Women’s mode and trip structure choices in daily activity-travel: a developing country perspective

ABSTRACT

In this paper, we analyze the travel patterns of Iranian women, where typical patriarchal views and specific social and cultural norms may differ from the patterns of those in western societies. In addition to inherent psycho-physical gender differences, women in Iran can face special constraints forcing them not to be involved in all activity-travel patterns that people in developed countries usually undertake. We pay special attention to the role of marital and employment status on women’s activity-travel patterns. To this end, we develop a joint mode and daily activity pattern (DAP) discrete choice model, which is a two-level mixed nested Logit. The upper nest of the proposed model embodies women’s DAP choices, and the lower nest belongs to the mode choices. In this paper, we try to show how different factors in a patriarchal Muslim society like Iran affect or restrict women’s type and structure of activity-travel patterns.     

Prediction of Tyre-Road Friction with an Inverted-Boat Shaped Pressure Distribution

In this paper, a predictive model is formulated to describe the frictional forces between the tyre and road. The model is based on an inverted-boat normal pressure distribution. The determination of the input parameters is simplified by the suggested stationary point approach for calculation of the frictional coefficients, which are analytically obtained. The verification of the established model shows that the predicted values are in a good agreement with measured data. A sensitivity study of the shape factors demonstrates that it is necessary to take the unsymmetric normal pressure distribution proposed in this paper into consideration to accurately predict frictional forces.     

阻抗在电磁场中的推广与应用

在研究微波甚至更高频段的电磁现象时由于难以给出电压电流的定义，因而传统意义上的电路阻抗慨念不冉适用,由电路阻抗联系了器件周围电磁场这一物理实质出发，总结电磁场与电磁波中三类阻抗及其在现代电磁工程中的应用，指出电磁波的波阻抗有着明确的方向，表明将阻抗的慨念引入电磁场，可以有效地利用电路的慨念方法简化对某些复杂电磁场问题的分析.     

A system dynamics approach to land use/transportation system performance modeling Part I: Methodology

This paper presents a system dynamics approach to simultaneous land use/transportation system performance modeling. A model is designed based on the causality functions and feedback loop structure between a large number of physical, socioeconomic, and policy variables. The model consists of 7 sub‐models: population, migration of population, household, job growth‐employment‐land availability, housing development, travel demand, and traffic congestion level. The model is formulated in DYNAMO simulation language, and tested on a data set from Montgomery County, MD. In Part I: Methodology, the overall approach and the structure of the model system is discussed and the causal‐loop diagrams and major equations are presented. In Part II: Application, the model is calibrated and tested with data from Montgomery County, MD. Least square method and overall system behavior are used to estimate the model parameters. The model is fitted with the 1970–80 data and validated with the 1980–1990 data. Robustness and sensitivities with respect to input parameters such as birth rate or regional economy growth are analyzed. The model performance as a policy analysis tool is examined by predicting the year by year impacts of highway capacity expansion on land use and transportation system performance. While this is a first attempt in using dynamic system simulation modeling in simultaneous treatment of land use and transportation system interactions, and model development and application are limited due to data availability, the results indicate that the proposed method is a promising approach in dealing with complex urban land use/transportation modeling.     

Rail freight transportation: A review of recent optimization models for train routing and empty car distribution

This paper describes two types of rail transportation problems in detail. These are train routing and makeup, and empty car distribution problems. Some of the recent optimization models which address these problems are reviewed and the areas for potential improvements in rail transportation literature are identified. The type of interactions which exist between routing, makeup, and empty car distribution decisions are highlighted and potential areas for future research are identified.     

双平面焊接圆管截面DKT节点的中心撑杆鞍点及冠点位置的应力集中系数(英文)

A set of parametric stress analyses was carried out for two-planar tubular DKT-joints under different axial loading conditions.The analysis results were used to present general remarks on the effects of the geometrical parameters on stress concentration factors(SCFs) at the inner saddle,outer saddle,and crown positions on the central brace.Based on results of finite element(FE) analysis and through nonlinear regression analysis,a new set of SCF parametric equations was established for fatigue design purposes.An assessment study of equations was conducted against the experimental data and original SCF database.The satisfaction of acceptance criteria proposed by the UK Department of Energy(UK DoE) was also checked.Results of parametric study showed that highly remarkable differences exist between the SCF values in a multi-planar DKT-joint and the corresponding SCFs in an equivalent uni-planar KT-joint having the same geometrical properties.It can be clearly concluded from this observation that using the equations proposed for uni-planar KT-connections to compute the SCFs in multi-planar DKT-joints will lead to either considerably under-predicting or over-predicting results.Hence,it is necessary to develop SCF formulae specially designed for multi-planar DKT-joints.Good results of equation assessment according to UK DoE acceptance criteria,high values of correlation coefficients,and the satisfactory agreement between the predictions of the proposed equations and the experimental data guarantee the accuracy of the equations.Therefore,the developed equations can be reliably used for fatigue design of offshore structures.     

