Measuring the potential for automobile fuel savings in the US: The impact of obesity

High rates of oil consumption and obesity in the US have become important socioeconomic concerns. While these concerns may seem unrelated at first, growing obesity rates in the US increase fuel consumption by adding passenger weight to vehicles. This paper estimates the additional amount of fuel (i.e., gasoline) consumed annually by noncommercial passenger highway vehicles in the US due to passenger overweight and obesity. The mathematical model presented in this paper estimates that as many as one billion additional gallons of gasoline are consumed each year due to overweight and obesity in the US, accounting for up to 0.8% of the fuel consumed by these vehicles annually. This additional fuel consumption causes carbon dioxide emissions of up to 20 billion pounds or more, accounting for up to 0.5% of the annual carbon dioxide emissions in the transportation sector.     

The inconvenient truth about improving vehicle fuel efficiency: A multi-attributes analysis of the technology efficient frontier of the US automobile industry

Vehicle fuel efficiency has taken on more economic and environmental significance due to the rise in gasoline prices in 2007/2008. We examine adoption of fuel efficiency technologies by the US automobile industry between 1985 and 2002 and consider the environmental implications. The technology efficient frontier between vehicle weight and fuel efficiency of the US automobile fleet did not move outward significantly for an extended period in the 1980s and 1990s indicating a lack of company- or industry-wide adoption of new fuel efficiency technologies. While the firm with inferior technology capability did push its efficient frontier outward to close the technology gap, the two leading firms’ efficient frontiers first showed signs of possible regression in the early 1990s, and did not move outward significantly until the mid 1990s. Several managerial and policy options are examined for improving vehicle fuel efficiency.     

Recent advances in automotive technology and the cost-effectiveness of fuel economy improvement

The potential for improving the fuel economy of conventional, gasoline-powered automobiles through optimized application of recent technology advances is analyzed. Results are presented at three levels of technical certainty, ranging from technologies already in use to technologies facing technical constraints (such as emissions control problems) which might inhibit widespread use. A fleet-aggregate, engineering-economic analysis is used to estimate a range of U.S. new car fleet average fuel economy levels achievable given roughly 10 years of lead time. Technology cost estimates are compared to fuel savings in order to determine likely cost-effective levels of fuel economy, which are found to range from 39 miles per gallon to 51 miles per gallon depending on technology certainty level. The corresponding estimated increases in average new car price range from $540 to $790 (1993$). Estimated fuel savings payback times average less than 3 years and the cost of conserved energy averages $0.50 per gallon, indicating that these levels of fuel economy improvement are cost-effective over a vehicle lifetime. A vehicle stock turnover model is used to project the reductions in gasoline consumption and associated emissions that would follow if the estimated fuel economy levels are achieved. Potential trade-offs regarding vehicle performance, safety, and emissions are also discussed.     

A joint model for vehicle type and fuel type choice: evidence from a cross-nested logit study

In the face of growing concerns about greenhouse gas emissions, there is increasing interest in forecasting the likely demand for alternative fuel vehicles. This paper presents an analysis carried out on stated preference survey data on California consumer responses to a joint vehicle type choice and fuel type choice experiment. Our study recognises the fact that this choice process potentially involves high correlations that an analyst may not be able to adequately represent in the modelled utility components. We further hypothesise that a cross-nested logit structure can capture more of the correlation patterns than the standard nested logit model structure in such a multi-dimensional choice process. Our empirical analysis and a brief forecasting exercise produce evidence to support these assertions. The implications of these findings extend beyond the context of the demand for alternative fuel vehicles to the analysis of multi-dimensional choice processes in general. Finally, an extension verifies that further gains can be made by using mixed GEV structures, allowing for random heterogeneity in addition to the flexible correlation structures.     

A new twist on the gig economy: conducting surveys on Amazon Mechanical Turk

Transportation - There is growing interest in using online outsourcing platforms that are part of the “gig economy” to conduct surveys for academic research. This interest has been...     

A note on the optimal control of an oversaturated intersection

An existence condition for the solution of an optimal control problem for a single traffic intersection is derived in this note. The optimal control problem has been initially formulated and solved in the pioneering work of Gazis (1963, 1964) and coworkers. It is shown that existence conditions are fairly restrictive if control is required to dissolve all intersection queues at the same time.     

A note on the consistent aggregation of nested logit demand functions

The present paper derives a set of rules allowing for the consistent aggregation of nested logit travel demand functions across origin and destination zones. Presented aggregation rules are derived for the case when the mode choice is performed conditional on destination choice. The derivation is based on the principles of consistency between aggregate and disaggregate travel demand models introduced by Sweet as well as upon the sampling theory.     

