2013 Session: 833

• Fuel Use and Optimality of Assignments in Multivehicle Households: Trends from 2001 to 2009
  Abstract: Multi-vehicle household fleets are often composed of vehicles with a wide range of attributes, including passenger and cargo capacities, towing capability, and fuel consumption. Decisions for how these vehicles are assigned to trips can have a significant impact on a household’s total fuel use. In this paper, actual vehicle assignments from the 2001 and 2009 NHTS data are compared to the fuel use-minimizing decisions using CTRAM — a model which determines optimal vehicle-to-trip assignments considering constraints on vehicle availability and capability.Results show that the average potential reduction in fuel use through optimal assignment for multi-vehicle households was 10.9% in 2001 and 10.2% in 2009. However, the increase in assignment optimality that is seen in this period does not appear to be the result of a greater prevalence of active, short-term vehicle assignment decisions, such as a driver’s voluntary use of a non-preferred vehicle, or switching vehicles mid-day. This finding provides evidence that the higher level of assignment optimality in 2009 was influenced by other, possibly longer-term decisions, such as considering fuel consumption in purchase decisions according to the primary driver’s expected usage of the vehicle (e.g. a small, efficient vehicle for long-distance work commuting). The significance of this conclusion is reinforced by the finding that increases in assignment optimality are smaller in lower income households, possibly due to the lack of efficient vehicles in the secondary market in the years preceding the 2009 survey.
  Authors: Bolon, Kevin; Keoleian, Greg; Kostyniuk, Lidia P.
  Authors: Bolon, Kevin; Keoleian, Greg; Kostyniuk, Lidia P.
  Year: 2013
  Document Type: Paper
  Subject: Planning and Forecasting
  Session: 833
  Paper Number: 13-3159
• Design Matters: Early Results from Field Experiment of Fuel Economy Feedback
  Abstract: Energy feedback to drivers is one method to engage drivers in energy saving driving styles. In contrast to the occasional broadcasting of general driving tips, in-vehicle energy feedback gives drivers access to accurate information about their specific driving situation on an ongoing basis. The increasing prevalence of such feedback in new vehicles suggests a belief that ongoing, in-vehicle feedback is better. However, there is little reliable evidence of the effectiveness of energy feedback in real-word driving in passenger vehicles. This study begins to fill this gap. Participants are given a commercially-available fuel consumption display and recording device to use in their personal vehicle for two months. For the first month the display is blank as the device records a baseline of driving and fuel consumption. For the second month the display is switched on to show drivers one of three feedback designs. This paper presents preliminary results (N=36) of a larger study that will include 150 drivers along the California-Nevada Interstate-80 corridor. Using a mixed-effects linear model, we find an average decrease of between 2% and 8% in fuel consumption (gallons/100 miles) between the without- and with-feedback months, depending on the feedback designs. Categorizing trips into types based on distance and multiple speed characteristics, there are differences in the apparent effectiveness of feedback across trip types. Most trips average approximately 5% reduction in fuel consumption. The long distance highway trip type showed only a 1% decrease in fuel consumption between the two study periods.
  Authors: Stillwater, Tai; Kurani, Kenneth S.
  Authors: Stillwater, Tai; Kurani, Kenneth S.
  Year: 2013
  Document Type: Paper
  Subject: Planning and Forecasting
  Session: 833
  Paper Number: 13-4112
• Accommodating Immigration Status and Self-Selection Effects in Joint Model of Household Auto Ownership and Residential Location Choice
  Abstract: As the proportion of immigrants in the US population continues to rise, it is becoming increasingly important to understand their residential location choices and travel behavior in the travel modeling and transportation policy making arena. This paper presents a joint model of residential location choice and auto ownership that explicitly accounts for immigration status and length of stay in the United States as explanatory variables. In addition, the joint model accommodates error correlations across the choice dimensions thus accounting for residential self-selection effects that may arise from unobserved preferences. The model takes the form of a bivariate multinomial probit (MNP) model and is estimated using the computationally tractable maximum approximate composite marginal likelihood (MACML) approach on a San Francisco Bay Area subsample of the 2009 National Household Travel Survey (NHTS). Model estimation results show that immigration and length of stay are significant explanatory variables in both residential location choice and auto ownership, with immigrants displaying assimilation effects, i.e., they increasingly resemble non-immigrant households as the length of stay increases. Even after controlling for immigration effects and including residential location choice as an explanatory variable in the auto ownership model, it is found that there are significant self-selection effects that are likely to dampen estimates of the impacts of land use changes on travel behavior in policy forecasts. The paper demonstrates the need to account for immigration variables and self-selection effects in transportation forecasting models that inform policy decisions.
