Modeling the Rounding of Departure Times in Travel Surveys: Comparing the Effect of Trip Purposes and Travel Modes

Rounding errors are often observed in reported trip departure and arrival times in paper-based travel surveys, and most of the reported times are multiples of 5, 15, 30, or 60 min. However, the rounding is rarely systematically analyzed. This study aimed to analyze the rounding of reported departure time in paper-based travel surveys by extending the rounding model proposed by Rietveld in 2002. The model parameters were estimated using the maximum likelihood method with constraints. The data in a 2012 household travel survey in Kumamoto, Japan, was used. The data in Japan were found to be often rounded to 10 min, which contrasted with the frequent rounding to 15 min in the Netherlands and United States. The model estimation results indicated that rounding to 5 and 10 min most often occurred. The response-error distribution when the reported departure time was 30 min was demonstrated using the Bayesian theorem and it was shown that the probabilities in which the actual departure times were exactly 30 min, 25–35 min, and 20–40 min were 7.9%, 63.5%, and 84.3%, respectively. Business trips were found to contain large rounding errors, and most public-transportation trips exhibited smaller rounding errors. These results may be used to refine several travel behavioral models in the future.

Download Full-text

Not My Usual Trip: Ride-hailing Characterization in Mexico City

10.18235/0003516 ◽

2021 ◽

Author(s):

Orlando Sabogal-Cardona ◽

Lynn Scholl ◽

Daniel Oviedo ◽

Amado Crotte ◽

Felipe Bedoya

Keyword(s):

Mexico City ◽

Public Transportation ◽

Social Issues ◽

Cultural Challenges ◽

Large Cities ◽

Household Travel Survey ◽

Transport Services ◽

Developing Cities ◽

Categorical Models ◽

Household Travel

With a few exceptions, research on ride-hailing has focused on North American cities. Previous studies have identified the characteristics and preferences of ride-hailing adopters in a handful of cities. However, given their marked geographical focus, the relevance and applicability of such work to the practice of transport planning and regulation in cities in the Global South is minimal. In developing cities, the entrance of new transport services follows very different trajectories to those in North America and Europe, facing additional social, economic, and cultural challenges, and involving different strategies. Moreover, the determinants of mode choice might be mediated by social issues such as the perception of crime and the risk of sexual harassment in public transportation, which is often experienced by women in large cities such as Mexico. This paper examines ride-hailing in the Metropolitan Area of Mexico City, unpacking the characteristics of its users, the ways they differ from users of other transport modes, and the implications for urban mobility. Building on the household travel survey from 2017, our analytical approach is based on a set of categorical models. Findings suggest that gender, age, education, and being more mobile are determinants of ride-hailing adoption. The analysis shows that ride-hailing is used for occasional trips, and it is usually done for leisure and health trips as well as for night trips. The study also reflects on ride-hailings implications for the way women access the city.

Download Full-text

The role of peer effects and the built environment on individual travel behavior

Environment and Planning B Urban Analytics and City Science ◽

10.1177/2399808317740354 ◽

2017 ◽

Vol 45 (3) ◽

pp. 452-469 ◽

Cited By ~ 6

Author(s):

Changjoo Kim ◽

Olivier Parent ◽

Rainer vom Hofe

Keyword(s):

Built Environment ◽

Travel Behavior ◽

Social Influences ◽

Strong Impact ◽

Behavioral Models ◽

Model Framework ◽

Household Travel Survey ◽

Transport Modes ◽

Household Travel

While urban planners and transportation geographers have long emphasized the importance of social influences on individual travel behavior, many challenges remain to bridge the gap between complex conceptual frameworks and operational behavioral models. Improving the ability of models to forecast activity-travel behavior can provide greater insights into urban planning issues. This paper proposes a new model framework by evaluating how individual travel behavior is influenced by inter- and intra-household interactions. The built environment, land-use mix, and social interactions influence household member choices among different transport modes. We propose a spatial multivariate Tobit specification that allows each individual to face a set of potential destinations and transport modes and takes into consideration the travel behavior of other household members and nearby neighbors. Using the Greater Cincinnati Household Travel Survey, we analyzed more than 37,000 trips made by 1968 individuals located in Hamilton County in Cincinnati, Ohio. Results reveal that social influences and the built environment have a strong impact on the willingness to walk and to cycle.

