An activity-based approach for scheduling multimodal transit services

This paper proposes a new activity-based transit assignment model for investigating the scheduling (or timetabling) problem of transit services in multi-modal transit networks. The proposed model can be used to generate the short-term and long-term timetables of multimodal transit lines for transit operations and service planning purposes. The interaction between transit timetables and passenger activity-travel scheduling behaviors is captured by the proposed model, as the activity and travel choices of transit passengers are considered explicitly in terms of departure time choice, activity/trip chain choices, activity duration choice, transit line and mode choices. A heuristic solution algorithm which combines the Hooke–Jeeves method and an iterative supply–demand equilibrium approach is developed to solve the proposed model. Two numerical examples are presented to illustrate the differences between the activity-based approach and the traditional trip-based method, together with comparison on the effects of optimal timetables with even and uneven headways. It is shown that the passenger travel scheduling pattern derived from the activity-based approach is significantly different from that obtained by the trip-based method, and that a demand-sensitive (with uneven headway) timetable is more efficient than an even-headway timetable.     

State-of-the art of freight forecast modeling: lessons learned and the road ahead

In this paper we review freight forecasting models and current advances and needs with respect to data and model development. We then present a case study to suggest which models should be developed for the State of California in the US. We suggest several alternatives including an aggregate commodity flow model, a disaggregate regional logistics model and a hybrid regional logistics model with a truck touring model. We point out however, that the data requirements for the latter model would be extensive. In addition, the development of hybrid models, for example progress in the integration of regional logistics models with urban truck touring models, will introduce new problems such as reconciling the outputs of multiple models for consistency.     

Treatment of seasonal tickets for public transport in estimation and application of mode/destination choice models

A new model system dealing with trips of length up to 100 km has recently been developed in Norway. A new way of dealing with seasonal passes for public transport is used in the travel-to-work model. The objective was to account for the fact that a respondent that posses a seasonal pass for public transport may behave as if public transport is free on the day they report a travel diary. On the other hand, we can not assume that public transport is free for respondents that used other modes of transport or that public transport is free to alternative destinations. This problem was solved by defining seasonal pass as a separate alternative in the form of a nest that included all modes of travel. The cost of a seasonal pass is a common cost for all modes in the nest and will thus not affect the choice within the nest. The estimation of this specification is compared with the more common approach of assigning an average cost per day based on the cost of a monthly pass and the number of workdays in a month. The comparison indicates that the “average cost per day” approach may produce biased estimates for several parameters. It also turns out that the cost parameter for seasonal pass is higher than the parameter for “out of pocket” cost, probably reflecting that there will be some uncertainty with respect to the actual use of a seasonal pass.     

A modelling system to simulate goods movements at an urban scale

The paper reports a modelling system to simulate goods movements at an urban scale. It allows joint analysis of choices made by end-consumers (assumed to be families) and retailers. These movements are examined at two levels: analysis of commodity flows, in terms of quantity, generated by the consumption of commodities; analysis of commodity flows, in terms of vehicles, due to restocking. The first level allows us to calculate the goods quantity flows due to consumption and restocking; the second level allows us to determine the service, vehicles used and target time, as well as the route chosen for restocking sales outlets in order to estimate vehicle flows on the urban/metropolitan transportation network. The modelling system is a multi-step model and considers a disaggregated approach for each decisional level.     

A comprehensive analysis of household transportation expenditures relative to other goods and services: an application to United States consumer expenditure data

This paper proposes a multiple discrete continuous nested extreme value (MDCNEV) model to analyze household expenditures for transportation-related items in relation to a host of other consumption categories. The model system presented in this paper is capable of providing a comprehensive assessment of how household consumption patterns (including savings) would be impacted by increases in fuel prices or any other household expense. The MDCNEV model presented in this paper is estimated on disaggregate consumption data from the 2002 Consumer Expenditure Survey data of the United States. Model estimation results show that a host of household and personal socio-economic, demographic, and location variables affect the proportion of monetary resources that households allocate to various consumption categories. Sensitivity analysis conducted using the model demonstrates the applicability of the model for quantifying consumption adjustment patterns in response to rising fuel prices. It is found that households adjust their food consumption, vehicular purchases, and savings rates in the short run. In the long term, adjustments are also made to housing choices (expenses), calling for the need to ensure that fuel price effects are adequately reflected in integrated microsimulation models of land use and travel.     

Estimation method for railway passengers’ train choice behavior with smart card transaction data

Smart card systems have become the predominant method of collecting public transport fares in Japan. Transaction data obtained through smart cards have resulted in a large amount of archived information on how passengers use public transportation. The data have the potential to be used for modeling passenger behavior and demand for public transportation. This study focused on train choices made by railway passengers. If each passenger’s train choice can be identified over a long period of time, this information would be useful for improving the customer relationship management of the railway company and for improving train timetables. The aim of this study was to develop a methodology for estimating which train is boarded by each smart card holder. This paper presents a methodology and an algorithm for estimation using long-term transaction data. To validate the computation time and accuracy of the estimation, an empirical analysis is carried out using actual transaction data provided by a railway company in Japan. The results show that the proposed method is capable of estimating passenger usage patterns from smart card transaction data collected over a long time period.     

广州地铁3号线首通段车站火灾模式调试中执行失败的解决方案

广州地铁3号线首通段车站火灾模式调试过程中,出现火灾模式执行失败,主要原因在于风阀延时保护模块动作切断电源。对发现的问题及故障原因进行了详细分析,讨论了机电设备控制系统与智能低压的通讯、风阀的控制原理,提出了解决方案。     

城市轨道交通事故故障应急处置相关问题研究

研究了城市轨道交通事故故障应急处置的机制及基本原则。应急反应机制和应急处理机制是应急处置机制的重要组成部分。在应急反应机制中,提出建立由高技术支持的轨道交通应急处置信息管理和发布系统,做好信息的采集、处理和发布,实现事故故障预警;在应急处理机制中,构建完整规范的事故故障预案体系,实现预案的及时更新、有效管理、方便学习和考核以及预案效果的评价和仿真。     

广州市轨道交通自动售检票系统现场设备数量的确定

通过广州市已运营、已建、在建的各条轨道交通线自动售检票系统的实例,对其现场设备数量的确定进行探讨。实践证明,除了依据客流、列车行车对数、设备通过能力等客观因素外,还应根据实际运用的经验及结合车站建筑结构对现场设备数量的确定作进一步完善,使系统充分发挥自身的功能和作用。