Experimental design influences on stated choice outputs: An empirical study in air travel choice

Discrete choice experiments are conducted in the transport field to obtain data for investigating travel behaviour and derived measures such as the value of travel time savings. The multinomial logit (MNL) and other more advanced discrete choice models (e.g., the mixed MNL model) have often been estimated on data from stated choice experiments and applied for planning and policy purposes. Determining efficient underlying experimental designs for these studies has become an increasingly important stream of research, in which the objective is to generate stated choice tasks that maximize the collected information, yielding more reliable parameter estimates. These theoretical advances have not been rigorously tested in practice, such that claims on whether the theoretical efficiency gains translate into practice cannot be made. Using an extensive empirical study of air travel choice behaviour, this paper presents for the first time results of different stated choice experimental design approaches, in which respective estimation results are compared. We show that D-efficient designs keep their promise in lowering standard errors in estimating, thereby requiring smaller sample sizes, ceteris paribus, compared to a more traditional orthogonal design. The parameter estimates found using an orthogonal design or an efficient design turn out to be statistically different in several cases, mainly attributed to more or less dominant alternatives existing in the orthogonal design. Furthermore, we found that small designs with a limited number of choice tasks performs just as good (or even better) than a large design. Finally, we show that theoretically predicted sample sizes using the so-called S-estimates provide a good lower bound. This paper will enable practitioners in better understanding the potential benefits of efficient designs, and enables policy makers to make decisions based on more reliable parameter estimates.     

Assessing the cost of transfer inconvenience in public transport systems: A case study of the London Underground

Few studies have adequately assessed the cost of transfers² in public transport systems, or provided useful guidance on transfer improvements, such as where to invest (which facility), how to invest (which aspect), and how much to invest (quantitative justification of the investment). This paper proposes a new method based on path choice,³ taking into account both the operator’s service supply and the customers’ subjective perceptions to assess transfer cost and to identify ways to reduce it. This method evaluates different transfer components (e.g., transfer walking, waiting, and penalty) with distinct policy solutions and differentiates between transfer stations and movements.The method is applied to one of the largest and most complex public transport systems in the world, the London Underground (LUL), with a focus on 17 major transfer stations and 303 transfer movements. This study confirms that transfers pose a significant cost to LUL, and that cost is distributed unevenly across stations and across platforms at a station. Transfer stations are perceived very differently by passengers in terms of their overall cost and composition. The case study suggests that a better understanding of transfer behavior and improvements to the transfer experience could significantly benefit public transport systems.     

A topological route choice model for metro

This article presents a route choice model for public transit networks that incorporates variables related to network topology, complementing those found in traditional models based on service levels (travel time, cost, transfers, etc.) and users’ socioeconomic and demographic characteristics (income level, trip purpose, etc.). The topological variables represent concepts such as the directness of the chosen route and user knowledge of the network. For both of these factors, the necessary data is endogenous to the modelling process and can be quantified without the need for information-gathering beyond what is normally required for building route choice models. Other novel variables in the proposed formulation capture notions of user comfort such as vehicle occupancy rates and certain physical characteristics of network stations. We conclude that these new variables significantly improve the explanatory and predictive ability of existing route choice specifications.     

Modeling heterogeneous risk-taking behavior in route choice: A stochastic dominance approach

This paper proposes a unified approach to modeling heterogonous risk-taking behavior in route choice based on the theory of stochastic dominance (SD). Specifically, the first-, second-, and third-order stochastic dominance (FSD, SSD, TSD) are respectively linked to insatiability, risk-aversion and ruin-aversion within the framework of utility maximization. The paths that may be selected by travelers of different risk-taking preferences can be obtained from the corresponding SD-admissible paths, which can be generated using general dynamic programming. This paper also analyzes the relationship between the SD-based approach and other route choice models that consider risk-taking behavior. These route choice models employ a variety of reliability indexes, which often make the problem of finding optimal paths intractable. We show that the optimal paths with respect to these reliability indexes often belong to one of the three SD-admissible path sets. This finding offers not only an interpretation of risk-taking behavior consistent with the SD theory for these route choice models, but also a unified and computationally viable solution approach through SD-admissible path sets, which are usually small and can be generated without having to enumerate all paths. A generic label-correcting algorithm is proposed to generate FSD-, SSD-, and TSD-admissible paths, and numerical experiments are conducted to test the algorithm and to verify the analytical results.     

我国新能源汽车的关键技术与发展瓶颈

介绍我国新能源汽车的技术路线格局、关键技术及主要产品,探讨新能源汽车的发展瓶颈,并提出相应的对策建议。     

高沁高速公路郑庄至里必段路线方案研究

结合山区地形,按照"以人为本"和"安全、环保、舒适、和谐"的新理念,对典型路段的路线方案进行优化设计、比选分析,最终选择最佳路线方案。     

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基于广州居民出行调查成果,本文从模型架构、效用函数基本形式、参数标定及校核等几个方面对交通方式选择模型的构建进行研究. 提出了方式划分的基本原则,并针对无车家庭、有小汽车家庭和摩托车家庭构建层次划分. 以小汽车家庭为例,阐述方式划分的基本形式. 进而,提出了方式划分参数标定的方法和基本步骤以及系数校核的关键点. 最后将预测结果和实际观测数据进行比较,验证模型的有效性. 本文提出不同层次交通方式划分模型,提高了模型的精度,并在效用函数中引入收入、车辆拥有和吸引量等因素,增强了模型的适用性,为其他类似城市交通方式选择模型的构建提供一定的参考.     

隧道监控系统综合防雷设计与实践

为做好隧道监控系统的防雷工作,通过防直击雷、防雷电感应和雷电波侵入、等电位连接、屏蔽、合理布线等有效措施,形成层层保护结构,防止雷电侵入,确保监控机房设备、隧道视频终端设备及工作人员的安全。依据GB 50057-1994 2004《建筑物防雷设计规范》和GB 50343-2004《建筑物电子信息系统防雷技术规范》,根据监控系统的网络构架及监控系统防雷要求进行设计,指出防雷器选型应注意的问题,重点阐述隧道监控系统防雷设计方案的具体内容：摄像机防护、控制器防雷、监控中心设备的防雷等。1年多来,栾川长青公司隧道监控系统没有发生监控设备被雷击的事故,该方案可在类似工程中推广应用。     

基于合理路径的拥挤路网交通状态分析方法

为防止路网交通拥堵的扩散,考虑路段状态指标饱和度和行程时间的影响,建立了基于合理路径集的路网分析模型.将非拥挤区域从内到外分为控制层、诱导控制层、诱导层和无关层4个层次,反映了路网状态的空间分布和潜在演化趋势.基于交通分配得到的流量,对本文的状态分析模型进行了数值验证,仿真结果表明:各层次路段在路网中的比例随流量的增大而变化,且拥堵区域呈现扩张趋势;高峰时段各层次路段的比例为20%、5%、10%、10%和56%;同层次中饱和度越大的路段对拥堵区域的影响越大.     

隧道掘进机（TBM）选型探讨

我国山岭隧道的长度不断增加,数十公里的隧道不断投入到施工阶段,然而由于埋深大、施工支洞布置困难、环境保护要求高等因素影响,越来越多的硬岩掘进机（TBM）得以应用。TBM对地质条件的适应性不及钻爆法灵活,但适宜的地质条件下可以取得很高的施工进度,它可分为开敞式、单护盾、双护盾等不同类型。不同的TBM有不同的特点,不同的工...