Download Full-text

Effects of covariates on alternating recurrent events in accelerated failure time models

The International Journal of Biostatistics ◽

10.1515/ijb-2019-0099 ◽

2020 ◽

Vol 0 (0) ◽

Author(s):

Moumita Chatterjee ◽

Sugata Sen Roy

Keyword(s):

Recurrent Events ◽

Failure Time ◽

Likelihood Method ◽

Model Parameters ◽

Accelerated Failure Time ◽

Survival Times ◽

Copula Functions ◽

Event Time ◽

Accelerated Failure Time Models ◽

Accelerated Failure

AbstractIn this article, we model alternately occurring recurrent events and study the effects of covariates on each of the survival times. This is done through the accelerated failure time models, where we use lagged event times to capture the dependence over both the cycles and the two events. However, since the errors of the two regression models are likely to be correlated, we assume a bivariate error distribution. Since most event time distributions do not readily extend to bivariate forms, we take recourse to copula functions to build up the bivariate distributions from the marginals. The model parameters are then estimated using the maximum likelihood method and the properties of the estimators studied. A data on respiratory disease is used to illustrate the technique. A simulation study is also conducted to check for consistency.

Download Full-text

Theory and Applications of the Unit Gamma/Gompertz Distribution

Mathematics ◽

10.3390/math9161850 ◽

2021 ◽

Vol 9 (16) ◽

pp. 1850

Author(s):

Rashad A. R. Bantan ◽

Farrukh Jamal ◽

Christophe Chesneau ◽

Mohammed Elgarhy

Keyword(s):

Stochastic Ordering ◽

Real Data ◽

Rate Function ◽

The Other ◽

Likelihood Method ◽

Model Parameters ◽

Data Sets ◽

Gompertz Distribution ◽

Probability And Statistics ◽

Analytical Behavior

Unit distributions are commonly used in probability and statistics to describe useful quantities with values between 0 and 1, such as proportions, probabilities, and percentages. Some unit distributions are defined in a natural analytical manner, and the others are derived through the transformation of an existing distribution defined in a greater domain. In this article, we introduce the unit gamma/Gompertz distribution, founded on the inverse-exponential scheme and the gamma/Gompertz distribution. The gamma/Gompertz distribution is known to be a very flexible three-parameter lifetime distribution, and we aim to transpose this flexibility to the unit interval. First, we check this aspect with the analytical behavior of the primary functions. It is shown that the probability density function can be increasing, decreasing, “increasing-decreasing” and “decreasing-increasing”, with pliant asymmetric properties. On the other hand, the hazard rate function has monotonically increasing, decreasing, or constant shapes. We complete the theoretical part with some propositions on stochastic ordering, moments, quantiles, and the reliability coefficient. Practically, to estimate the model parameters from unit data, the maximum likelihood method is used. We present some simulation results to evaluate this method. Two applications using real data sets, one on trade shares and the other on flood levels, demonstrate the importance of the new model when compared to other unit models.

Download Full-text

Accessibility and Intraurban Travel

Environment and Planning A Economy and Space ◽

10.1068/a190735 ◽

1987 ◽

Vol 19 (6) ◽

pp. 735-748 ◽

Cited By ~ 118

Author(s):

S Hanson ◽

M Schwab

Keyword(s):

Travel Behavior ◽

Activity Spaces ◽

Household Travel Survey ◽

Trip Frequency ◽

Potential Activity ◽

Using Data ◽

Household Travel ◽

Automobile Use ◽

The Relationship ◽

Travel Distances

This paper contains an examination of the fundamental assumption underlying the use of accessibility indicators: that an individual's travel behavior is related to his or her location vis-à-vis the distribution of potential activity sites. First, the conceptual and measurement issues surrounding accessibility and its relationship to travel are reviewed; then, an access measure for individuals is formulated. Using data from the Uppsala (Sweden) Household Travel Survey and controlling for sex, automobile availability, and employment status, the authors explore the relationship between both home- and work-based accessibility and five aspects of an individual's travel: mode use, trip frequencies and travel distances for discretionary purposes, trip complexity, travel in conjunction with the journey to work, and size of the activity space. From the results it can be seen that although all of these travel characteristics are related to accessibility to some degree, the travel–accessibility relationship is not as strong as deductive formulations have implied. High accessibility levels are associated with higher proportions of travel by nonmotorized means, lower levels of automobile use, reduced travel distances for certain discretionary trip purposes, and smaller individual activity spaces. Furthermore, the density of activity sites around the workplace affects the distances travelled by employed people for discretionary purposes. Overall, accessibility level has a greater impact on mode use and travel distance than it does on discretionary trip frequency. This result was unexpected in light of the strong trip frequency–accessibility relationship posited frequently in the literature.

