The body of this dissertation comprises two standalone essays, presented in two respective chapters.

Chapter One develops estimates of how motorists value their travel-time savings and characterizes the degree of heterogeneity in these values by observable traits. These estimates are obtained by analyzing the choices that commuters make in a real market situation, where they are offered a free-flow alternative to congested travel. They are generated, however, in an empirical setting where several key observations are missing. To overcome this, Rubin’s Multiple Imputation Method is employed to produce consistent estimates and valid statistical inferences. These estimates are then compared to those produced in a “single imputation” scenario to illustrate the potential hazards of single imputation methods when multiple imputation methods are warranted. A preferred model suggests that the median commuter is willing to pay $30 to save an hour of travel time. However, taking observed heterogeneity into account, median estimates range from $7 to $65 according to varying, observable motorist characteristics.

Chapter Two develops a theoretical framework for jointly modeling the marginal external accident and travel-delay costs of driving. The framework explicitly accounts for the optimal tradeoffs that motorists make between accident risk and risk-reducing effort. Accident and travel-delay externalities are decomposed into components that correspond to physical accident risk, efforts to offset this risk, and their effects on travel times. An empirical model is developed from this framework, suggesting that joint external costs are $1.80 per vehicle-mile and external accident costs are $0.80 per vehicle-mile during a typical peak-period commute. The analysis does not require observations on accident rates and illustrates how the commonly-adopted approach to modeling accident externalities tends to understate these costs.

We estimate how motorists value their time savings and characterize the degree of heterogeneity in these values by observable traits. We obtain these estimates by analyzing the choices that commuters make in a real market situation, where they are offered a free-flow alternative to congested travel. We do so, however, in an empirical setting where several key observations are missing. To overcome this, we apply Rubin’sMultiple ImputationMethod to generate consistent estimates and valid statistical inferences. We also compare these estimates to those produced in a "single imputation" scenario to illustrate the potential hazards of single imputation methods when multiple imputation methods are warranted. Our results show the importance of properly accounting for errors in the imputation process, and they also show that value of time savings varies greatly according to motorist characteristics.

We estimate how motorists value their time savings and characterize the degree of heterogeneity in these values by observable traits. We obtain these estimates by analyzing the choices that commuters make in a real market situation, where they are offered a free-flow alternative to congested travel. We do so, however, in an empirical setting where several key observations are missing. To overcome this, we apply Rubin’s Multiple Imputation Method to generate consistent estimates and valid statistical inferences. We also compare these estimates to those produced in a "single imputation" scenario to illustrate the potential hazards of single imputation methods when multiple imputation methods are warranted. Our results show the importance of properly accounting for errors in the imputation process, and they also show that value of time savings varies greatly according to motorist characteristics.

The potential for zero emission heavy duty trucks (ZEHDTs) is examined via simulation modeling, case studies, interviews and a survey. Impacts of ZEHDTs on freight operations are assessed. Costs and benefits of using diesel, natural gas hybrid and battery electric vehicles are compared for 2020, 2025, 2030. ZE applications are limited in the near term due to range and charging limitations, but as ZE performance improves and prices go down, they are viable for a larger segment of the market. Hybrid vehicles are the most cost effective alternative for reducing air toxics, but ZEHDTs reduce air toxics the most by 2025. The report presents recommendations for promoting and increasing the market share of ZEHDTs and hybrids.

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California is pursuing multiple policies to spur the transition to a cleaner heavy-duty vehicle fleet. Achieving these targets will require massive change in the heavy-duty short-haul industry, and many unanswered questions remain. How do battery-electric heavy-duty trucks compare to diesel in everyday short-haul operations? How much would it cost to transition to a zero-emission truck fleet, and who would pay?

To begin to answer these questions, researchers at the National Center for Sustainable Transportation conducted a comprehensive analysis of the potential for zero-emission or near-zero-emission heavy-duty trucks to be used in short-haul drayage services. The researchers considered operational, economic, and environmental impacts through simulation modeling, interviews, case studies, stated preference surveys, and cost-effectiveness analyses.

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