An assessment of the performance of the European long intermodal freight trains (LIFTS)

Intermodal rail/road freight transport has always been considered as a competitive alternative to its road freight counterpart in the European medium- to long-distance corridors (markets). Such consideration has been based on the increasing competitiveness of some innovative rail services and the existing and prospective performance of both modes in terms of the full social – internal or operational and external – costs. The most recent innovation of rail technologies and related services launched by some European railway companies, still at the conceptual level, is the Long Intermodal Freight Train (LIFT). This is supposed to be a block train operating in long-distance corridors (markets) with a substantial and regular freight demand.This paper develops analytical models for assessing the performance of the LIFTs, the already-operating Conventional Intermodal Freight Trains (CIFTs), and their road counterpart as well. The performance consists of the full – internal (private) and external – costs of the door-to-door delivery of loading units – containers, swap-bodies, and semi-trailers. The internal costs embrace the operational costs of the transport (rail and road) and intermodal terminal operators. The external costs include the costs of the impacts of door-to-door delivery of loading units on society and the environment. These negative externalities include noise, air pollution, traffic accidents, and congestion.The models are applied to a simplified version of intermodal and road transport system using inputs from the European freight transport sector. The aims are to compare the full costs of particular modalities in order to investigate the potential of the LIFTs as compared with the CIFTs in improving the internal efficiency of the rail freight sector and its competitiveness with respect to its road counterpart. In addition, the paper attempts to assess some effects on the potential modal shift of EU (European Union) transport policies on internalizing transport externalities.     

A sequential approach to exploiting the combined strengths of SP and RP data: Application to freight shipper choice

The possibility of and procedure for pooling RP and SP data have been discussed in recent research work. In that literature, the RP data has been viewed as the yardstick against which the SP data must be compared. In this paper we take a fresh look at the two data types. Based on the peculiar strengths and weaknesses of each we propose a new, sequential approach to exploiting the strengths and avoiding the weaknesses of each data source. This approach is based on the premise that SP data, characterized by a well-conditioned design matrix and a less constrained decision environment than the real world, is able to capture respondents' tradeoffs more robustly than is possible in RP data. (This, in turn, results in more robust estimates of share changes due to changes in independent variables.) The RP data, however, represent the current market situation better than the SP data, hence should be used to establish the aggregate equilibrium level represented by the final model. The approachfixes the RP parameters for independent variables at the estimated SP parameters but uses the RP data to establish alternative-specific constants. Simultaneously, the RP data are rescaled to correct for error-in-variables problems in the RP design matrixvis-à- vis the SP design matrix. All specifications tested are Multinomial Logit (MNL) models.The approach is tested with freight shippers' choice of carrier in three major North American cities. It is shown that the proposed sequential approach to using SP and RP data has the same or better predictive power as the model calibrated solely on the RP data (which is the best possible model for that data, in terms of goodness-of-fit figures of merit), when measured in terms of Pearson's Chi-squared ratio and the percent correctly predicted statistic. The sequential approach is also shown to produce predictions with lower error than produced by the more usual method of pooling the RP and SP data.     

A new scenario based approach for designing driver support systems applied to the design of a lane change support system

Designing a new driver support system that meets the expectations of drivers is a difficult and time-consuming process. Despite the availability of various types of design support, it has essentially remained a process in which designers are forced to make assumptions about what other people want. This paper presents a new approach for determining users’ preferences and finding the best compromise between those preferences when designing a new driver support system. Using scenarios, virtual reality simulation, and gaming principles, the new approach gives users a pro-active role in the design process. To evaluate the new approach, it was applied to the design of a lane change support system. This resulted in a hierarchy of information that is a detailed, consistent and reliable image of users’ preferences. By combining this hierarchy with a manufacturing and marketing constraint, the design specification of a lane change support system was deduced. One of the many findings was that a lane change support system should be modular and that modules for the left side should be different from modules for the right side of the vehicle. The paper concludes with reasoning why the new approach offers added value for the design of driver support systems.