Analyzing loss aversion and diminishing sensitivity in a freight transport stated choice experiment

Choice behaviour might be determined by asymmetric preferences whether the consumers are faced with gains or losses. This paper investigates loss aversion and diminishing sensitivity, and analyzes their implications on willingness to pay and willingness to accept measures in a reference pivoted choice experiment in a freight transport framework. The results suggest a significant model fit improvement when preferences are treated as asymmetric, proving both loss aversion and diminishing sensitivity. The implications on willingness to pay and willingness to accept indicators are particular relevant showing a remarkable difference between symmetric and asymmetric model specifications. Not accounting for loss aversion and diminishing sensitivity, when present, produces misleading results and might affect significantly the policy decisions.     

Productivity,efficiency and technical change in the European railways: A non-parametric approach

The purpose of this paper is to analyse the evolution of productivity in the European railways in the period 1970–95. We use a non-parametric approach that enables changes in productivity to be broken down into variations in efficiency and technical change. The results indicate that the productivity growth is concentrated in the last period (1985–95), when the majority of the companies undertook processes of reforms. This increase in productivity is mainly due to technical progress. We also analyse the determinants of efficiency and, unlike other papers, the technical change, finding that the greater the degree of autonomy and financial independence, the higher the efficiency levels and technical change. This revised version was published online in June 2006 with corrections to the Cover Date.     

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以英国M42高速公路线圈交通数据为输入,建立预测模型,提出神经网络OD矩阵预测方法. 将预测结果与该公路3a号至7号交叉口间各支路上自动车牌识别装置测得的车辆数据进行对比,验证其有效性. 解决了以下关键问题：利用线圈数据实现OD矩阵预测的可操作性,该类数据的特殊性是否影响模型构建,通过变异数稳定数据转换能否改善模型性能,能否同时进行单个OD预测. 得到基于训练数据平方根代换的最佳计算结果和单个OD预测模型.     

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以道路网络的路段流量为基础进行OD分布矩阵估计.与以往文献不同的是本文应用了多层前馈神经网络的方法.由于路段流量与相关的OD矩阵分布之间存在连续性关系,这为神经网络模型的逼近特性提供了可行性.本文的方法适用于OD分布矩阵的实时校正.在已知OD分布矩阵的前提下,对两种情境———试验网络和实际Naples农村道路网进行仿真分析.主成分分析法的应用减少了变量个数并有利于改进输入数据.估计误差相对较低,与分析方法相反的是处理的时间几乎是实时的,因此这种方法可用于动态交通管理.本文的神经网络方法在误差和计算时间方面优于传统商业软件得到的OD估计结果.     

Spillback congestion in dynamic traffic assignment: A macroscopic flow model with time-varying bottlenecks

In this paper, we propose a new model for the within-day Dynamic Traffic Assignment (DTA) on road networks where the simulation of queue spillovers is explicitly addressed, and a user equilibrium is expressed as a fixed-point problem in terms of arc flow temporal profiles, i.e., in the infinite dimension space of time’s functions. The model integrates spillback congestion into an existing formulation of the DTA based on continuous-time variables and implicit path enumeration, which is capable of explicitly representing the formation and dispersion of vehicle queues on road links, but allows them to exceed the arc length. The propagation of congestion among adjacent arcs will be achieved through the introduction of time-varying exit and entry capacities that limit the inflow on downstream arcs in such a way that their storage capacities are never exceeded. Determining the temporal profile of these capacity constraints requires solving a system of spatially non-separable macroscopic flow models on the supply side of the DTA based on the theory of kinematic waves, which describe the dynamic of the spillback phenomenon and yield consistent network performances for given arc flows. We also devise a numerical solution algorithm of the proposed continuous-time formulation allowing for “long time intervals” of several minutes, and give an empirical evidence of its convergence. Finally, we carry out a thorough experimentation in order to estimate the relevance of spillback modeling in the context of the DTA, compare the proposed model in terms of effectiveness with the Cell Transmission Model, and assess the efficiency of the proposed algorithm and its applicability to real instances with large networks.     

