法国南特第一列Incentro轻轨列车

简要介绍了法国南特轻轨车辆的设计思路、结构特点和模块化设计。     

Bayesian imputation of non‐chosen attribute values in revealed preference surveys

Obtaining attribute values of non‐chosen alternatives in a revealed preference context is challenging because non‐chosen alternative attributes are unobserved by choosers, chooser perceptions of attribute values may not reflect reality, existing methods for imputing these values suffer from shortcomings, and obtaining non‐chosen attribute values is resource intensive. This paper presents a unique Bayesian (multiple) Imputation Multinomial Logit model that imputes unobserved travel times and distances of non‐chosen travel modes based on random draws from the conditional posterior distribution of missing values. The calibrated Bayesian (multiple) Imputation Multinomial Logit model imputes non‐chosen time and distance values that convincingly replicate observed choice behavior. Although network skims were used for calibration, more realistic data such as supplemental geographically referenced surveys or stated preference data may be preferred. The model is ideally suited for imputing variation in intrazonal non‐chosen mode attributes and for assessing the marginal impacts of travel policies, programs, or prices within traffic analysis zones. Copyright © 2012 John Wiley & Sons, Ltd.     

Assessment of economic impacts from unexpected events with an interregional commodity flow and multimodal transportation network model

Loss and damage caused by unscheduled events, especially earthquakes, have sudden and significant impacts not only on the region’s economy where the event occurs but also on other regions. The New Madrid Seismic Zone, located in the center of the United States, could have great impacts on economic activities related to this area, if a major earthquake occurred. Based on the 1993 US Commodity Flow Survey [US Commodity Flow Survey, 1993. Available from: <http://www.bts.gov/ntda/cfs/prod.html>], more than 42% of total commodity flows in the US are related to the greater Midwest, which includes the New Madrid Seismic Zone. If a catastrophic earthquake occurred in this area, the indirect damages could spread far beyond the region, and could have sizable impacts on other regions. A model of interregional commodity flows, incorporating regional input–output relationships, and the corresponding transportation network flows, was applied to assess the economic impacts of such an unexpected event. The economic impacts from the event are described for three hypothetical scenarios, analyzing the magnitude and the extent of the direct and indirect impacts. These analytical results may be used to propose strategic management of the recovery and reconstruction efforts after the event.     

Reducing CO<Subscript>2</Subscript> from cars in the European Union

The European Union (EU) recently adopted CO₂ emissions mandates for new passenger cars, requiring steady reductions to 95 gCO₂/km in 2021. We use a multi-sector computable general equilibrium (CGE) model, which includes a private transportation sector with an empirically-based parameterization of the relationship between income growth and demand for vehicle miles traveled. The model also includes representation of fleet turnover, and opportunities for fuel use and emissions abatement, including representation of electric vehicles. We analyze the impact of the mandates on oil demand, CO₂ emissions, and economic welfare, and compare the results to an emission trading scenario that achieves identical emissions reductions. We find that vehicle emission standards reduce CO₂ emissions from transportation by about 50 MtCO₂ and lower the oil expenditures by about €6 billion, but at a net added cost of €12 billion in 2020. Tightening CO₂ standards further after 2021 would cost the EU economy an additional €24–63 billion in 2025, compared with an emission trading system that achieves the same economy-wide CO₂ reduction. We offer a discussion of the design features for incorporating transport into the emission trading system.     

Stated preference modelling of intra-household decisions: Can you more easily approximate the preference space?

While the study of choices focuses primarily on the individual decision maker, there is growing interest in the examination of the choices made by groups. Much of the research into the choices of multiple decision makers has revealed that they differ significantly to those of individuals. In this study of household vehicle choice we similarly compare individual choices to group choices and support this finding. Consequently any research into choices that involve groups should acquire data from those groups. In this paper we show how this may be done via an interactive agency choice experiment which makes the individual preferences endogenous to the choice of the group. This method and many like it, however, involve significant time, incentive and administrative costs that often make such studies prohibitive. In this paper we also compare another class of model, minimum information group inference, which is designed to provide an overview of the likely group choice and while not having the specificity of detail as other methods, has the advantage of being much easier and cheaper to implement and is perhaps the only methodology that can be employed when it is not feasible for respondents to interact. We find that this method is a good approximation of group choice, mapping the preference space over which group choice is likely to be located.

     

The meaning of car availability in mode choice decisions

The paper examines various definitions of car availability that have been used in the literature, and compares the results when applied to a common data set. It argues that car availability means different things to different people depending on their licence holding/car owning status. Using in‐depth interview data, the factors determining car allocation and transferability within a household, and subsequently mode choice, are discussed. An attempt is made to draw some general conclusions for research and modelling. This suggests that different approaches are required depending on whether or not there is competition for use of the car within a household. Also that in cases of competition, mode choice is not a two‐stage process depending on car availability and trip characteristics, but a concurrent decision based on both of these factors.     

A review of passenger rail franchising in Britain: 1996/1997-2006/2007

This paper reviews 10 years of passenger rail franchising in Great Britain and highlights problems in three areas: the tension between commercial and social objectives; the presence of risks and uncertainty; and vulnerability to strategic behaviour such as low-balling, chiselling and back loading. It concludes that franchising has had some good features (such as the high level of competitive pressure) but also some bad features (such as a high rate of franchise failures). In addition, an ugly feature of franchising is the scope for strategic behaviour. Further reform is suggested based on a distinction between commercial and social franchises.     

Optimization of curving performance of rail vehicles

The curving performance of a transit rail vehicle model with 21 degrees of freedom is optimized using a combination of multibody dynamics and a genetic algorithm (GA). The design optimization is to search for optimal design variables so that the noise or wear, arising from misalignment of the wheelsets with the track, is reduced to a minimum level during curve negotiations with flange contact forces guiding the rail vehicle. The objective function is a weighted combination of angle of attack on wheelsets and ratios of lateral to vertical forces on wheels. Using the combination of the GA and a multibody dynamics modelling program, A'GEM, the generation of governing equations of motion for complex nonlinear dynamic rail vehicle models and the search for global optimal design variables can be carried out automatically. To demonstrate the feasibility and efficacy of the proposed approach of using the combination of multibody dynamics and GAs, the numerical simulation results of the optimization are offered, the selected objective function is justified, and the sensitivity analysis of different design parameters and different design parameter sets on curving performance is performed. Numerical results show that compared with suspension and inertial parameter sets, the geometric parameter set has the most significant effect on curving performance.     

Controls on stratification in the Rhine ROFI system

Stratification in the Rhine ROFI is very variable; the mean water column stability is controlled by the combined effect of tidal, wind and wave stirring which, at times, brings about complete vertical homogeneity. Control by the mixing variables has been elucidated by a regression analysis of mean stratification on the components of the windstress and significant wave height. There is strong partial correlation with all three variables which explains between 56% and 65% of the variance in two time series of observations in October 1990 and September 1992, respectively. During periods of low stirring the water column was observed to re-stratify over the whole inshore region through the relaxation of the horizontal gradients under gravity and with the influence of rotation. Superimposed on the mean stratification there is strong semi-diurnal variation, occurring throughout the stratified region at times of reduced mixing. The amplitude of this semi-diurnal variation is of the same order as the mean stability and frequently results in conditions being mixed or nearly mixed once per tide. This semi-diurnal variation results primarily from cross-shore tidal straining which interacts with the main density gradient to induce stratification. The hypothesis that water column stability is controlled by the combination of these processes has been tested using a reduced physics model which has been successful in reproducing the main features of both the mean and semi-diurnal components of stratification.