A time-use activity-pattern recognition model for activity-based travel demand modeling

This study develops a new comprehensive pattern recognition modeling framework that leverages activity data to derive clusters of homogeneous daily activity patterns, for use in activity-based travel demand modeling. The pattern recognition model is applied to time use data from the large Halifax STAR household travel diary survey. Several machine learning techniques not previously employed in travel behavior analysis are used within the pattern recognition modeling framework. Pattern complexity of activity sequences in the dataset was recognized using the FCM algorithm, and resulted in identification of twelve unique clusters of homogeneous daily activity patterns. We then analysed inter-dependencies in each identified cluster and characterized the cluster memberships through their socio-demographic attributes using the CART classifier. Based on the socio-demographic characteristics of individuals we were able to correctly identify which cluster individuals belonged to, and also predict various information related to their activities, such as start time, duration, travel distance, and travel mode, for use in activity-based travel demand modeling. To execute the pattern recognition model, the 24-h activity patterns are split into 288 three dimensional 5 min intervals. Each interval includes information on activity types, duration, start time, location, and travel mode if applicable. Results from aggregated statistical evaluation and Kolmogorov–Smirnov tests indicate that there is heterogeneous diversity among identified clusters in terms of temporal distribution, and substantial differences in a variety of socio-demographic variables. The homogeneous clusters identified in this study may be used to more accurately predict the scheduling behavior of specific population groups in activity-based modeling, and hence to improve prediction of the times and locations of their travel demands. Finally, the results of this study are expected to be implemented within the activity-based travel demand model, Scheduler for Activities, Locations, and Travel (SALT).

     

Easing or tightening control strategies: determination of COVID-19 parameters for an agent-based model

Some agent-based models have been developed to estimate the spread progression of coronavirus disease 2019 (COVID-19) and to evaluate strategies aimed to control the outbreak of the infectious disease. Nonetheless, COVID-19 parameter estimation methods are limited to observational epidemiologic studies which are essentially aggregated models. We propose a mathematical structure to determine parameters of agent-based models accounting for the mutual effects of parameters. We then use the agent-based model to assess the extent to which different control strategies can intervene the transmission of COVID-19. Easing social distancing restrictions, opening businesses, speed of enforcing control strategies, quarantining family members of isolated cases on the disease progression and encouraging the use of facemask are the strategies assessed in this study. We estimate the social distancing compliance level in Sydney greater metropolitan area and then elaborate the consequences of moderating the compliance level in the disease suppression. We also show that social distancing and facemask usage are complementary and discuss their interactive effects in detail.

     

Performance analysis of crowd-shipping in urban and suburban areas

Transportation - Crowd logistics is a novel shipping concept where delivery operations are carried out by using existing resources, namely vehicle capacity and drivers from the crowd, thereby...     

Improving the coexistence of offshore wind farms and shipping: an international comparison of navigational risk assessment processes

The continued growth and evolution of the offshore wind industry, and the emergence of other novel marine uses such as wave and tidal generators, have upped the ante for spatial planners, as well as consenting and approval authorities in various coastal states. These stakeholders rely on processes such as navigational risk assessments (NRAs) to balance safety and efficiency requirements and to make optimal decisions over use of space. Given the increasingly complex and crowded seascape, however, there are some apprehensions about potential shortcomings in these NRA processes. There is also some concern that these inadequacies may lead to unsafe or inefficient marine spatial use. To understand how NRA processes can be improved further, a literature review is conducted, followed by a survey of respondents who are involved in the planning, consenting and/or approval of offshore wind farms across seven different countries. A summary of the NRA processes in these seven countries is presented, and several shortcomings are identified. Based on the findings of the survey, a list of recommendations is presented to enhance existing NRA processes—and to improve the coexistence of shipping and offshore wind farms (OWFs).