A copula-based continuous cross-nested logit model for tour scheduling in activity-based travel demand models

Ghader, Sepehr; Carrión, Carlos; Tang, Liang; Asadabadi, Arash; Zhang, Lei

doi:10.1016/j.trb.2021.01.001

Cited by 15 publications

(7 citation statements)

References 32 publications

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“…In addition, the function representing the TOD should have the same utility at t = 0 and t = 24 , so a cyclic function is needed for interaction. Currently, the commonly used utility functions are in the form of trigonometric functions ( 6 , 7 , 43 , 49 , 51 ):…”

Section: Methodsmentioning

confidence: 99%

“…Ghader et al ( 50 ) proposed the autoregressive continuous logit model, which combines the CL model and the autoregressive process and can accommodate the correlation between alternatives in the continuous spectrum. Ghader et al ( 51 ) introduced a Gaussian copula function based on a CCNL model to describe the correlation between the two dependent alternatives of activity start and end times.…”

Section: Literature Reviewmentioning

confidence: 99%

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Finite-Mixture Continuous Logit Model: Formulation and Application for Shopping Start Time Choice of Non-Commuters

Geng

Zhang³

et al. 2023

Transportation Research Record: Journal of the Transportation R

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As a continuous generalization of the multinomial logit (MNL) model, the continuous logit (CL) model can be used for continuous response variables (e.g., departure time and activity duration). However, the existing CL model requires the calculation of numerical integrals to obtain the choice probabilities; it thus takes a long time to estimate the model parameters, particularly when the sample size is large. In this paper, we formulate the finite-mixture CL (FMCL) model as a new continuous choice model by combining the finite-mixture method and the CL model, in which the continuous distributional function of the finite mixture is embedded in the CL model. As a result, the individual choice probability can be obtained directly by computing the probability density of the continuous distribution function; this avoids calculation of the integral but still obeys the random utility maximization (RUM) principle. Simulation experiments are conducted to demonstrate the capability of the model. In an empirical study, the proposed model is applied for non-commuters’ shopping activity start time using the expectation-maximization (EM) algorithm based on Shanghai Household Travel Survey data. The results show that the FMCL model developed in this paper can greatly reduce the model estimation time (10,048 observations requiring only 3 min) of the CL model, and the model also has a more intuitive interpretation of model coefficients, directly reflecting variable effects on time-of-day choice. These two advantages can greatly enhance the practical value of the proposed modeling method.

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Section: Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Finite-Mixture Continuous Logit Model: Formulation and Application for Shopping Start Time Choice of Non-Commuters

Geng

Zhang³

et al. 2023

Transportation Research Record: Journal of the Transportation R

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show abstract

“…In 1974, UT began to be widely used in transportation, and McFadden [17] proposed the multinomial logit model (MNL), which further refned the theory of random utility maximization (RUM). Subsequently, the form of MNL models has been gradually expanded to more fexible nested logit (NL) models [18], mixed logit (ML) models [19], latent class logit models (LCM) [20], and so on. Currently, UT is often applied to travel route choice behavior in transportation travel behavior.…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling the Traveler’s Route Choice Behavior under Unexpected Accidents

Zhu

Shi

Cui

et al. 2023

Journal of Advanced Transportation

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To investigate the route choice behavior of travelers under unexpected accidents, this study designs four different scenarios of travelers’ route choice behavior experiments according to the severity of unexpected accidents. The bounded rationality characteristics of travelers, such as the time perception difference coefficient, psychological threshold effect coefficient, and scale effect, are introduced into the generalized random regret minimization (GRRM) model. An improved generalized random regret minimization (IGRRM) model is constructed based on travelers’ route choice behavior under unexpected accidents. The collected data of travelers’ route choice results under four different congestion-level scenarios are analyzed by the IGRRM model. The study finds that with the increase in congestion level, travelers are more willing to change the route; during the commute, travelers tend to choose the route with less travel time and angular cost; in the moderate and serious congestion scenarios, travelers no longer reject the detour route; attribute perception difference, scale effect, and psychological threshold effect; affect travelers’ route choice behavior. The IGRRM model based on the route choice behavior of travelers can more accurately characterize the route choice behavior of travelers under unexpected accidents, provide a basis for traffic flow distribution under unexpected accidents, and benefit traffic management departments to take traffic control and guidance measures to ease the traffic congestion caused by unexpected accidents.

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“…Based on the analysis of travel behavior, the logit model is widely used in the field of transportation mode division. Sepehr Ghader [6] introduced a multi-dimensional continuous activity scheduling choice modeling framework and focused on modeling the joint choice of arrival to an activity and departure from the activity. The introduced framework can provide a sufficient tool for the time-of-day component of various travel demand models.…”

Section: Introductionmentioning

confidence: 99%

Study on transportation mode decision of population agglomeration at Shijiazhuang Zhengding International Airport

Dou

2022

Seventh International Conference on Electromechanical Control Technology and Transportation (ICECTT 2022)

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A copula-based continuous cross-nested logit model for tour scheduling in activity-based travel demand models

Cited by 15 publications

References 32 publications

Finite-Mixture Continuous Logit Model: Formulation and Application for Shopping Start Time Choice of Non-Commuters

Finite-Mixture Continuous Logit Model: Formulation and Application for Shopping Start Time Choice of Non-Commuters

Modeling the Traveler’s Route Choice Behavior under Unexpected Accidents

Study on transportation mode decision of population agglomeration at Shijiazhuang Zhengding International Airport

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