Download Full-text

Mixture of Inverse Weibull and Lognormal Distributions: Properties, Estimation, and Illustration

Mathematical Problems in Engineering ◽

10.1155/2015/526786 ◽

2015 ◽

Vol 2015 ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

K. S. Sultan ◽

A. S. Al-Moisheer

Keyword(s):

Information Matrix ◽

Real Data ◽

Likelihood Method ◽

Model Parameters ◽

Component Mixture ◽

Data Set ◽

Hazard Functions ◽

Lognormal Distributions ◽

Proposed Model ◽

Estimation Of Model Parameters

We discuss the two-component mixture of the inverse Weibull and lognormal distributions (MIWLND) as a lifetime model. First, we discuss the properties of the proposed model including the reliability and hazard functions. Next, we discuss the estimation of model parameters by using the maximum likelihood method (MLEs). We also derive expressions for the elements of the Fisher information matrix. Next, we demonstrate the usefulness of the proposed model by fitting it to a real data set. Finally, we draw some concluding remarks.

Download Full-text

A new ensemble-based statistical methodology to verify changes in weather and climate models

10.5194/egusphere-egu21-4255 ◽

2021 ◽

Author(s):

Christian Zeman ◽

Christoph Schär

Keyword(s):

Climate Models ◽

Climate Model ◽

Numerical Models ◽

Hypothesis Test ◽

Model Development ◽

Atmospheric Model ◽

Statistical Hypothesis ◽

Model Parameters ◽

Rounding Errors ◽

Weather And Climate

Since their first operational application in the 1950s, atmospheric numerical models have become essential tools in weather and climate prediction. As such, they are a constant subject to changes, thanks to advances in computer systems, numerical methods, and the ever increasing knowledge about the atmosphere of Earth. Many of the changes in today's models relate to seemingly unsuspicious modifications, associated with minor code rearrangements, changes in hardware infrastructure, or software upgrades. Such changes are meant to preserve the model formulation, yet the verification of such changes is challenged by the chaotic nature of our atmosphere - any small change, even rounding errors, can have a big impact on individual simulations. Overall this represents a serious challenge to a consistent model development and maintenance framework.Here we propose a new methodology for quantifying and verifying the impacts of minor atmospheric model changes, or its underlying hardware/software system, by using ensemble simulations in combination with a statistical hypothesis test. The methodology can assess effects of model changes on almost any output variable over time, and can also be used with different hypothesis tests.We present first applications of the methodology with the regional weather and climate model COSMO. The changes considered include a major system upgrade of the supercomputer used, the change from double to single precision floating-point representation, changes in the update frequency of the lateral boundary conditions, and tiny changes to selected model parameters. While providing very robust results, the methodology also shows a large sensitivity to more significant model changes, making it a good candidate for an automated tool to guarantee model consistency in the development cycle.

Download Full-text

Does Investing in Rail Transit Benefit the Poor? A Comparative Study of Rail and Bus Travel by Low-Income Households in the California Household Travel Survey

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198118796738 ◽

2018 ◽

Vol 2672 (6) ◽

pp. 11-20

Author(s):

Ryland Lu

Keyword(s):

Low Income ◽

Household Income ◽

Bus Rapid Transit ◽

Rail Transit ◽

Rapid Transit ◽

Travel Survey ◽

Household Travel Survey ◽

The Poor ◽

Household Travel ◽

Low Income Households

This paper addresses academic discourse that critiques urban rail transit projects for their regressive impacts on the poor and proposes bus funding as a more equitable investment for urban transit agencies. The author analyzed data from the 2012 California Household Travel Survey on transit trips in Los Angeles County. The author cross-tabulated data on the modal breakdown of transit trips by household income category and on the breakdown of household income associated with trips by bus and rail transit modes. The author also comparatively evaluated the speed of trips (as a ratio of miles per hour) taken by rail and by bus by low-income households in the county. The author found convincing evidence that, on average, trips low-income households made by rail transit covered a greater distance per hour than trips taken by bus transit, but that trips made on the county’s bus rapid transit services with dedicated rights-of-way had a higher mean speed than those taken by rail. Moreover, the mode and income cross-tabulations indicate that rail transit projects only partially serve low-income households’ travel needs. To the extent that equitable transit planning entails minimizing the disparities in access, both rail and bus rapid transit projects can advance social justice if they are targeted at corridors where they can serve travel demand by low-income, transit dependent households.

