A dynamic analysis of person and household activity and travel patterns using data from the first two waves in the Puget Sound Transportation Panel

Daily activity participation and travel patterns are examined using data from the Puget Sound Transportation Panel (PSTP), which contains two-pairs of daily travel diary information (wave 1 in 1989 and wave 2 in 1990). Summary data of the travel diaries at the person and household levels are obtained using cluster analysis. At the person level, four clusters are found reasonable for both activity and travel. The four-cluster solutions indicate substantial day-to-day variation in activity participation and similarity in travel behavior over time. Temporal changes are analyzed using contingency table methods and log-linear models. The analysis reveals that activity participation and mobility present many regularities over time. Transitions within each wave show strong dependence between two days for both activity and travel, with higher dependency for the travel patterns than for the activity patterns. These are consistent when the analysis focuses on a longer period such as a year. Temporal dependencies appear to be stronger in the household-based than the person-based analysis. A hierarchical structure is also found in the relationship between activity and travel clusters. The link between activity and travel is much stronger within a day, weaker from one day to another, and the least strong from one year to the next. Important irregularities, however, are found and may be due to scheduling time-frames adopted by the respondents that are only partially captured in the data used.     

Analysis of vehicle ownership evolution in Montreal,Canada using pseudo panel analysis

This paper employs a pseudo-panel approach to study vehicle ownership evolution in Montreal region, Canada using cross-sectional origin–destination survey datasets of 1998, 2003 and 2008. Econometric modeling approaches that simultaneously accommodate the influence of observed and unobserved attributes on the vehicle ownership decision framework are implemented. Specifically, we estimate generalized versions of the ordered response model—including the generalized, scaled- and mixed-generalized ordered logit models. Socio-demographic variables that impact household’s decision to own multiple cars include number of full and part-time working adults, license holders, middle aged adults, retirees, male householders, and presence of children. Increased number of bus stops, longer bus and metro lengths within the household residential location buffer area decrease vehicle fleet size of households. The observed results also varied across years as manifested by the significance of the interaction terms of some of the variables with the time elapsed since 1998 variable. Moreover, variation due to unobserved factors are captured for part-time working adults, number of bus stops, and length of metro lines. In terms of the effect of location of households, we found that some neighborhoods exhibited distinct car ownership temporal dynamics over the years.     

Modelling the joint choice of activity timing and duration

This paper develops a model of activity and trip scheduling that combines three elements that have to date mostly been investigated in isolation: the duration of activities, the time-of-day preference for activity participation and the effect of schedule delays on the valuation of activities. The model is an error component discrete choice model, describing individuals’ choice between alternative workday activity patterns. The utility function is formulated in a flexible way, applying a bell-shaped component to represent time-of-day preferences for activities. The model was tested using a 2001 data set from the Netherlands. The estimation results suggest that time-of-day preferences and schedule delays associated with the work activity are the most important factors influencing the scheduling of the work tour. Error components included in the model suggest that there is considerable unobserved heterogeneity with respect to mode preferences and schedule delay.     

Analysis of travel activity determinants using robust statistics

This study investigates travel behavior determinants based on a multiday travel survey conducted in the region of Ghent, Belgium. Due to the limited data reliability of the data sample and the influence of outliers exerted on classical principal component analysis, robust principal component analysis (ROBPCA) is employed in order to reveal the explanatory variables responsible for most of the variability. Interpretation of the results is eased by utilizing ROSPCA. The application of ROSPCA reveals six distinct principal components where each is determined by a few variables. Among others, our results suggest a key role of variable categories such as journey purpose-related impedance and journey inherent constraints. Surprisingly, the variables associated with journey timing turn out to be less important. Finally, our findings reveal the critical role of outliers in travel behavior analysis. This suggests that a systematic understanding of how outliers contribute to observed mobility behavior patterns, as derived from travel surveys, is needed. In this regard, the proposed methods serve for processing raw data typically used in activity-based modelling.     

The impact of activity chaining on the duration of daily activities

There is a broad body of theoretical and empirical literature dealing with trip chaining behaviour. This paper adds to the literature while focusing on the impact of activity chaining on the duration of time spent on individual purposes. Two questions in particular are addressed: first, does an additional purpose added to a trip chain affect the duration of the activities included? Second, is there any pattern of included activities that explains differences in duration? Duration data models are employed using German data. We find evidence that the number of purposes influences duration significantly. Leisure, shopping and personal business activities are affected by the occurrence of obligatory activities (work, school/university). We cannot find any evidence that personal business or leisure activities influence the duration of shopping, whereas the opposite is supported. Therefore, in terms of daily activities, obligatory and shopping activities are superior to leisure and personal business. We conclude that activity chaining and especially the pattern of combined purposes affect the duration of activities allocated to single purposes while controlling for a wide range of other explanatory variables. The results can be used in transport and simulation models.     

