A parameterized consideration set model for airport choice: an application to the San Francisco Bay Area

Airport choice is an important air travel-related decision in multiple airport regions. This paper proposes the use of a probabilistic choice set multinomial logit (PCMNL) model for airport choice that generalizes the multinomial logit model used in all earlier airport choice studies. The paper discusses the properties of the PCMNL model, and applies it to examine airport choice of business travelers residing in the San Francisco Bay Area. Substantive policy implications of the results are discussed. Overall, the results indicate that it is important to analyze the choice (consideration) set formation of travelers. Failure to recognize consideration effects of air travelers can lead to biased model parameters, misleading evaluation of the effects of policy action, and a diminished data fit.     

Bayesian estimation of multinomial probit models of work trip choice

In this paper, we estimate a multinomial probit model of work trip mode choice in Seoul, Korea, using the Bayesian approach with Gibbs sampling. This method constructs a Markov chain Gibbs sampler that can be used to draw directly from the exact posterior distribution and perform finite sample likelihood inference. We estimate direct and cross-elasticities with respect to travel cost and the value of time. Our results show that travel demands are more sensitive to travel time than travel cost. The cross-elasticity results show that the bus has a greater substitute relation to the subway than the auto (and vice versa) and that an increase in the cost of an auto will increase the demand for bus transport more so than that of the subway.     

Modeling children’s school travel mode and parental escort decisions

Understanding of the activity-travel patterns of children is becoming increasingly important to various policy makers. Further, there is also a growing recognition that intra-household interactions need to be explicitly accommodated in travel models for realistic forecasts and policy evaluation. In the light of these issues, this paper contributes towards an overall understanding of the school-travel behavior of children and the related interdependencies among the travel patterns of parents and children. An econometric model is formulated to simultaneously determine the choice of mode and the escorting person for children’s travel to and from school. The 2000 San Francisco Bay Area Travel Survey (BATS) data are used in the model estimation process. Empirical results indicate that the characteristics of child like age, gender, and ethnicity, and employment and work flexibility characteristics of the parents have strong impacts on the mode choice decisions. In addition, the impacts of some of these attributes on the choice of mode to school are different from the corresponding impacts on the choice of mode from school. The distance between home and school is found to strongly and negatively impact the choice of walking to and from school, with the impact being stronger for walking to school. Several land-use and built-environment variables were explored, but were found not to be statistically significant predictors.

性能基导航中飞行技术误差估计研究综述

从人为因素、飞行器性能与环境因素3方面剖析了性能基导航中飞行技术误差的影响因素及其特性。依据导航方式与特定运行条件分类论述了基于飞行试验的飞行技术误差试验统计研究, 指出了此类研究方法的局限性。评述了基于成型机理的飞行技术误差方差估计模型与方法, 讨论了各种方法的特点和应用范围。从飞行技术误差估计方法与应用2方面分析了现有研究的局限性与后续研究展望。分析结果表明: 在手动操作方式下, 不同的飞行策略对飞行技术误差有较大影响, 航径偏移指示器的灵敏度与侧向飞行技术误差负相关。在航路和终端区, 某些通用航空飞行器的侧向飞行技术误差的标准差分别高达759.32、481.52m, 主要原因是未安装高精度导航系统。对飞行试验结果进行统计拟合的估计方法无法全面地覆盖全部机型、航段与天气条件, 因而具有一定的局限性, 而基于成型机理的飞行技术误差估计方法估计的侧向、高度飞行技术误差的标准差分别为2.68、1.13m, 通过与仿真结果和实测数据的比较, 方法的有效性得到验证。性能基导航设备在实时估计飞行技术误差时, 采用假设常值而不进行实时估计, 将会使飞行器处于危险中。从多重因素入手研究如何减小性能基导航中飞行技术误差是未来的重要研究方向。     

航班延误恢复调度的混合粒子群算法

为了优化航班延误恢复调度, 考虑了航班延误的经济效益、社会影响和经济损失构成, 定义了航线影响因子, 构建了一种新的航班延误恢复调度模型, 将局部搜索方法引入到粒子群算法中, 提出了求解航班延误恢复调度问题的混合粒子群算法。计算结果表明: 与先来先服务调度方法相比, 混合粒子群算法可以减少航班延误损失4.2%, 与基本粒子群算法和进化策略算法相比, 混合粒子群算法平均可减少航班延误损失2.0%, 随着航班延误恢复规模的增大, 算法优势会更明显。     

基于飞行流量耦合的区域容量改进模型

研究了包括多个扇区的区域容量评估问题, 通过分析飞行流量在空域单元之间产生耦合约束因素, 提出了空域单元的耦合容量, 研究了区域耦合容量的影响因素。结合管制员工作负荷等限制建立了区域耦合容量的多目标整数规划模型, 并使用该模型计算了兰州区域各空域单元耦合容量。计算结果表明: 扇区1、2、3耦合容量分别为22、19、33架次.h^-1, 小于其最大容量; 区域耦合容量小于区域仿真容量评估结果, 因此, 该模型更有利于合理分配空域资源。     

The effect of attitudes toward cars and public transportation on behavioral intention in commuting mode choice—A comparison across six Asian countries

This study investigated the contribution of psychological factors in explaining the choice of transportation mode in six Asian countries. Data were collected from 1118 respondents in Japan, Thailand, China, Vietnam, Indonesia, and the Philippines. The dependent variable was the intention to use one of three modes for work travel after getting a job: car, public transit, or other modes. The explanatory variables were three attitude factors taken from a previous study, including: 1/symbolic affective, reflecting affective motives of travel mode use; 2/instrumental, referring to functional attributes of travel modes; and 3/social orderliness which represents for environmental friendliness, safety, altruism, quietness et cetera. Several logit model estimates were made using the samples from the six countries separately and together. We obtained three main findings. First, attitude variables about the car were all significant determinants for the entire sample from Asian countries. Second, the social orderliness aspect of public transit was a common concern of respondents from developing countries in selecting this mode for work trips. Third, in countries in which the intent to use a car was not very high, attitude factors about the car were found to be significant determinants of the behavioral intention to commute by car but were less significant in countries in which the desire to use a car was high.     

Expanding scope of hybrid choice models allowing for mixture of social influences and latent attitudes: Application to intended purchase of electric cars

Recently, policy makers’ expectations about the role of electric cars in reducing emissions have risen substantially. In parallel, academic research on purchase intentions has dramatically increased. Originally, most studies have focused on utility attributes and price. More recently, several hybrid choice models have been estimated to include the impact of attitudes on choice probabilities. In addition, a few studies have caught the attention to social influence. In contributing to this line of research, this paper reports the results of an expanded hybrid choice, which simultaneously estimated all these different effects in a single integrated model of purchase intention. Results indicate that the model performs well. Costs considerations contribute most to the utility of electric cars. Social influence is less important, but there is also evidence that people tend to take it into consideration when there are positive public opinions about electric cars and the market share becomes almost half of friends of their social network. The intention to purchase an electric car is also influenced by attitudes about environmental concerns and technology acceptance.     

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.     

Modelling parking choices considering user heterogeneity

We examine car driver’s behaviour when choosing a parking place; the alternatives available are free on-street parking, paid on-street parking and parking in an underground multi-storey car park. A mixed logit model, allowing for correlation between random taste parameters and estimated using stated choice data, is used to infer values of time, both when looking for a parking space and for accessing the final destination. Apart from the cost of parking, we found that vehicle age was a key variable when choosing where to park in Spain. We also found that the perception of the parking charge was fairly heterogeneous, depending both on the drivers’ income levels and whether or not they were local residents. Our results can be generalised for personalised policy making related with parking demand management.