A note on the turn and arrival likelihood algorithms of traffic assignments

This note illustrates by means of examples that two of the three modifications of Dial's assignment algorithm suggested recently by Tobin (1977) should be subject to further research prior to implementation. Three potential problems with these algorithms are shown to be significant for small contrived networks.     

Determining the effects of scheduling on automated automobile guideway utilization

This paper develops an analytic approach for measuring the effect of vehicle scheduling and of metering methods required to balance entrance rates among stations on lane capacity utilization of automated automobile guideways. The scheduling process at each entrance is represented by a probabilistic model which generates a system of nonlinear equations. The solution of this system yields the maximum steady state input rates at the entrances to the guideway system. The method developed is applicable to network configurations in which a small number of merges must be scheduled for each vehicle before it enters the guideway. It is demonstrated by application to a corridor guideway serving a major activity center during peak inbound demand, and also it is shown how the approach may be extended to more complex networks.     

A note on consistency of choice units in entropy models

In using entropy maximization models to forecast locational and travel behaviour, one is confronted with the problem of delineating the choice process as precisely as possible. In addition to defining a fine-grain choice structure implying individuals seeking distinct location sites within residential zones and travelling to distinct jobs or shops within destination zones, this note also accounts for the fact that the location choice is of a site for a household or firm, but the corresponding travel choices are by individual members of a household. In conjunction with disaggregation across quantities with large variance, the above principles are applied to formulate improved versions of residential and shopping location models.     

A note on the calculation and calibration of doubly constrained trip distribution models

The use of growth factor models for trip distribution has given way in the past to the use of more complex synthetic models. Nevertheless growth factor models are still used, for example in modelling external trips, in small area studies, in input-output analysis, and in category analysis. In this article a particular growth factor model, the Furness, is examined. Its application and functional form are described together with the method of iteration used in its operation. The expected information statistic is described and interpreted and it is shown that the Furness model predicts a trip distribution which, when compared with observed trips, has the minimum expected information subject to origin and destination constraints. An equivalent entropy maximising derivation is described and the two methods compared to show how the Furness iteration can be used in gravity models with specified deterrence functions. A trip distribution model explicitly incorporating information from observed trips, is then derived.It is suggested that if consistency is to be maintained between iteration, calibration, and the derivation of gravity models, then expected information should be used as the calibration statistic to measure goodness of fit. The importance of consistency in this respect is often overlooked.Lastly, the limitations of the models are discussed and it is suggested that it may be better to use the Furness iteration rather than any other, since it is more fully understood. In particular its ease of calculation makes it suitable for use in small models computed by hand.     

The impact of urban form on automobile travel: disentangling causation from correlation

A longstanding question within the field of transportation demand management is the strength of the relationship between urban form and mobility behavior. Although several studies have identified a strong correlation between these variables, there is as yet scant evidence to support policy interventions that target land use as a means of influencing travel. To the contrary, some of the more recent research has cast skepticism on the proposition that the relationship is causative, recognizing the possibility that households endogenously self-select themselves into communities that support their preferences for particular transportation modes. Focusing on individual automobile travel, the present study seeks to contribute to this line of inquiry by estimating econometric models on a panel of travel-diary data collected in Germany between 1996 and 2003. Specifically, we employ the two-part model (2PM)—a procedure involving probit and OLS estimators—to assess the determinants of the discrete decision to use the car and the continuous decision of distance traveled. Beyond modeling variables that capture the urban form features that are commonly suggested to influence mobility behavior, including mixed use and public transit, this study employs instrumental variables to control for potential endogeneity emerging from the simultaneity of residential and mode choices. Unlike much of the work to date, our results suggest that urban form has a causative impact on car use, a finding that is robust to alternative econometric specifications.

A choice experiment on alternative fuel vehicle preferences of private car owners in the Netherlands

This paper presents results of an online stated choice experiment on preferences of Dutch private car owners for alternative fuel vehicles (AFVs) and their characteristics. Results show that negative preferences for alternative fuel vehicles are large, especially for the electric and fuel cell car, mostly as a result of their limited driving range and considerable refueling times. Preference for AFVs increases considerably with improvements on driving range, refueling time and fuel availability. Negative AFV preferences remain, however, also with substantial improvements in AFV characteristics; the remaining willingness to accept is on average € 10,000–€ 20,000 per AFV. Results from a mixed logit model show that consumer preferences for AFVs and AFV characteristics are heterogeneous to a large extent, in particular for the electric car, additional detour time and fuel time for the electric and fuel cell car. An interaction model reveals that annual mileage is by far the most important factor that determines heterogeneity in preferences for the electric and fuel cell car. When annual mileage increases, the preference for electric and fuel cell cars decreases substantially, whilst the willingness to pay for driving range increases substantially. Other variables such as using the car for holidays abroad and the daily commute also appear to be relevant for car choice.     