Download Full-text

A Study on A New Type 1 Half-Logistic Family of Distributions and Its Applications

Statistics Optimization & Information Computing ◽

10.19139/soic-2310-5070-674 ◽

2020 ◽

Vol 8 (4) ◽

pp. 934-949

Author(s):

Morad Alizadeh ◽

Alireza Nematollahi ◽

Emrah Altun ◽

Mahdi Rasekhi

Keyword(s):

Residual Life ◽

Moment Generating Function ◽

Likelihood Method ◽

Mean Deviation ◽

Model Parameters ◽

Type I ◽

Monte Carlo Simulation Study ◽

New Type ◽

Application Fields ◽

Family Of Distributions

In this paper, we propose a new class of continuous distributions with two extra shape parameters called the a new type I half logistic-G family of distributions. Some of important properties including ordinary moments, quantiles, moment generating function, mean deviation, moment of residual life, moment of reversed residual life, order statistics and extreme value are obtained. To estimate the model parameters, the maximum likelihood method is also applied by means of Monte Carlo simulation study. A new location-scale regression model based on the new type I half logistic-Weibull distribution is then introduced. Applications of the proposed family is demonstrated in many fields such as survival analysis and univariate data fitting. Empirical results show that the proposed models provide better fits than other well-known classes of distributions in many application fields.

Download Full-text

Population changes in rattail species on the Chatham Rise

10.26686/wgtn.17007577 ◽

2021 ◽

Author(s):

◽

Kathleen Large

Keyword(s):

Maximum Likelihood ◽

Stock Assessment ◽

Production Model ◽

Likelihood Method ◽

Model Parameters ◽

Important Species ◽

Surplus Production ◽

Surplus Production Model ◽

Abundance Indices ◽

The Impact

The aim of this project was to conduct a stock assessment to determine the population dynamic characteristics of rattail species taken as bycatch in the hoki, hake and ling fishery on the Chatham Rise. No quantitative assessment of the current size of rattail populations , and how these may have changed over time, has been carried out before. There is interest in the need to quantify the impact of commercial fishing on the rattail populations, as rattails (Macrouridae family) are considered to be an ecologically important species complex in the deep ocean, and there may be the potential for the development of a commercial fishery based on their value as processed fishmeal. The minimum data required for a stock assessment are an abundance index and a catch history. Abundance indices are available for over 20 species of rattail produced from scientific surveys conducted annually on the Chatham Rise since 1992. Catch histories for individual rattail species in the same area are not available. A method was developed to reconstruct commercial catches of rattails from commercial effort data and survey catch and effort data. A surplus production model was fitted to the reconstructed catch data and survey abundance indices, using maximum likelihood and Bayesian methods to estimate model parameters and uncertainty. A surplus production model has two components: an observation model for abundance indices and a process model for population dynamics. Maximum likelihood estimation was applied to a model that specified errors for the observations only, and this produced estimates that had wide confidence intervals. A Bayesian approach was then taken to fit a statespace version of the model that incorporates errors associated with the observation and process models. While the Bayesian method produced more plausible parameter estimates (in comparison to the maximum likelihood method) and parameter uncertainty was reduced, our analysis indicated the posterior estimates were highly sensitive to the specification of different priors. There may be several reasons for these results, including: the small number of observations, lack of contrast in the data and mis-specification of the model. Meaningful estimates of the absolute size of rattail populations are not possible with these results, where estimates can vary by orders of magnitude depending on prior specification. This implies that more work needs to be done to develop more effective methods that can be used to help inform decisions regarding the management of these fish populations. Improving data collection, investigating informative priors and extending/respecifying the model are considered worthwhile avenues of future work to improve stock assessments of rattails.

Download Full-text