The analysis of motor vehicle crash clusters using the vector quantization technique

In this paper, a powerful tool for analyzing motor vehicle data based on the vector quantization (VQ) technique is demonstrated. The technique uses an approximation of a probability density function for a stochastic vector without assuming an “a priori” distribution. A self‐organizing map (SOM) is used to transform accident data from an N‐dimensional space into a two‐dimensional plane. The SOM retains all the original data yet provides an effective visual tool for describing patterns such as the frequency at which a particular category of events occurs. This enables new relationships to be identified. Accident data from three cities in Italy (Turin, Milan, and Legnano) are used to illustrate the usefulness of the technique. Crashes are aggregated and clustered crashes by type, severity, and along other dimensions. The paper includes discussion as to how this method can be utilized to further improve safety analysis. Copyright © 2010 John Wiley & Sons, Ltd.     

Shift of reference point and implications on behavioral reaction to gains and losses

It is widely recognized that individual decision-making is subject to the evaluation of gains and losses around a reference point. The estimation of discrete choice models increasingly use data from stated choice experiments which are pivoted around a reference alternative. However, to date, the specification of a reference alternative in transport studies has been fixed, whereas it is common to observe individuals adjusting their preferences according to a change in their reference point. This paper focuses on individual reactions, in a freight choice context, to a negative change in the reference alternative values, identifying the behavioural implications in terms of loss aversion and diminishing sensitivity. The results show a significant adjustment in the valuation of gains and losses around a shifted reference alternative. In particular, we find an average increase in loss aversion for cost and time attributes, and a substantial decrease for punctuality. These findings are translated to significant differences in the willingness to pay and willingness to accept measures, providing supporting evidence of respondents’ behavioural reaction.     

An innovative method for the analysis of vehicle movements in roundabouts based on image processing

The objective of this paper is to propose a method, based on the image processing of field survey data, to analyze vehicles movements into roundabouts. This research study consisted of three stages: a field survey to collect vehicular flow images captured by video cameras, the processing of these images using a proprietary software (VeTRA—Vehicle Tracking for Roundabout Analysis), and finally, the analysis of the collected data. The main feature of the software is that it allows the automatic computation of the main variables necessary to rank and evaluate a generic roundabout: the entry/exit (E/E) matrix with classification of vehicles (e.g., heavy, light, and motorbikes), vehicle trajectories, and vehicular speed diagrams along the paths inside the roundabout. The processing system is robust enough to withstand classic problems affecting image processing such as variable wind conditions, cloud cover, shadows, and obstructions. Calibration and error evaluation have been deduced from data collected by a high precision Real Time Kinematic GPS video recording system mounted on a probe vehicle. Data of E/E matrices generated by VeTRA are compared with those manually counted on the corresponding video images. A case study of an existing roundabout is featured in the paper. The results indicate that the software has a high capability of generating the E/E matrix. The analysis of vehicular trajectories with both the plot of curvature diagrams and the corresponding speed diagrams enable the evaluation of driver behavior relative to the geometric shape of the roundabout. Copyright © 2011 John Wiley & Sons, Ltd.     

Characterization of fall–winter upwelling recurrence along the Galician western coast (NW Spain) from 2000 to 2005: Dependence on atmospheric forcing

Upwelling events driving ENACW (Eastern North Atlantic Coastal Water) into the Galician western coast rias had been considered typical spring–summer processes, according to the research developed in this area. However, they can also be observed in fall or winter under northerly winds blowing at shelf. Six different upwelling events were analyzed in the Ria of Pontevedra during the wet season (NDJF) from 2000 to 2005. These events were characterized by means of the zonal Ekman transport (Q_x) at four control points in front of the western rias (locally known as Rias Baixas) and thermohaline variables measured at a fixed station in the main mouth of the Ria of Pontevedra. The duration of the upwelling events ranged from 27 days (during February and March 2002) to 69 days (during November–December 2004 and January 2005). Upwelling events studied in the Ria of Pontevedra from 2000 to 2005 showed the similarity in upwelling features during both seasons (similar wind forcing and upwelled water). Finally, Q_x was correlated with the most representative atmospheric patterns in the Northern Hemisphere (EA, NAO, EA/WR, POL and SCA) from 1966 to 2005. The winter EA pattern has the most influence on Q_x showing an annual evolution with a prevalence of the positive phase from 1976 on. This positive phase is directly correlated with a prevalence of positive values of Q_x which are upwelling unfavorable in the Rias Baixas.