港口与运输方式及陆港联合选择的巢式Logit模型

为刻画托运人对港口、运输方式及陆港的联合选择行为,将港口费用、等待时间、班轮频率、货物价值、单次运量、运输成本、运输及通关时间、准班率、陆港服务作为效用变量,构建港口选择位于上层、运输方式及陆港选择位于下层的巢式Logit模型.基于辽宁部分城市集装箱托运人的RP/SP调查数据,对模型参数进行估计和检验.结果表明,低运量倾向选择公路运输,托运人对多式联运的运输成本、运输及通关时间比公路运输的更重视,对公路运输的准班率比多式联运的更重视,陆港服务对多式联运具有显著正向影响,巢式Logit模型比MNL模型具有更优的统计学特征.     

An improved Dial's algorithm for logit-based traffic assignment within a directed acyclic network

Abstract

Dial's algorithm is one of the most effective and popular procedures for a logit-type stochastic traffic assignment, as it does not require path enumeration over a network. However, a fundamental problem associated with the algorithm is its simple definition of ‘efficient paths’, which sometimes produces unrealistic flow patterns. In this paper, an improved algorithm based on the route extension coefficient is proposed in order to circumvent this problem, in which ‘efficient paths’ simultaneously consider link travel cost and minimum travel cost. Path enumeration is still not required and a similar computing efficiency with the original algorithm is guaranteed. A limitation of the algorithm is that it can only be applied to a directed acyclic network because a topological sorting algorithm is used to decide the order of the sequential calculation. A numerical example based on the Beijing subway network illustrates the effectiveness of the proposed algorithm. It is found that it is able to exclude most unrealistic paths, but include all reasonable paths when compared with path enumeration and the original Dial's algorithm.     

Gas anxiety and the charging choices of plug-in hybrid electric vehicle drivers

Plug-in hybrid electric vehicles (PHEVs) can provide many of the benefits of battery electric vehicles (BEVs), such as reduced petroleum consumption and greenhouse gas emissions, without the “range anxiety” that can accompany driving a vehicle with limited range when there are few charging opportunities. However, evidence indicates that PHEVs are often plugged in more frequently than BEVs in practice. This is somewhat paradoxical: drivers for whom plugging in is optional tend to do so more frequently than those for whom it is necessary. This has led to the coining of a new term – “gas anxiety” – to describe the apparent desire of PHEV drivers to avoid using gasoline. In this paper, we analyze the variables influencing the charging choices of PHEV owners, testing whether drivers express preferences consistent with the concept of gas anxiety. We analyze data collected in a web-based stated preference survey using a latent class logit model. The results reveal two classes of decision-making patterns among the survey respondents: (1) those who weight the cost of gasoline and the cost of recharging approximately equally (the cost-minimizing class), and (2) those who weight the cost gasoline more heavily than the cost of recharging (the gas anxiety class). Respondents in the gas anxiety class expressed a willingness to recharge at a charging station even when doing so would cost approximately four times as much as the cost of the gasoline avoided. While the gas anxiety class represents the majority of our sample, more recent PHEV adopters are more likely to be in the cost-minimizing class. Looking forward, this suggests that public charging station operators may need to price charging competitively with gasoline on a per-mile basis to attract PHEV owners.     

基于Logit模型的居住区共享泊位选择行为分析

为定量描述停车者对居住区共享泊位的选择行为影响因素,将停车者的个人属性与出行属性作为效用变量,将居住区共享泊位停车和路内就近停车作为选择肢,建立二项Logit模型。分析表明：个人月收入、停车时长、额外步行距离、费率差等为影响停车者选择居住区共享泊位停车的显著影响因素,其中额外步行距离和费率差对共享泊位选择概率的影响程度更大,较低层次的个人月收入变化对共享泊位选择概率的影响更大。     

Air itinerary shares estimation using multinomial logit models

ABSTRACT

The main goal of this study is the development of an aggregate air itinerary market share model. In order to achieve this, multinomial logit models are applied to distribute the city-pair passenger demand across the available itineraries. The models are developed at an aggregate level using open-source booking data for a large group of city-pairs within the US air transport system. Although there is a growing trend in the use of discrete choice models in the aviation industry, existing air itinerary share models are mostly focused on supporting carrier decision-making. Consequently, those studies define itineraries at a more disaggregate level using variables describing airlines and time preferences. In this study, we define itineraries at a more aggregate level, i.e. as a combination of flight segments between an origin and destination, without further insight into service preferences. Although results show some potential for this approach, there are challenges associated with prediction performance and computational intensity.     

