A conceptual and methdological framework for the generation of activity-travel patterns

This paper develops a conceptual framework for the generation of activity and travel patterns in the context of more general structures and presents an integrated model system as a step toward development of an improved travel demand forecasting model system. We propose a two-stage structure to model activity and travel behavior. The first stage, the stop generation and stop/auto allocation models, consists of the choices for the number of household maintenance stops and the allocation of stops and autos to household members. The second stage, the tour formation model, includes the choices for the number of tours and the assignment of stops to tours for each individual, conditional on the choices in the first stage. Empirical results demonstrate that individual and household socio-demographics are important factors affecting the first stage choices, the generation of maintenance stops and the allocation of stops and autos among household members, and the second stage choices, the number of tours and the assignment of stops to tours. This revised version was published online in June 2006 with corrections to the Cover Date.     

Conformity: How VMT-speed distributions can affect mobile emission inventories

Transportation conformity is a US regulatory process that requires that transportation modeling be integrated with air quality modeling. Consequently, every change to either modeling process is undertaken with great scrutiny by the regional governments, who have to use the models for demonstrating conformity. This paper explores the "trip versus link debate," which stems from the fact that the standard travel demand models used by most metropolitan planning organizations are primarily link oriented, while the air quality models have been primarily trip oriented. Using the Sacramento region we examine the effects on mobile source emissions inventories when speed-VMT distributions are constructed using the trip and link-based philosophies. The results of our study indicate that trip-based VMT-speed distributions produce consistently lower emissions estimates than the link-based distributions. We use the results to assert that deciding between a trip-based or link-based conformity modeling process involves more than the technical difficulty of changesto the models or the potential political ramifications, it involves assessing which method will provide the most accurate estimates of regional motor vehicle emissions. We also examine ways to think about constructing mobile source emission inventories.     

城市综合交通调查的规范与创新

城市综合交通调查在中国已有30余年的广泛实践,当前的信息化和大数据背景下正历经发展与变革.在分析城市综合交通调查现状问题的基础上,提出制定《城市综合交通体系规划交通调查导则》(以下简称《导则》)的必要性.从目标与总体框架、调查项目分类、术语定义、调查内容与问题选项分类、调查流程规范几个层面对《导则》的主要思想与关键内容进行解析.提出城市综合交通调查未来发展方向应是将信息化技术与传统调查手段结合,提高调查效率与质量,关注信息化手段未能涵盖的交通特征.     

Using the built environment to oversample walk,transit, and bicycle travel

Characteristics of the built environment (BE) have been associated with walk, transit, and bicycle travel. These BE characteristics can be used by transportation researchers to oversample households from areas where walk, transit, or bicycle travel is more likely, resulting in more observations of these uncommon travel behaviors. Little guidance, however, is available on the effectiveness of such built environment oversampling strategies. This article presents measures that can be used to assess the effectiveness of BE oversampling strategies and inform future efforts to oversample households with uncommon travel behaviors. The measures are sensitivity and specificity, positive likelihood ratio (LR+), and positive predictive value (PPV). To illustrate these measures, they were calculated for 10 BE-defined oversampling strata applied post-hoc to a Seattle area household travel survey. Strata with an average block size of <10 acres within a ¼ mile of household residences held the single greatest potential for oversampling households that walk, use transit, and/or bicycle.     

Multi-step prediction of experienced travel times using agent-based modeling

This paper develops an agent-based modeling approach to predict multi-step ahead experienced travel times using real-time and historical spatiotemporal traffic data. At the microscopic level, each agent represents an expert in a decision-making system. Each expert predicts the travel time for each time interval according to experiences from a historical dataset. A set of agent interactions is developed to preserve agents that correspond to traffic patterns similar to the real-time measurements and replace invalid agents or agents associated with negligible weights with new agents. Consequently, the aggregation of each agent’s recommendation (predicted travel time with associated weight) provides a macroscopic level of output, namely the predicted travel time distribution. Probe vehicle data from a 95-mile freeway stretch along I-64 and I-264 are used to test different predictors. The results show that the agent-based modeling approach produces the least prediction error compared to other state-of-the-practice and state-of-the-art methods (instantaneous travel time, historical average and k-nearest neighbor), and maintains less than a 9% prediction error for trip departures up to 60 min into the future for a two-hour trip. Moreover, the confidence boundaries of the predicted travel times demonstrate that the proposed approach also provides high accuracy in predicting travel time confidence intervals. Finally, the proposed approach does not require offline training thus making it easily transferable to other locations and the fast algorithm computation allows the proposed approach to be implemented in real-time applications in Traffic Management Centers.     

Activity patterns,time use,and travel of millennials: a generation in transition?

Millennials, defined in this study as those born between 1979 and 2000, became the largest population segment in the United States in 2015. Compared to recent previous generations, they have been found to travel less, own fewer cars, have lower driver’s licensure rates, and use alternative modes more. But to what extent will these differences in behaviour persist as millennials move through various phases of the lifecycle? To address this question, this paper presents the results of a longitudinal analysis of the 2003–2013 American Time Use Survey data series. In early adulthood, younger millennials (born 1988–1994) are found to spend significantly more time in-home than older millennials (born 1979–1985), which indicates that there are substantial differences in activity-time use patterns across generations in early adulthood. Older millennials are, however, showing activity-time use patterns similar to their prior generation counterparts as they age, although some differences – particularly in time spent as a car driver – persist. Millennials appear to exhibit a lag in adopting the activity patterns of predecessor generations due to delayed lifecycle milestones (e.g. completing their education, getting jobs, marrying, and having children) and lingering effects of the economic recession, suggesting that travel demand will resume growth in the future.     

Measuring community reaction to urban transportation impacts using Von Neumann‐Morgenstern utility theory

This paper attempts to measure the impacts of urban transportation system improvements or changes on the community. The community's perceptions of the impacts are represented by its utilities (or disutilities) over various ranges of values of the multiple attributes representing these impacts. The utility technique used in the evaluation is based upon von Neumann‐Morgenstern (vN‐M, 1947) Utility Theory, and is applied using Raiffa's (1970) Fractile Method.

The paper specifically applies the technique to model the perceptions of five subgroups within a community to the impact of a new light rail transit system that is being incorporated in the transportation system of the City of Calgary.

Results of the modeling indicate explicitly how the community changes its perception over ranges of values of the attributes evaluated. Biases of various subgroups within the community over these attributes are also shown. Statistical tests indicate that aggregated utility perceptions can represent the utility perceptions of the individual subgroups quite reasonably.     

斗轮式取料机行走位置精确定位

斗轮式取料机行走位置校正装置在定位中起到很重要的作用.分析了原有行走机构定位原理与状况.介绍了新定位装置的设计思路和实施方案,改革后提高了全场设备相互协同的效率和相互保护的可靠性.     

A Trip Reconstruction Tool for GPS-based Personal Travel Surveys

ABSTRACT

This article reports on the development of a trip reconstruction software tool for use in GPS-based personal travel surveys. Specifically, the tool enables the automatic processing of GPS traces of individual survey respondents in order to identify the road links traveled and modes used by each respondent for individual trips. Identifying the links is based on a conventional GIS-based map-matching algorithm and identifying the modes is a rule-based algorithm using attributes of four modes (walk, bicycle, bus and passenger-car). The tool was evaluated using GPS travel data collected for the study and a multi-modal transportation network model of downtown Toronto. The results show that the tool correctly detected about 79% of all links traveled and 92% of all trip modes.     

XML5163XLJ13型旅居客车开发

介绍XML5163XLJ13型旅居车的总体布置、结构特点,以及开发旅居客车的前景.