conference paper
conference paper
MS Thesis
This dissertation comprises two essays that study normative environmental policy and the purported side effects of (already enacted) environmental policies. In the first essay, we analyze the management of a stock pollutant in a simplified economy using optimal control. The level of stock pollutant affects utility negatively and it may trigger a catastrophic event when it hits a predetermined threshold, which results in a sudden drop in utility. A numerical illustration for the case of global climate change shows that decision maker can delay the onset of a catastrophe by increasing abatement (by investing into green capital); and by improving the environmental performance of production technology. This delaying effect can be amplified by using both policy instruments in tandem. We also observe that the time to catastrophe slightly increases with a decrease in discounting factor; an increase in the amount of catastrophic damage and a decrease in post-catastrophe capital prices. The time period from 1979 to 2003 saw the emergence of Corporate Average Fuel Economy (CAFE) standards, fluctuating and then stabilizing gasoline prices, and an increased share of light trucks. In the second essay, we analyze the alleged causality of this increased share by the introduction of fuel economy standards. We estimate the market demand for fuel economy of domestic cars and light trucks using a polynomial lag model. The main result of this essay is that the rising share of light trucks in the new domestic vehicle sales can be attributed to the increase in personal incomes during the 25 years considered, aided by the provision of laxer fuel economy standards for light trucks. Moreover, the fuel economy standards did increase the fuel efficiency of domestic vehicles.
working paper
Transit operator absence from work is a costly and pervasive problem within public transport organizations. This paper reviews over forty international studies in order to document significant factors related to this phenomenon. We begin with a brief assessment of the magnitude and costs of operator absence and isolate two major theories which have been proposed to explain operator absence behavior: the income-leisure tradeoff and occupational stress. Case study reports from three U.S. public transport organizations are used to illustrate the range of factors which influence employee absence behavior. We conclude with suggestions for organizational changes which may serve to reduce operator absence and suggestions for further research.
conference paper
conference paper
Ramp metering on freeways is one, among many others, application in which a proportional-integral (PI)-Controller has been successfully used to keep the system at a desired state. However, the design becomes challenging if the system presents a dead time restricting the stability region and affecting performance. The cause of the dead time is the distance between the on-ramp and the lane drop. A change in the control action affects the system after the time taken to vehicles travel this distance. There are a vast literature in the control theory addressing the effects of dead time and techniques to overcome it, but it is not to ramp metering control. In this study, a dynamic model of the system is presented along with ALINEA, an established Ramp Metering control algorithm based on a PI-Controller. The authors show that by incorporating a Smith Predictor into ALINEA, the stability region becomes larger, insensitive to the dead time, and can be found analytically. Numerical experiments confirm the analysis and that the proposed controller still presents a larger stability region even when there are modeling errors, allowing a faster response to disturbance.
working paper
Reducing vehicle emissions levels is particularly important in the South Coast Air Basin of California, which includes the Los Angeles Metropolitan Area and the adjacent and interdependent Orange County, Riverside, and San Bernardino Metropolitan Areas. The climate and topography create ideal conditions for the area’s infamous smog; and cars, trucks and buses contribute 88 percent of carbon monoxide emissions and about 50 percent of the ozone components: oxides of nitrogen and reactive organic gases. It is apparent that air quality can be greatly improved if gasoline-powered personal vehicles can be replaced in substantial numbers by vehicles powered by electricity or alternative fuels, such as methanol, ethanol, propane, or compressed natural gas (CNG) (see Sperling, 1988 and National Research Council, 1990, for discussions of the environmental factors associated with specific alternative fuels). While none of these alternative fuels has zero-level emissions (even electricity, if generation is taken into account), they all have lower overall emissions levels than currently available gasoline and diesel fuels; they are considered “clean” fuels for the purposes of this market research study. Personal vehicles are defined for the purposes of the study to be cars or light trucks owned or leased by private individuals. The objective of this study is to determine the effect on personal vehicle purchase and fuel use of a few important attributes that potentially differentiate clean-fuel vehicles from conventional gasoline or diesel vehicles. By concentrating on quantitative estimation, it is intended that this study complement others aimed at qualitative assessments of the roles of information and uncertainty in consumer acceptance of clean-fuel vehicles (e.g., Turrentine and Sperling, 1991).