  Authors: Paleti, Rajesh; Pendyala, Ram M.; Bhat, Chandra R.; Lorenzini, Karen Marie; Konduri, Karthik Charan
  Authors: Paleti, Rajesh; Pendyala, Ram M.; Bhat, Chandra R.; Lorenzini, Karen Marie; Konduri, Karthik Charan
  Year: 2013
  Document Type: Paper
  Subject: Planning and Forecasting
  Session: 833
  Paper Number: 13-4335
• Calculating Potential Emission Reductions Through Introduction of Electric Vehicles
  Abstract: Electric vehicles are expected to significantly reduce road transport emissions, given an increasingly renewable power generation. While technological issues are more and more being overcome, the economic viability and thus possible adoption is still constrained, mainly by higher prices than for conventional vehicles. However, first vehicles have been available on the market for some time now and many more are expected to arrive soon and at decreasing cost.In our work we analyze the possible market development for electric vehicles with an application to Germany. We develop a drivetrain choice model with economical, technical and social constraints on the current vehicle registrations and inventory. It estimates the demand for electric vehicles until 2030 for private and commercially registered cars as well as light commercial vehicles.The results show a replacement potential of more than one fourth of the total German annual mileage for these vehicles. The result has a high granularity to allow for detailed emission calculation along different spatial areas as well as vehicle and engine types. Besides a baseline forecast, our method allows for calculating different scenarios regarding policy actions or the future development of important parameters such as energy prices. The results provide insights for policy measures as well as for transport and environmental modeling.
  Authors: Kihm, Alexander; Trommer, Stefan; Mehlin, Markus
  Authors: Kihm, Alexander; Trommer, Stefan; Mehlin, Markus
  Year: 2013
  Document Type: Paper
  Subject: Planning and Forecasting
  Session: 833
  Paper Number: 13-3871
• An Integrated Model of Residential Location, Work Location, Vehicle Ownership, and Commute Tour Characteristics
  Abstract: This paper offers an econometric model system that simultaneously considers six different activity-travel choice dimensions in a unifying framework. The six dimensions include residential location choice, work location choice, auto ownership, commuting distance, commute mode, and number of stops on commute tours. The paper presents the modeling methodology in detail as well as estimation results for a joint model system estimated on a data set extracted from the 2009 National Household Travel Survey. Estimation results show substantial presence of correlated unobserved effects (self-selection) across choice dimensions, underscoring the value offered by joint equations model systems in the travel modeling field.
  Authors: Paleti, Rajesh; Bhat, Chandra R.; Pendyala, Ram M.
  Authors: Paleti, Rajesh; Bhat, Chandra R.; Pendyala, Ram M.
  Year: 2013
  Document Type: Paper
  Subject: Planning and Forecasting
  Session: 833
  Paper Number: 13-4783
• Fuel Use and Optimality of Assignments in Multivehicle Households: Trends from 2001 to 2009
  Authors: Bolon, Kevin
  Authors: Bolon, Kevin
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 833
  Paper Number: 13-3159
• Design Matters: Early Results from Field Experiment of Fuel Economy Feedback
  Authors: Kurani, Kenneth
  Authors: Kurani, Kenneth
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 833
  Paper Number: 13-4112
• Accommodating Immigration Status and Self-Selection Effects in Joint Model of Household Auto Ownership and Residential Location Choice
  Authors: Paleti, Rajesh
  Authors: Paleti, Rajesh
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 833
  Paper Number: 13-4335
• An Integrated Model of Residential Location, Work Location, Vehicle Ownership, and Commute Tour Characteristics
  Authors: Paleti, Rajesh
  Authors: Paleti, Rajesh
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 833
  Paper Number: 13-4783
• Calculating Potential Emission Reductions Through Introduction of Electric Vehicles
  Authors: Kihm, Alexander
  Authors: Kihm, Alexander
  Year: 2013
  Document Type: Presentation
  Subject: Planning and Forecasting
  Session: 833
  Paper Number: 13-3871