Meeting mobility and air quality goals: Strategies that work

Recent federal legislation sets tough air quality goals for the nation but offers scant guidance to urban areas responsible for meeting those goals. Traditionally, transportation-related air quality policy emphasized cleaner vehicle and fuels technologies and alternatives to single-occupant vehicle travel such as car-pooling and mass transit. Analysis suggests, however, that meeting air quality goals will require the addition of policies to manage the growing demand for transportation. The introduction of market forces into transportation supply and demand decisions would support traditional transportation and air quality strategies, and produce additional mobility, air quality, and economic benefits. Recent transportation legislation offers states and localities the flexibility to meet mobility and air quality goals in an innovative, nontraditional manner. Drawing on theoretical analysis and recent empirical evidence we offer a package of measures for the consideration of state, and federal policy-makers.The authors are with the Office of Policy Analysis of the U.S. Environmental Protection Agency. The views expressed here belong solely to the authors. This paper does not represent the view of the US EPA or the policy of the United States Government. This paper was significantly improved by extensive comments from Bruce Schillo, and by suggestions from Michael Shelby, John Chamberlin (all of the EPA Office of Policy Analysis), Robin Miles-McLean (EPA Office of Mobile Sources), Allen Basala (EPA Office of Air Quality Planning and Standards), and numerous other colleagues. The authors are responsible for all errors and interpretations.     

Comparison of results of two models of transportation demand in Hong Kong: CDAM and a version of microTRIPS

CDAM is a new computer program for solving the combined trip distribution and assignment model for multiple user classes, which enables transport planners to estimate consistent Origin-Destination (O-D) matrices and equilibrium traffic flows simultaneously if the trip production and attraction of each user class at zone centroids are available. This paper reports an application of CDAM to the central Kowloon study area in Hong Kong. The coefficients of the model related to the components of generalized costs are calibrated on 1986 travel data. A comparison of results of CDAM and a version of MicroTRIPS models of transportation demand in Hong Kong are presented. Finally, some conclusions are drawn and the advantage of the CDAM are discussed.     

Estimating bus component failure distributions from censored samples

A technique is developed and demonstrated which can be used to estimate bus component failure distributions in an operational setting. The advantage of the described method is that it estimates the distribution of an entire population when only a portion of that population has experienced a failure (censored samples). Further, in an operational setting, components in a population do not age at the same rate and thus, their ages (in miles) are not ordered with respect to time. A sampling technique is derived to draw an ordered, censored sample from a population that has been aged in an operational setting. The resulting sample is used to estimate the life distribution of the component of interest.     

Airline Jet Fuel Hedging: Theory and Practice

Abstract

Most international airlines hedge fuel costs, but the theoretical justification behind this action is weak. The paper explores the nature and extent of airline fuel hedging and asks why airlines hedge. The availability of hedging instruments is first discussed, with the most liquid markets in crude and exchange traded contracts. Aviation fuel contracts are possible, but with counter‐party risk. Most major passenger airlines with sufficient cash and credit now hedge at least part of their future needs. Hedging does protect profits against a sudden upturn in crude prices caused by political and consumer uncertainty leading to slower economic growth. However, if higher oil prices are induced by strong economic growth and oil supply constraints, hedging increases volatility with hedging gains reinforcing improved profits from higher traffic and improved yields. If hedging does not reduce volatility, it may still have an accounting role in moving profits from one time period to another, insure against bankruptcy, and signal the competence of management to investors and other stakeholders.     

A State-of-the-Art Review of Car-Following Models with Particular Considerations of Heavy Vehicles

Abstract

Car-following (CF) models are fundamental in the replication of traffic flow and thus they have received considerable attention. This attention needs to be reflected upon at particular points in time. CF models are in a continuous state of improvement due to their significant role in traffic micro-simulations, intelligent transportation systems and safety engineering models. This paper presents a review of existing CF models. It classifies them into classic and artificial intelligence models. It discusses the capability of the models and potential limitations that need to be considered in their improvement. This paper also reviews the studies investigating the impacts of heavy vehicles in traffic stream and on CF behaviour. The findings of the study provide promising directions for future research and suggest revisiting the existing models to accommodate different behaviours of drivers in heterogeneous traffic, in particular, heavy vehicles in traffic.     

Random regret minimization or random utility maximization: an exploratory analysis in the context of automobile fuel choice

Interest in alternative behavioural paradigms to random utility maximization (RUM) has existed ever since the dominance of the RUM formulation. One alternative is known as random regret minimization (RRM), which suggests that when choosing between alternatives, decision makers aim to minimize anticipated regret. Although the idea of regret is not new, its incorporation into the same discrete choice framework of RUM is very recent. This paper is the first to apply the RRM‐model framework to model choice amongst durable goods. Specifically, we estimate and compare the RRM and RUM models in a stated choice context of choosing amongst vehicles fuelled with petrol, diesel and hybrid (associated with specific levels of fuel efficiency and engine capacity). The RRM model is found to achieve a marginally better fit (using a non‐nested test of differences) than its equally parsimonious RUM counterpart. As a second contribution, we derive a formulation for regret‐based elasticities and compare utility‐based and regret‐based elasticities in the context of stated vehicle type choices. We find that in the context of our choice data, mean estimates of elasticities are different for many of the attributes and alternatives. Copyright © 2011 John Wiley & Sons, Ltd.     

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行程时间的不确定性是影响货运车队路径选择的一个重要因素，特别是对于要求货物准时送达的配送任务（例如商品混凝土的配送），提出了在车辆调度中考虑由拥挤路段交通流量波动引起的行程时间不确定性的方法，建立了考虑行程时间可靠性要求的车辆优化调度数学模型，给出了相应的启发式算法，通过算例介绍了该模型和算法的应用。结果表明配送总成本随行程时间可靠性要求的提高而增加。