Steady state analysis of towed marine cables

Efficient numerical schemes were presented for the steady state solutions of towed marine cables. For most of towed systems, the steady state problem can be resolved into two-point boundary-value problem, or initial value problem in some special cases where the initial values are available directly. A new technique was proposed and attempted to solve the two-point boundary-value problem rather than the conventional shooting method due to its algorithm complexity and low efficiency. First, the boundary conditions are transformed into a set of nonlinear governing equations about the initial values, then bisection method is employed to solve these nonlinear equations with the aid of 4th order Runge-Kutta method. In common sense, non-uniform (sheared) current is assumed, which varies in magnitude and direction with depth. The schemes are validated through the DE Zoysa's example, then several numerical examples are also presented to illustrate the numerical schemes.     

Determinants of ground transport modal choice in long-distance trips in Spain

In transport economics, modeling modal choice is a fundamental key for policy makers trying to improve the sustainability of transportation systems. However, existing empirical literature has focused on short-distance travel within urban systems. This paper contributes to the limited number of investigations on mode choice in medium- and long-distance travel. The main objective of this research is to study the impacts of socio-demographic and economic variables, land-use features and trip attributes on long-distance travel mode choice. Using data from 2007 Spanish National Mobility Survey we apply a multilevel multinomial logit model that accounts for the potential problem of spatial heterogeneity in order to explain long-distance travel mode choice. This approach permits us to compute how the probability of choosing among private car, bus and train varies depending on the traveler spatial location at regional level. Results indicate that travelers characteristics, trip features, cost of usage of transport modes and geographical variables have significant impacts on long-distance mode choice.     

具有模糊特性变量的出行方式预测Logit模型

基于非集计模型与模糊数学理论, 以城市群居民出行行为为研究对象, 选择出行者的出行时间和出行费用作为影响因素, 利用极大似然估计法进行参数标定, 通过t检验、命中率检验与优度检验, 将出行时间模糊化, 忽略出行费用的影响, 建立了具有模糊特性变量的出行方式预测Logit模型。将轨道交通与小汽车2种出行方式的时间模糊化参数分别选为0.1、0.3、0.5, 分析了出行方式与出行时间对居民出行行为的影响。分析结果表明: 轨道交通与小汽车的平均出行感知时间之比为0.8~1.2, 且2种出行感知时间同等程度变化; 当轨道交通出行时间模糊化参数为0.1, 小汽车出行时间小于70 min时, 出行者均选择轨道交通出行; 当轨道交通出行时间模糊化参数为0.3, 小汽车出行时间小于67 min时, 出行者继续选择轨道交通出行, 但当小汽车出行时间大于67 min, 小汽车出行时间模糊化参数分别为0.1、0.3时, 出行者选择小汽车出行; 当轨道交通出行时间模糊化参数为0.5, 小汽车出行时间小于58 min时, 出行者仍然选择轨道交通出行, 但当小汽车出行时间大于66 min时, 出行者均选择小汽车出行。     

轨道交通建设对沿线居住区位选择的影响

为了预测轨道交通建设对沿线居住区位选择的影响, 结合居民工资水平、交通可达性与住房价格等建立居民消费剩余模型, 建立了居住地Logit选择模型来确定因交通流量分布改变而导致的居住区位选择分布; 借助居民居住地与交通工具联合选择模型, 确定路面交通流量变化, 进而获得轨道交通运营后因交通成本变化引起的不同工资水平居民的居住选择变化情况, 分析了轨道交通建成导致住宅价格增长给居民的居住区位选择行为带来的二次影响; 以单中心城市为背景, 设定10个轨道交通站点为研究对象, 分别计算了8类不同工资类型的居民在轨道交通建设与房价增长后, 在10个轨道交通站点居住区位选择的变化。分析结果表明: 轨道交通建成后居民向远离城市中心的方向移动, 但工资水平较低的居民时间价值较低, 居住选择受其建成影响较小; 随着轨道交通沿线居住区位可达性的提升, 轨道交通附近房价增长, 最远的居住区位平均每平米房价增长2 619元, 最近的居住区位平均每平米房价增长11.5元, 与此同时, 工资水平较高的居民向城市中心移动, 工资水平较低的居民向远离城市中心的方向移动。