Using the built environment to oversample walk,transit, and bicycle travel

Characteristics of the built environment (BE) have been associated with walk, transit, and bicycle travel. These BE characteristics can be used by transportation researchers to oversample households from areas where walk, transit, or bicycle travel is more likely, resulting in more observations of these uncommon travel behaviors. Little guidance, however, is available on the effectiveness of such built environment oversampling strategies. This article presents measures that can be used to assess the effectiveness of BE oversampling strategies and inform future efforts to oversample households with uncommon travel behaviors. The measures are sensitivity and specificity, positive likelihood ratio (LR+), and positive predictive value (PPV). To illustrate these measures, they were calculated for 10 BE-defined oversampling strata applied post-hoc to a Seattle area household travel survey. Strata with an average block size of <10 acres within a ¼ mile of household residences held the single greatest potential for oversampling households that walk, use transit, and/or bicycle.     

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.     

基于序贯Kriging模型的潜器型线优化设计

潜器型线优化设计是一个多目标优化问题,在型线设计过程中,阻力性能与包络体积的要求是相互冲突的。为了解决计算流体力学软件如Fluent在进行潜器的外形优化设计时效率低下问题,采用Kriging模型代替仿真模型进行潜器外形设计的策略,其基本思想是：选取设计变量和样本点,利用ICEM软件建立参数化的水动力分析模型,用Fluent软件计算得到样本点的阻力响应值,建立反映设计变量与响应之间关系的Kriging模型,将阻力和体积作为潜器外形优化的两个目标,利用多目标遗传算法求出Pareto最优解。由于采样策略对Kriging模型精度影响很大,本文提出了一种新的序贯采样方法命名为加权累积误差方法,来选取样本点以提高Kriging模型精度。结果表明提出的序贯Kriging建模技术能极大提高潜器型线优化设计效率,同时保证设计精度。     

浅析废气分析仪类型和取样系统

摩托车HC、CO、NOx、CO2等不同排气成分需要采用不同的测量仪器和方法.通常有不分光红外线法、氢火焰离子化法、化学发光法等;取样方法有直接取样法和稀释取样法,以适用于不同测量法规要求.排放测量系统中影响排放分析精度的因素很多,如分析仪的工作原理、仪器本身的精度、标准气体的纯度、背景气体和水分等对分析仪的干扰、取样系统的选择和设计及试验方法等.     

基于旅客出行意图的航线潜在价值计算模型

传统的航线价值计算通常以统计客流量为主,忽略了旅客偏好对航线潜在价值的影响,因此,本文提出了一种基于旅客出行意图的航线潜在价值计算模型.该模型利用最大似然估计法对旅客舱位偏好进行量化,然后引入出行意图的概念将旅客出行行为进行细分,并利用Gibbs Sampling方法实现出行意图的求解,最终达到航线潜在价值计算的目的.在中国民航旅客订票数据集上的实验表明,本文方法获得的2010年航线价值序列与2011年航线价值序列的相似度要明显高于统计客流量的方法,且对排名前5的高价值航线的挖掘准确率可达100%.     

Probe vehicle data sampled by time or space: Consistent travel time allocation and estimation

A characteristic of low frequency probe vehicle data is that vehicles traverse multiple network components (e.g., links) between consecutive position samplings, creating challenges for (i) the allocation of the measured travel time to the traversed components, and (ii) the consistent estimation of component travel time distribution parameters. This paper shows that the solution to these problems depends on whether sampling is based on time (e.g., one report every minute) or space (e.g., one every 500 m). For the special case of segments with uniform space-mean speeds, explicit formulae are derived under both sampling principles for the likelihood of the measurements and the allocation of travel time. It is shown that time-based sampling is biased towards measurements where a disproportionally long time is spent on the last segment. Numerical experiments show that an incorrect likelihood formulation can lead to significantly biased parameter estimates depending on the shapes of the travel time distributions. The analysis reveals that the sampling protocol needs to be considered in travel time estimation using probe vehicle data.     

基于EDI的集装箱运价指数生成与技术分析

为克服目前集装箱运价指数计算中所存在的抽样信息不全面和干扰信息过多等缺陷,通过采用港航电子数据交换(EDI)源信息来生成集装箱运价指数,并展开相应的技术分析。研究表明:这一途径是可行的。     

Specification of the cross-nested logit model with sampling of alternatives for route choice models

We present an operational estimation procedure for the estimation of route choice multivariate extreme value (MEV) models based on sampling of alternatives. The procedure builds on the state-of-the-art literature, and in particular on recent methodological developments proposed by Flötteröd and Bierlaire (2013) and Guevara and Ben-Akiva (2013b). Case studies on both synthetic data and a real network demonstrate that the new method is valid and practical.     

Guidelines for samplers: measuring a change in behaviour from before and after surveys

This paper addresses the issue of using before and after surveys to evaluate behavioural changes in response to transport policies and investments, a procedure that, we argue is done far too rarely in this profession. Further, it demonstrates very clearly that, in almost all conceivable cases, there are considerable economies to be obtained by using a panel (again, under-utilised in our profession) to undertake evaluation, rather than successive independent cross-sectional surveys. The paper also addresses the critical issue of sample size requirements for measuring changes of a relatively small magnitude in travel behaviour; i.e., to state, with 95% confidence, that if there is a ∂ percent change in behaviour for the sample, there is a ∂ percent ± e percent change in the behaviour of the population, where e is the sampling error. In this paper, we present a method for calculating such sample size requirements from first principles and demonstrate the applicability both hypothetically and then empirically using data from the Puget Sound Transportation Panel. The formulation enables designers of before and after surveys to investigate the trade-offs between the statistical accuracy of their predictions and the sample size requirements systematically, without the need to specify ∂ a priori. This latter point is crucial, we argue, because we have limited information on ∂, yet, as we explain here, it drives the sample size requirements using alternative, well-cited approaches for calculating sample sizes to assess behavioural change. The results have important ramifications both for those implementing transport policies intended to produce behavioural change, especially when a cost-benefit evaluation of the policy is desired, and for those interpreting the results reported in previous studies.     

辽宁省公路绿化现状调查

通过网格取样、抽样调查方法,对辽宁省公路绿化立地状况、现有绿化模式及树种等进行全面调查,汇总分析,指出当前公路绿化存在的一些问题并对进一步提高公路绿化水平提出几点建议。