policy brief
An activity-based modeling toolbox was produced for planning
agencies to investigate the effects certain policies have on travel
demand.
conference paper
The emergence of supply-side competition in the advanced traveler information system (ATIS) industry and marketability of private ATIS service are examined. An architectural model in which the ATIS companies collect network information from their subscribers while providing them with real-time traffic information is described. A simulation study on competition and cooperation among multiple private and public information agencies follows. This study focuses on analyzing the interaction among information agencies and the effect of this interaction on traffic system performance.
MS Thesis
The driving factors for pursuing alternative fuels stem from energy issues associated with fossil based sources. In particular, such sources are finite in quantity, foreign sourced, and directly emit both greenhouse gasses (GHGs) and criteria pollutants during their utilization. In California, the transportation sector is in the lead for the consumption of overall energy by sector, with passenger vehicles emitting the most GHGs out of the entire transportation sector. Motivated by the large body of legislation and the complex nature of the potential alternative fuel supply chains, the goal of this work is to examine hydrogen as an alternative transportation fuel. To this end, a computer model was developed that allows for the systematic selection of preferred hydrogen supply chains. The goals of this thesis are to: 1) Establish spatially and temporally resolved generation, distribution, dispensing, and utilization scenarios for fueling the hydrogen transportation sector based on a systematic selection technique, and 2) Quantify the environmental impacts, and energy requirements in comparison to the current supply of petroleum fuels. The modeling approach developed herein, the Hydrogen Fueling infrastructure tool (HFit), takes a global decision-making approach to the creation and evolution of a future hydrogen infrastructure. In order to exercise the HFit, several case studies were conducted with different decision-making datasets. The outputs allowed for the simulation and quantification of a future hydrogen economy within the state of California on a spatial and temporal basis.
published journal article
published journal article
published journal article
Evacuation mode choice has been researched over the past decade for disaster management and planning, focusing primarily on established modes such as personal automobiles, carpooling, and transit. Recently, however, on-demand ridesourcing has become a viable mode alternative, most notably through the growth of major transportation network companies, such as Uber and Lyft. The availability of this new transportation option is expected to have important implications for adaptive disaster response. The goal of this work is to investigate the influence of internal and external contextual factors on preferred ridesourcing applications during small-scale urban evacuations. A case study was conducted in the three most populous metropolitan areas in the United States. Data were collected using an internet-based stated preference survey, and a discrete choice model was estimated to analyze the 185 responses. Determinants of on-demand ridesourcing for evacuation include internal factors, such as interactions between race, gender, and income, and external contextual factors, such as the evacuation notification source, consequence severity, immediacy, evacuation distance, unfamiliarity of surroundings, and traveling with others. Findings are illustrated through three ridesourcing applications based on specific evacuation needs. Policy recommendations are provided for the design of equitable evacuation services, soft policy communication strategies, and public-private partnerships.
book/book chapter
working paper
A study was conducted to determine how demand for clean-fuel vehicles and their fuels is likely to vary as a function of attributes that distinguish these vehicles from conventional gasoline vehicles. For the purposes of the study, clean-fuel vehicles are defined to encompass both electric vehicles, and unspecified (methanol, ethanol, compressed natural gas or propane) liquid and gaseous fuel vehicles, in both de or multiple-fuel versions. The attributes include vehicle purchase price, fuel operating cost, vehicle range between refueling, availability of fuel, dedicated versus multiple-fuel capability, and the level of reduction in emissions (compared to current vehicles). In a mail-back stated preference survey, approximately 700 respondents in the California South Coast Air Basin gave their choices among sets of hypothetical future vehicles, as well as their choices between alternative fuel versus gasoline for hypothetical multiple-fuel vehicles. Estimates of attribute importance and segment differences are made using discrete-choice nested multinomial logit models for vehicle choice, and binomial logit models for fuel choice. These estimates can be used to modify present vehicle-type choice and utilization models to accommodate clean-fuel vehicles; they can also be used to evaluate scenarios for alternative clean-fuel vehicle and fuel supply configurations. Results indicate that range between refueling is an important attribute, particularly if range for an alternative fuel is substantially less than that for gasoline. For fuel choice, the most important attribute is fuel cost, but the predicted probability of choosing alternative fuel is also affected by emissions levels, which can compensate for differences in fuel prices.
published journal article
published journal article