs. The approach is consistent with other benefit to cost analyses. Its accuracy and the perceived fairness are critical when significant funds are at stake. The model allows some regions to use local data or opt to use defaults from national research findings, select the benefits and costs of interest, and calculate the costs and benefits of a given program. A step by step introduction to the program, its capabilities, and a set of working examples to guide the user through the process of evaluation is included in the report. A key strength of this model is its wide range of benefits and costs that can be selected for the analysis. The model’s flexibility and robustness allows it to be adopted by agencies throughout the country. Future research could seek to enhance the model to include more of the internal benefits to employers (e.g., changes in worker productivity, reduction in overhead, changes in employee retention, etc.). A byproduct of this research effort that goes beyond the initial project objectives is the development of a structured approach to evaluate the impact of soft programs. Compared to the currently available soft program evaluation methods, the approach developed in this report provides a less heuristic method of estimation resulting in statistically robust mode share impact predictions. Another future area of analysis would be the refinement of such models to provide a standardized approach to soft program impact assessment