Understanding time use: Daily or weekly data?

The appropriate duration of time diaries as a source of time use data is analyzed in a structured way. Nine detailed European surveys based on seven-days diaries are used in order to study different dimensions of data quality, duration and variability of activities, and modeling capabilities. Pseudo diaries of 1, 2 (one week, one weekend) and 3 (one week, both weekend) days are constructed to further analyze these issues, selecting the seven-days diaries data as a benchmark. Comparative results show that two and three-days weighted surveys seem to be an adequate surrogate for the information obtained in weekly surveys that capture a basic work–leisure cycle.     

Measurement biases in panel data

The objective of this paper is to examine reporting errors in panel data obtained from multi-day travel diaries. A distinction is made between within and between wave biases. The former leads to an increase in under-reporting associated with the number of days the diary is kept. The latter is related to the number of waves respondents have been participating, so-called panel experience. These biases imply that observed mobility changes between waves are partly due to reporting errors: without controlling for them, changes in mobility can not be inferred from the data. An important cause of these measurement errors is the increase in the number of days on which no trips at all were reported. In addition, shorter trips and less complex chains are more susceptible to underreporting. The methodology used in this paper provides a means of dealing with these problems. Attrition is taken into account by a rather simple measure. The paper concludes with a number of suggestions for sample and survey design.     

The design of environmentally aware travel diaries

Any policy addressing the concerns and trends associated with the impact of travel on the environment should be based on a solid understanding of the activities giving rise to them. While the measurement of the total environment loads by air or noise measurement stations is essential, it needs to be matched by the observation of the human behaviours creating them. This is especially true in the transport sector, which has been rightly or wrongly identified as having the potential to make a substantial contribution to the reduction of air and noise pollution. While the contribution of freight transport is of growing concern and importance, this paper focuses on the measurement of passenger transport throughout.

In the past transport planners have largely relied on the travel diary as their prime instrument to measure traveller behaviour. The travel diary is a survey instrument designed to record all movements during the course of one or more days including their relevant details. It is complemented by spearate household and personal forms for recording general information. In the following paper the term travel diary implies all three elements (the diary, the person form and the household form).

The remainder of the paper discusses to what extent and how the travel diary can be used to capture data for the assessment of policies directed at reducing the impact of transport on the social and natural environment. The requirements of a travel diary and the potential uses of new technologies in realising such a travel diary are then presented. A brief outlook on the possibilities of reasling such a diary concludes the paper.     

Weekly mobility of life cycle groups

This paper describes parts of a study of travel by urban residents on seven consecutive days. The conceptual structure of the research understands travel as a demand derived by a dynamic process of individuals and households allocating their budgets to activities within the framework posed by societal regimens. Societal rules have a time dimension which is repetitive with a weekly cycle. Thus, distinctive basic patterns of weekly mobility are expected for segments of the society and differences in the obligation to adhere to those basic patterns. The data used for testing these hypotheses is described and the issue of increasing reporting bias over the diary period is addressed. Sixteen life cycle groups of persons are selected here for the presentation of some findings.The profiles of trip rates for the groups over the seven days of the week (estimated with analysis of covariance) and the decomposition of the variances of trip rates into interindividual, intraindividual and systematic parts (by repeated measurement analysis) are reported. Characteristic differences in the volume of mobility, the shape of profiles and the variance components reflect different patterns of tripmaking for segments of the population over the week. It is concluded that even for well-defined person categories, interpersonal variety of mobility behavior is large but has to be seen in relation to even greater intrapersonal variability. Both components can best be understood within the period of one week which individuals use to organize their mobility.     

不同需求日高铁列车开行方案协同优化方法

不同需求日的出行需求在结构和总量上都存在差异,不仅需要提供与各需求日相匹配的运输能力,而且不同需求日的列车开行方案应有很大相似性,使高铁运输组织能平稳过渡。为权衡铁路运营成本和运输组织衔接,在考虑高铁运输组织平稳过渡前提下,谋求铁路运输成本和旅客出行费用最小,对不同需求日列车开行方案进行协同优化。由各需求日各OD对需求生成最大包络需求,以最大包络需求列车开行方案为备选列车集,产生各个需求日的列车开行方案。建立不同需求日开行方案协同优化双层规划模型,设计求解模型的遗传算法。算例分析表明,在公共列车集比例限制下,协同优化产生的开行方案具有较好评价指标,算法收敛性较好,体现了模型和算法的有效性。     

Transportation impacts of center-based telecommuting: Interim findings from the Neighborhood Telecenters Project

The transportation impacts of center-based telecommuting for 24 participants (representing 69 person-days of travel and 295 trips) in the California Neighborhood Telecenters Project are analyzed. Comparing non-telecommuting (NTC) day to telecommuting (TC) day travel shows that person-trips did not change significantly, whereas vehicle-trips increased significantly (by about one trip) on TC days. Both PMT and VMT decline significantly on TC days: by an average of 68 miles (74%) and 38 miles (65%), respectively. When these savings are weighted by the frequency of telecommuting, overall reductions in PMT and VMT come to 19% and 17%, respectively, of total weekday travel. Commute trips increase slightly (by 0.5 trips) but significantly, mainly due to lunch-time trips made home from the telecenter. Total non-commute travel does not increase, but there is a significant shift from other modes to driving alone on TC days. Commute mode split on NTC days is not affected by telecommuting. Travel on TC days tends to be compressed into fewer hours. Higher numbers of return home, eat meal, shopping, and social/recreational trips are made on TC days, in exchange for a reduction (to zero) in the number of change mode trips.