Relationships between characteristics of motorcycles and hydrocarbon emissions in Taiwan: A note

Taiwan’s inspection and maintenance (I/M) programs identifies high-emission motorcycles but, although these help reduce air pollution, they have been criticized for being cost-ineffective. This study examines the relationship between characteristics of motorcycles and hydrocarbon emissions in the Central Air Quality Basin of Taiwan. It is shown that engine size and type, age and manufacturer of a motorcycle significantly affect HC emissions. Larger-size engines emit smaller amounts of HCs; whereas older motorcycles emitted greater amounts. In addition, two-stroke-engine machines produced significantly higher HC emission levels than four-strokes. Variations in HC emissions testing are a result of various I/M testing locations and efficiency may be improved by modifying these.     

Identifying the early adopters of alternative fuel vehicles: A case study of Birmingham,United Kingdom

The transport sector has been identified as a significant contributor to greenhouse gas emissions. As part of its emissions reduction strategy, the United Kingdom Government is demonstrating support for new vehicle technologies, paying attention, in particular, to electric vehicles.Cluster analysis was applied to Census data in order to identify potential alternative fuel vehicle drivers in the city of Birmingham, United Kingdom. The clustering was undertaken based on characteristics of age, income, car ownership, home ownership, socio-economic status and education. Almost 60% of areas that most closely fitted the profile of an alternative fuel vehicle driver were found to be located across four wards furthest from Birmingham city centre, while the areas with the poorest fit were located towards the centre of Birmingham. The paper demonstrates how Census data can be used in the initial stages of identifying potential early adopters of alternative vehicle drivers. It also shows how such research can provide scope for infrastructure planning and policy development for local and national authorities, while also providing useful marketing information to car manufacturers.     

陕西重汽2006新款重卡靓节油

2005年12月28日,目前亚洲最大的现代化陕汽商用车基地正式投产,第一辆2006年节油新品正式下线,这是陕汽发展史上一个新的里程碑.目前,陕汽形成以潍柴动力、康明斯发动机、法士特、汉德车桥为主的国内强势供应链体系,这使陕汽2006款新产品在技术、品质、配置及服务等方面保证国内领先.     

Value of travel time reliability: A review of current evidence

Travel time reliability is a fundamental factor in travel behavior. It represents the temporal uncertainty experienced by travelers in their movement between any two nodes in a network. The importance of the time reliability depends on the penalties incurred by the travelers. In road networks, travelers consider the existence of a trip travel time uncertainty in different choice situations (departure time, route, mode, and others). In this paper, a systematic review of the current state of research in travel time reliability, and more explicitly in the value of travel time reliability is presented. Moreover, a meta-analysis is performed in order to determine the reasons behind the discrepancy among the reliability estimates.     

Curbing automobile use for sustainable transportation: analysis of mode choice on short home-based trips

This paper analyzes transportation mode choice for short home-based trips using a 1999 activity survey from the Puget Sound region of Washington State, U.S.A. Short trips are defined as those within the 95th percentile walking distance in the data, here 1.40 miles (2.25 km). The mean walking distance was 0.4 miles (0.6 km). The mode distribution was automobile (75%), walk (23%), bicycle (1%), and bus (1%). Walk and bicycle are found less likely as the individual’s age increases. People are more likely to drive if they can or are accustomed to. People in multi-person families are less likely to walk or use bus, especially families with children. An environment that attracts people’s interest and provides activity opportunities encourages people to walk on short trips. Influencing people’s choice of transport mode on short trips should be an important part of efforts encouraging the use of non-automobile alternatives.

Training urban bus drivers to promote smart driving: A note on a Greek eco-driving pilot program

Economical, ecological and safe driving (eco-driving) is aimed at reducing fuel consumption, greenhouse gas emissions and accidents. Eco-driving is concerned about driving in a way compatible with modern engine technology: smart, smooth and safe techniques that lead to potential fuel savings of 10–15%. The Centre for Renewable Energy Sources of Greece conducted an eco-driving pilot study in collaboration with the Organization of Urban Transportation of Athens, and the Thermo-Bus Company to assess the effects of changing urban bus drivers’ driving style.