An activity-episode generation model that captures interactions between household heads: development and empirical analysis

In this paper, we develop an approach for modeling the daily number of non-work, out-of-home activity episodes for household heads that incorporates in its framework both interactions between such members and activity setting (i.e. independent and joint activities). Trivariate ordered probit models are estimated for the heads of three household types – couple, non-worker; couple, one-worker; and couple, two-worker households – using data from a trip diary survey that was conducted in the Greater Toronto Area (GTA) during 1987. Significant interactions between household heads are found. Moreover, the nature of these interactions is shown to vary by household type implying that decision-making structures and, more generally, household dynamics also vary by household type. In terms of predictive ability, the models incorporating interactions are found to predict more accurately than models excluding interactions. The empirical findings emphasize the importance of incorporating interactions between household members in activity-based forecasting models.     

Modeling stochastic perception error in the mean-excess traffic equilibrium model

In this paper, we extend the α-reliable mean-excess traffic equilibrium (METE) model of Chen and Zhou (Transportation Research Part B 44(4), 2010, 493-513) by explicitly modeling the stochastic perception errors within the travelers’ route choice decision processes. In the METE model, each traveler not only considers a travel time budget for ensuring on-time arrival at a confidence level α, but also accounts for the impact of encountering worse travel times in the (1 − α) quantile of the distribution tail. Furthermore, due to the imperfect knowledge of the travel time variability particularly in congested networks without advanced traveler information systems, the travelers’ route choice decisions are based on the perceived travel time distribution rather than the actual travel time distribution. In order to compute the perceived mean-excess travel time, an approximation method based on moment analysis is developed. It involves using the conditional moment generation function to derive the perceived link travel time, the Cornish-Fisher Asymptotic Expansion to estimate the perceived travel time budget, and the Acerbi and Tasche Approximation to estimate the perceived mean-excess travel time. The proposed stochastic mean-excess traffic equilibrium (SMETE) model is formulated as a variational inequality (VI) problem, and solved by a route-based solution algorithm with the use of the modified alternating direction method. Numerical examples are also provided to illustrate the application of the proposed SMETE model and solution method.     

Uncertain benefits: Application of Bayesian melding to the Alaskan Way Viaduct in Seattle

Uncertainty is inherent in major infrastructure projects, but public decision-making for such projects ignores it. We investigate the uncertainty about the future effects of tearing down the Alaskan Way Viaduct in downtown Seattle, using an integrated model of housing, jobs, land use and transportation, on outcomes including average commute times. Our methodology combines the urban simulation model UrbanSim with the regional transportation model. We assess uncertainty using Bayesian melding, yielding a full predictive distribution of average commute times on 22 different routes in 2020. Of these routes, 14 do not include the viaduct and eight do. For the 14 base routes that do not include the viaduct, the predictive distributions overlap substantially, and so there is no indication that removing the viaduct would increase commute times for these routes. For each of the eight routes that do include the viaduct, the 95% predictive interval for the difference in average travel times between the two scenarios includes zero, so there is not strong statistical support for the conclusion that removing the viaduct would lead to any increase in travel times. However, the median predicted increase is positive for each of these routes, with an average of 6 min, suggesting that there may be some measurable increase in travel time for drivers that use the viaduct as a core component of their commute.     

基于混合Logit模型的旅客对短途高速铁路列车选择行为

以南京到上海和南京到杭州的短途高速铁路客流为背景,应用行为调查法与意向调查法开展客流调查,获取客流数据.基于选择行为理论,以旅客对列车的选择作为因变量,旅客个体特征、出行特征、列车服务水平作为白变量,基于多项式Logit模型构建混合Logit模型,拟合客流调查数据.结果 表明:混合Logit模型的拟合优度高于多项式Lo...     

