A conceptual and methdological framework for the generation of activity-travel patterns

This paper develops a conceptual framework for the generation of activity and travel patterns in the context of more general structures and presents an integrated model system as a step toward development of an improved travel demand forecasting model system. We propose a two-stage structure to model activity and travel behavior. The first stage, the stop generation and stop/auto allocation models, consists of the choices for the number of household maintenance stops and the allocation of stops and autos to household members. The second stage, the tour formation model, includes the choices for the number of tours and the assignment of stops to tours for each individual, conditional on the choices in the first stage. Empirical results demonstrate that individual and household socio-demographics are important factors affecting the first stage choices, the generation of maintenance stops and the allocation of stops and autos among household members, and the second stage choices, the number of tours and the assignment of stops to tours. This revised version was published online in June 2006 with corrections to the Cover Date.     

场地平整的设计方法初探

场地平整设计已成为许多开发区招商引资的先决条件,决定着开发区域的开发强度、出地率、开发成本、土石方平衡等诸多因素。针对场地平整设计的方法及设计要点进行了初步探讨,有关经验可供相关专业人员参考。     

Using repeated cross-sectional travel surveys to enhance forecasting robustness: Accounting for changing mode preferences

Transportation system capacity and performance, urban form and socio-demographics define the influences and constraints conditioning the preferences of urban residents for different transport modes. Changes in characteristics of urban areas are likely to lead to changes in preferences for alternative modes of transport over time; as a consequence, statistical models to forecast mode choice need to be sensitive to both purposeful changes to urban systems as well as exogenous shocks. We make use of the 1996, 2001 and 2006 household surveys conducted in the Greater Toronto and Hamilton Area to study mode preference evolution and model forecasting performance. These repeated cross-sectional household surveys provide an opportunity to investigate aggregate structural changes in commuting mode preferences over time, in a manner sensitive to changes in the urban area. We focus on commuting mode choices because these trips are prime determinants of peak period congestion and peak spreading. We then address how to combine the three cross-sections econometrically in a robust way that allows for use of a single mode choice model across the entire period. Using independent data from 2012, we are able to compare the individual year and combined models in terms of forecasting performance to demonstrate the combined model’s more robust forecasting performance into the future.     

A new estimation approach for the multiple discrete–continuous probit (MDCP) choice model

This paper develops a blueprint (complete with matrix notation) to apply Bhat’s (2011) Maximum Approximate Composite Marginal Likelihood (MACML) inference approach for the estimation of cross-sectional as well as panel multiple discrete–continuous probit (MDCP) models. A simulation exercise is undertaken to evaluate the ability of the proposed approach to recover parameters from a cross-sectional MDCP model. The results show that the MACML approach does very well in recovering parameters, as well as appears to accurately capture the curvature of the Hessian of the log-likelihood function. The paper also demonstrates the application of the proposed approach through a study of individuals’ recreational (i.e., long distance leisure) choice among alternative destination locations and the number of trips to each recreational destination location, using data drawn from the 2004 to 2005 Michigan statewide household travel survey.     

Empirical approaches to combining revealed and stated preference data: Some recent developments with reference to urban mode choice

This paper replaces the nested logit ‘trick’ used in estimation of a modal choice model, when stated preference (SP) and revealed preference (RP) data are pooled, with an error component mixed logit model that can (i) relax the IID condition attached to subsets of alternatives in nested logit models, (ii) accommodate correlated observations, and (iii) reveal the relevant scale parameter for subsets of alternatives. Such a model can also incorporate state dependence between data types and preference heterogeneity on observed attributes. An example of choice among bus, train and car modes illustrates the difference in empirical evidence, especially elasticity outputs.     

城市轨道交通车辆最高运行速度的选择

研究目的:通过对影响列车最高运行速度的几大要素进行分析,寻找轨道交通车辆选型时确定列车最高运行速度等级的一般规律,从而达到节约能源、减少车底数的目的.研究结论:确定城市轨道交通车辆最高运行速度等级时一般以平均车站间距作为首要依据,车站间距约为3.4 km时,推荐选择列车最高运行速度120 km/h;当车站站间距约为2.3 km时,推荐选择列车最高运行速度100 km/h;当车站站间距约为1.5 km时,推荐选择列车最高运行速度80 km/h.     

关于SDH传输设备误码问题的处理

误码是指在传输过程中码元发生了错误，是日常运行维护中经常遇到的问题。因此充分理解和掌握误码性能事件对于做好SDH设备的维护工作具有重要作用。为此，分析误码产生的原因，总结处理方法。     

分光光度计测量结果的不确定度评定

测量不确定度是对测量结果而言,表达这个结果分散性程度的参数,是计量学中的一个重要内容。本文对分光光度计校准过程的透射比示值误差测量结果的不确定度和波长示值误差测量结果的不确定度进行了评定,给出了评定方法、步骤及结果,并对测量不确定度进行了讨论。     

强夯法施工锤重参数的合理选用

如何选择强夯处理工程地基中的有关施工参数，直接关系到地基的加固效果。在对常规方法确定参数的全面分析后，通过对下落锤体对地基土体的冲力作用研究，提出了在同一单击能量（机械提升能量）情况下，采用重锤低落距处理地基工程优于轻锤高落距强夯方案。     

Sampling of alternatives for route choice modeling

This paper presents a new paradigm for choice set generation in the context of route choice model estimation. We assume that the choice sets contain all paths connecting each origin–destination pair. Although this is behaviorally questionable, we make this assumption in order to avoid bias in the econometric model. These sets are in general impossible to generate explicitly. Therefore, we propose an importance sampling approach to generate subsets of paths suitable for model estimation. Using only a subset of alternatives requires the path utilities to be corrected according to the sampling protocol in order to obtain unbiased parameter estimates. We derive such a sampling correction for the proposed algorithm.Estimating models based on samples of alternatives is straightforward for some types of models, in particular the multinomial logit (MNL) model. In order to apply MNL for route choice, the utilities should also be corrected to account for the correlation using, for instance, a path size (PS) formulation. We argue that the PS attribute should be computed based on the full choice set. Again, this is not feasible in general, and we propose a new version of the PS attribute derived from the sampling protocol, called Expanded PS.Numerical results based on synthetic data show that models including a sampling correction are remarkably better than the ones that do not. Moreover, the Expanded PS shows good results and outperforms models with the original PS formulation.