A latent class accelerated hazard model of social activity duration

Over the past decade, activity scheduling processes have gained increasing attention in the field of transportation research. However, still little is known about the scheduling of social activities even though these activities account for a large and growing portion of trips. This paper contributes to this knowledge. We analyze how the duration of social activities is influenced by social activity characteristics and characteristics of the relationship between the respondent and the contacted person(s). To that end, a latent class accelerated hazard model is estimated, based on social interaction diary data that was collected in the Netherlands in 2008. Chi-square tests and analyses of variance are used to test for significant relations between the latent classes and personal and household characteristics. Findings suggest that the social activity characteristics and the characteristics of the relationship between the socializing persons are highly significant in explaining social activity duration. This shows that social activities should not be considered as a homogenous set of activities and it underlines the importance of including the social context in travel-behavior models. Moreover, the results indicate that there is a substantial amount of latent heterogeneity across the population. Four latent classes are identified, showing different social activity durations, and different effects for both categories of explanatory variables. Latent class membership can be explained by household composition, socio-economic status (education, income and work hours), car ownership and the number of interactions in 2 days.     

Analysis of variability in multi-day GPS imputed activity-travel diaries using multi-dimensional sequence alignment and panel effects regression models

The use of GPS devices and smartphones has made feasible the collection of multi-day activity-travel diaries. In turn, the availability of multi-day travel diary data opens up new avenues for analyzing dynamics of individual travel behavior. This paper addresses the issue of day-to-day variability in activity-travel behavior. The study, which is the first of its kind in China, applies a unique combination of methods to analyze the degree of dissimilarity between travel days using multi-day GPS data. First, multi-dimensional sequence alignment is applied to measure the degree of dissimilarity in individual daily activity-travel sequences between pairs of travel days. Next, a series of panel effects regression models is used to estimate the effects of socio-demographics and days of the week. The models are estimated using multi-day activity-travel patterns imputed from GPS-enabled smartphone data collected in Shanghai, China. Results indicate that (1) days of the week have significant effects on day-to-day variability in activity-travel behavior with weekday activity-travel sequences being more similar and thereby different from weekend sequences; (2) the degree of dissimilarity in activity-travel sequences is strongly influenced by respondent socio-demographic profiles; (3) individuals having more control over and flexibility in their work schedule show greater intra-personal variability. Day-to-day variability in activity-travel behavior of this sample is similar to patterns observed in developed countries in some aspects but different in others. Strict international comparison study based on comparative data collection is required to further distinguish the sources of travel behavior differences between developing countries and developed countries. The paper ends with a discussion of the limitations of this study and the implications of the research findings for future research.     

Provision of accessible transportation alternatives for the transportation handicapped in Taiwan

Four transportation handicapped groups are identified in Taiwan (impaired ambulation, visually impaired, aged, and others) and nine accessible transportation alternatives are proposed. The costs and potential ridership for these nine alternatives in the Taipei area are estimated. Using analytic hierarchy process (AHP) and multicriteria evaluation with qualitative and quantitative data (MEQQD) methods, the most appropriate accessible transportation alternatives for each of the four handicap groups are selected. It is found that the best accessible transportation alternative for the impaired ambulation, the aged, and others would be a demand-responsive lift-equipped specialized van, while half-fare subsidized taxi would be the second-best option. By contrast, the best alternative for the visually impaired would be half-fare subsidized taxi, while conventional bus with broadcast equipment would be the second-best choice.     

Modelling the dynamics of bus use in a changing travel environment using panel data

Panel data offers the potential to represent the influence on travel choices of changing circumstances, past history and persistent individual differences (unobserved heterogeneity). A four-wave panel survey collected data on the travel choices of residents before and after the introduction of a new bus rapid transit service. The data shows gradual changes to bus use over the four waves, implying time was required for residents to become aware of the new service and to adapt to it. Ordered response models are estimated for bus use over the survey period. The results show that the influence of level of service (LOS) is underestimated if unobserved heterogeneity is not taken into account. The delayed response to the new service is able to be well represented by including LOS as a lagged variable. Current bus use is found to be conditioned on past bus use, but with additional influence of lagged LOS and unobserved heterogeneity. It is shown how different model specifications generate different evolution patterns with the most realistic predictions arising from a model which takes into account lagged responses to change in LOS and unobserved heterogeneity. The paper demonstrates the feasibility of developing panel data models that can be applied to forecasting the effect of interventions in the travel environment. Longer panels—encompassing periods of both stability and change—are required to support future efforts at modelling travel choice dynamics.     

