published journal article
conference paper
conference paper
Advances in the automobile industry and intelligent transportation systems in the recent decade have made what was once a dream, driver-less vehicles, closer than ever to reality now. Although autonomous vehicles introduce many benefits ranging from decreasing delay to higher levels of safety on roads, they will be priced relatively high once they enter the market. The high price and the consequent low demand may translate to less motivation for the automobile industry to move toward mass production, and it could take decades for the market to reach equilibrium. In this paper, the authors describe formulations for analyzing shared ownership and use of autonomous vehicles as well as some variants that they newly propose. Households interested in participating in the program will join together, forming clusters of households. Each cluster will share the ownership of a set of autonomous vehicles. The program also allows participants to rideshare together. Such a program will decrease the number of vehicles needed by households, and will therefore make the ownership of autonomous vehicles more economical. In addition, clusters of households can register their vehicles in a carsharing program when they are not being used, in order to partially cover the ownership cost. The authors implement this program for a sample of households in San Diego, California, and discuss the reduction in vehicle ownership as a result of participating in the program.
working paper
Air quality in Southern California and elsewhere could be substantially improved if some gasoline powered personal vehicles were replaced by vehicles powered by electricity or alternative fuels, such as methanol, ethanol, propane, or compressed natural gas. Quantitative market research information about how consumers are likely to respond to alternative-fuel vehicles is critical to the development of policies aimed at encouraging such technological change. In 1991, a three-phase stated preference (SP) survey was implemented in the South Coast Air Basin of California to predict the effect on personal vehicle purchases of attributes that potentially differentiate clean-fuel vehicles from conventional gasoline (or diesel) vehicles. These attributes included: limited availability of refueling stations, limited range between refueling or recharging, vehicle prices, fuel operating costs, emissions levels, multiple-fuel capability, and performance. Respondents were asked to choose one vehicle from each of five sets of hypothetical clean-fuel and conventional gasoline vehicles, each vehicle defined in terms of attributes manipulated according to a specific experimental design. Discrete choice models, such as the multinomial logit model, are then used to estimate how the values of the attribute levels influence purchase decisions. The SP survey choice sets were customized to each respondent’s situation, as determined in the preceding Phase of the survey. The final Phase of the survey involved fuel-choice SP tasks for multi-fuel vehicles that can run on either clean fuels or gasoline. Preliminary results from a pilot sample indicate that the survey responses are plausible and will indeed be useful for forecasting.
published journal article
This paper presents an analysis of the perceptions held by for-hire and private trucking company logistics and operations managers about the impacts of congestion on their operations and the feasibility and effectiveness of actual and potential congestion mitigation policies. Responses to an extensive survey of nearly 1200 California-based or large national carriers are examined using confirmatory factor analysis. The method applied facilitates both the grouping of congestion relief policies into classes and the identification of characteristics of companies which lead them to favor one set of policies over others. This research comes at a time when California government leaders and transportation policy analysts are struggling with key resource allocation issues that will impact the short and long term future of goods movement in the state. To the greatest extent possible, insights of commercial vehicle operations users of the transportation network should be included in the policy analysis process. (C) 1999 Elsevier Science Ltd. All rights reserved.
published journal article
conference paper
published journal article
published journal article
The vehicle miles of travel for each vehicle in multi-vehicle households is modelled as a function of household characteristics, vehicle characteristics, and the matches of vehicle to driver in the satisfaction of travel desires. A structural equations model is developed in which principal driver characteristics, as well as vehicle miles of travel, are endogenous. There are links between how each vehicle is used and who in the household is each vehicle’s principal driver. Each vehicle’s usage can then be expressed in reduced-form equations as a function of exogenous household and vehicle type variables for forecasting purpose’s. The model is estimated on a 1993 sample of approximately 2000 multi-vehicle households in California.
conference paper
The high complexity of cross-domain engineering in combination with the pressure for product innovation, higher quality, time-to-market, and budget constraints make it imperative for companies to use integrated engineering methods and tools. Computer engineering tools are mainly focused on a particular domain and therefore it is difficult to combine different tools for system-level analysis. This paper presents a novel approach and tool for integrated cyber-physical systems (CPS) design based on the FBS (Function-Behavior-State) methodology where multi-domain simulation models capturing both the behavioral-structural aspects of a system are automatically generated from its functional description. Our approach focuses on simulation-enabled FBS models using automatic and context-sensitive mappings of standard Functional Basis elementary functions to simulation components described in physical modeling languages (i.e. Modelica). Using a real electromechanical CPS application we demonstrate how our context-sensitive synthesis approach generates industry-quality executable functional models of higher quality than state-of-the-art approaches using manual mapping.