Phd Dissertation
A method for accurate emissions estimation that will contribute to promoting public health has been increasingly important. The purpose of this study is to develop a novel method that is designed to make accurate real-time emissions estimation from individual vehicles on freeways possible. The benefit of this method is that it can overcome the weakness of macroscopic emissions estimation methods, which underestimated emissions. The most distinguishing feature of the Speed Profile Estimation (SPE) method is that it uses a speed profile (SP) that is generated by the sum of a basic SP (BSP), which is calculated by the basic travel information of an individual vehicle obtained from vehicle reidentification (REID), and a residual SP (RSP), which is estimated by categorized traffic information. In order to estimate RSP this research employs Autoregressive (AR) model and Fourier series (FS). And to find the parameters of RSP, the total absolute difference between actual SP emissions and estimated SP emissions was optimized by genetic algorithm. For this, parameters are calculated for all possible combinations of three categorizations and clusters by K-mean clustering. Individual vehicle trajectories from two freeways, US101 and I-80, were provided by the Next Generation Simulation (NGSIM) dataset. US101 was examined for calibration, and I-80 for validation. And then, transferability tests were conducted for various section distances to verify model transferability. Finally, REID is simulated with low vehicle signatures match rates to test its applicability to real situations. Unlike previous methods, the SPE is notable for its real-time, transferable, reliable, and cost efficient emissions estimation. The calibration and validation account only 4.0 % and 4.1 % MAPEs, respectively. Moreover, transferability tests showed that MAPEs are lower than 4.4 % in both longer and shorter section distances. Furthermore, REID simulation increases only 0.2 % MAPE even in low vehicle signatures match rates, which is lower than 5 % MAPE in emissions estimation. Any signal-like formulation other than AR or FS can perform better emissions estimation when it replaces the RSP. Also, in this research the SPE method was calibrated only for LOS F, when it is arguably of greatest value, but further research should be coordinated to extend the models in other possible traffic conditions such as LOS ÃE.
published journal article
research report
This report presents a method to investigate the operational and environmental effects of the policy of allowing qualified single-occupancy hybrid vehicles to use dedicated High-Occupancy Vehicle (HOV)/carpool lanes in California.. The method combines the traditional planning method with microscopic simulation modeling. The planning method is used for demand estimation and analysis and the microscopic traffic simulation modeling method is used for accurate measures of the system. The study employs a microscopic traffic simulation model that is capable of evaluating the HOV/hybrid system and providing detailed outputs that are not available in conventional static models. The study also includes detailed emissions modeling in order to estimate accurate emissions by integrating emission models into microscopic simulation models. An important aspect of the study involves predicting future hybrid vehicle demand; hybrid demand models are developed based on consumers’ automobile choice behavior analysis. This is modeled both with standard network calculations employing network assignments sensitive to time savings from HOV lane use as well as using estimates of the locations of households owning hybrid vehicles and the O-D matrices for the hybrid drivers. We use these results to modify existing models to enhance their accuracy for hybrid vehicles. The updated models are then be applied to data from the recent Caltrans 2000-2001 Statewide Household Travel Survey and the 2001 National Household Travel Survey (NHTS). These survey data allow us to locate the households and trip destinations of likely hybrid vehicle owners. Results from previous studies of demand for toll lanes have established monetary values of saved travel time that can be applied to estimated time savings from network simulations to forecast incentives for purchase of hybrid vehicles. We also develop a supply-side model to estimate availability and prices of hybrid vehicles by body type and manufacturer and price in order to forecast penetration of hybrid vehicles. A total of four different scenarios were constructed. With the assumption that the total demand for all scenarios remains the same and the hybrid-HOV policy results in some solo drivers switching to hybrid vehicle drivers, these four scenarios are evaluated in terms of a set of operational performance measures and air quality measures. The key findings from this study are summarized as follows:•The initial wave of single occupant hybrid vehicles entering the HOV lanes do not have a substantial negative impact on HOV lane operations.•A hybrid demand exceeding 50 thousand statewide will have significant impact on the HOV lane operations in OC.•From the air quality perspective, a high share of hybrid vehicles will cause fewer emissions.