道路运输企业发展甩挂运输的效益研究

甩挂运输是一种先进的运输组织方式,是提高道路运输效率的重要手段,对于促进节能减排,推动道路运输业的发展具有重要意义。本文针对某一具体甩挂运输企业构建数学模型并从固定成本、变动成本两个方面对其进行经济效益评价,从油耗、二氧化碳排放量和污染物排放量三个方面进行节能减排评价,进而论证得出了甩挂运输具有提高经济效益和节能减排的优势。     

Characteristics analysis for travel behavior of transportation hub passengers using mobile phone data

The travel behavior of passengers from the transportation hub within the city area is critical for travel demand analysis, security monitoring, and supporting traffic facilities designing. However, the traditional methods used to study the travel behavior of the passengers inside the city are time and labor consuming. The records of the cellular communication provide a potential huge data source for this study to follow the movement of passengers. This study focuses on the passengers’ travel behavior of the Hongqiao transportation hub in Shanghai, China, utilizing the mobile phone data. First, a systematic and novel method is presented to extract the trip information from the mobile phone data. Several key travel characteristics of passengers, including passengers traveling inside the city and between cities, are analyzed and compared. The results show that the proposed method is effective to obtain the travel trajectories of mobile phone users. Besides, the travel behavior of incity passengers and external passengers are quite different. Then, the correlation analysis of the passengers’ travel trajectories is provided to research the availability of the comprehensive area. Moreover, the results of the correlation analysis further indicate that the comprehensive area of the Hongqiao hub plays a relatively important role in passengers’ daily travel.

     

钢索输送机的研制

目前应用的缠绕卷筒式架索机体积庞大、笨重，造价昂贵，并存在动力浪费、无效劳动比例大等缺陷。中作提出，解决此问题的关键是不用缠绕卷筒拖动换索系统，并应用自己的一项国家专利《绳缆传动机构》，研制成功了一种功率为30KW的“钢索输送机”，可顺利拖动了钢索长度为15km的换索系统，在“钢索输送”的下方设置一适当长度的滑动钢槽，便可以顺利完成换索作业，并按需要合理处理被更换下来的旧钢索。此种架索机作业速度均匀，运行平稳，安装拆卸、操作方便，造价低廉。     

Exploratory analysis of motorcycle holding time heterogeneity using a split-population duration model

This study integrated the samples taken in 2000 for motorcycle usage and their corresponding records registered in the Taiwan’s Vehicle Registration System to observe the survival process of motorcycle ownership. The specific heterogeneity of censored observations that failed to demonstrate actual ownership status in the registration system was corrected by employing a split-population duration model with a Weibull hazard function. The results indicated that around 11% of all observations would never experience an eventual registration termination and that the hazard rates of terminating motorcycle ownership grew at a slightly increasing rate as the holding time increased. Ways of enhancing the accuracy of the motorcycle registration system and accelerating the elimination mechanisms for old motorcycles should be carefully examined.     

Temporal stability of travelers' activity choice and home-stay duration: Some empirical evidence

This paper explores the temporal stability of activity type-choice models and models of travelers' home-stay duration. To empirically evaluate this stability, a nested logit model of activity-type choice and a proportional hazards model of home-stay duration are estimated using data from two-day travel diaries collected in the fall of 1989 and again, from the same individuals, in the fall of 1990. The results show that the models are not temporally stable over the one year time period separating the two travel-diary samples. A number of possible reasons for this instability are discussed.     

Regulating CO2 emissions of transportation in Europe: A CGE-analysis using market-based instruments

This paper analyzes the use of market-based emission regulation instruments to address the carbon dioxide emissions of transportation. Simulations with a static multi-region computable general equilibrium model show that including transportation into the European emission trading system is superior to a closed emission trading system for transportation or a tax-based approach. Furthermore, we show that exempting transportation from emission regulation is the most favorable approach in terms of welfare. This counterintuitive result is due to a large tax-interaction effect caused by high pre-existing fuel taxes in the transport sector.     

A justice-theoretic approach to the distribution of transportation benefits: Implications for transportation planning practice in the United States

Transportation improvements inevitably lead to an uneven distribution of user benefits, in space and by network type (private and public transport). This paper makes a moral argument for what would be a fair distribution of these benefits. The argument follows Walzer’s “Spheres of Justice” approach to define the benefits of transportation, access, as a sphere deserving a separate, non-market driven, distribution. That distribution, we propose, is one where the maximum gap between the lowest and highest accessibility, both by mode and in space, should be limited, while attempting to maximize average access. We then review transportation planning practice for a priori distributional goals and find little explicit guidance in conventional and even justice-oriented transportation planning and analyses. We end with a discussion of the implications for practice.     

Toward criteria in the development of urban transportation systems

Improved criteria are necessary to aid in determining awards of federal funds for metropolitan transit projects. Commuting is the main use for public transit. Thus a primary objective of an urban transit system should be to provide a flexible and balanced set of options to the workers in the metropolitan area for their journey to work. This paper discusses various facets of an appropriate balance among the three modes: rapid rail, bus, and automobile. Three cities are selected for further analysis: Baltimore, Kansas City, and Phoenix. These cities represent different stages in economic-transportation development, and also present different spatial patterns of residence and employment. The applicability of rapid rail transit to each city is examined in view of central city worker concentration and recent trends.