Management Cybernetics: A New Institutional Framework for Coastal Management

This article analyzes institutional arrangements for the delivery of coastal programs through a new way of thinking about their evolution and structure. The notion of three distinct "dimensions" describing the phases in the evolution of institutional arrangements is introduced. The notion of dimensions is developed from conceptualizing about how institutional arrangements are diagrammed. This allows the visualization of how individual institutions and key stakeholders relate to each other in the delivery of coastal programs, how effective these relationships are, and how their relationships could be redesigned. "Dimensional thinking" enables the re-examination of existing institutional design of coastal programs and how these can evolve to meet the challenges of the new millennium. It is concluded that institutional arrangements have grown from a single dimensional view, where institutions (mainly governmental) delivered programs in isolation, through to the present second dimension where agency programs are managed through coordinating bodies and through coastal management plans. It is argued that a third dimension of institutional arrangements, one that recognizes and embraces the rapid pace of change in this century, will be needed that is aligned by themes rather than by organizational structure. To illustrate a third dimension a visualization tool is developed drawing from management cybernetics. It recognizes the increasing importance of formal and informal networks in relation to traditional modernist hierarchical management by recognizing multiple stakeholders (government at all levels, industry, advocacy groups, conservation interests, and the broader community) and their degree of mutual dependence. Dimensional thinking has the potential to institutionalize the interaction between these multiple stakeholders to ensure the effective delivery of coastal programs in the new millennium. A single answer to what the third dimension of coastal management program evolution should include is not presented. Rather, an approach is presented that allows coastal managers to move forward in the debate on redesigning coastal programs to meet today's complex suite of issues, values, and interests. An experimental case study from Western Australia is used to illustrate the potential application of the dimensional thinking to coastal management institutional design in that State's coastal program.     

Mussel and Seaweed Cultivation in Offshore Wind Farms: An Opinion Survey

German coastal regions and adjacent offshore waters are claimed for a variety of different, and often overlapping, uses. Conflicts of interest are expected to increase due to the planned construction of offshore wind farms. The development of an integrated approach combining different commercial activities, such as open ocean aquaculture and wind farming, could be a possible solution to overcome these conflicts. To illuminate existing perception and opinions on this multiple-use idea, this study examines the attitudes of representatives of eight different actor groups toward potential offshore wind farm–mariculture integration in the German North Sea. Results from our questionnaire survey show that the respondents’ attitudes toward the suggested multiple-use setting seem to be largely influenced by their general opinion toward offshore wind farms. The Fisheries actor group differs from the other questioned groups in that negative attitudes are overall predominant. This case study points to the need for a credible mechanism that more successfully integrates key actor groups, such as fisheries, into future planning and research issues.     

基于活动链的出行需求预测方法综述

基于活动链出行预测理论主要研究人们对社会经济活动(以下简称活动)和出行行为的决策特性。介绍此理论的发展过程,给出6个重要的模型系统,并简要评价各个模型的优缺点。然后简单介绍1994年由Ben Akiva提出的基于活动链出行需求模型,进一步说明系统的框架和预测过程。通过对基于活动链理论发展过程和实际模型应用效果的分析,给出目前模型系统存在的缺点和问题,探索改进出行需求预测方法的途径。     

Decomposing travel times measured by probe-based traffic monitoring systems to individual road segments

In probe-based traffic monitoring systems, traffic conditions can be inferred based on the position data of a set of periodically polled probe vehicles. In such systems, the two consecutive polled positions do not necessarily correspond to the end points of individual links. Obtaining estimates of travel time at the individual link level requires the total traversal time (which is equal to the polling interval duration) be decomposed. This paper presents an algorithm for solving the problem of decomposing the traversal time to times taken to traverse individual road segments on the route. The proposed algorithm assumes minimal information about the network, namely network topography (i.e. links and nodes) and the free flow speed of each link. Unlike existing deterministic methods, the proposed solution algorithm defines a likelihood function that is maximized to solve for the most likely travel time for each road segment on the traversed route. The proposed scheme is evaluated using simulated data and compared to a benchmark deterministic method. The evaluation results suggest that the proposed method outperforms the bench mark method and on average improves the accuracy of the estimated link travel times by up to 90%.