Spatial transferability of travel forecasting models: a review and synthesis

Sikder, Sujan; Pinjari, Abdul Rawoof; Srinivasan, Sivaramakrishnan; Nowrouzian, Roosbeh

doi:10.1007/s12572-013-0090-6

Cited by 40 publications

(35 citation statements)

References 24 publications

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“…However, as discussed by Sikder et al (2013), from a practical point of view, models cannot be completely transferred with the same specification between states or regions. Nevertheless, the proposed methods and overall framework can be transferred with some modifications, and some states or regions may need to use the estimated models of other places because of data limitations.…”

Section: Generalizability and Transferabilitymentioning

confidence: 99%

Bayesian Spatio-Temporal Analysis of Road Traffic Crashes

Azimian¹

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BAYESIAN SPATIO-TEMPORAL ANALYSIS OF ROAD TRAFFIC CRASHES Amin Azimian Road traffic crashes are one of the major causes of death and serious injury in the US, leading to economic losses and human suffering. In recent years, several research efforts have been made to screen areas and locate hotspots/zones and to identify the factors contributing to traffic crashes of different severity levels. Such research typically aggregates crash locations into spatial units at the macro level, such as counties, or at the micro level, such as road segments or intersections. Many crash estimation methods have been proposed in the literature. These methods range from classical approaches, such as the linear, Poisson, negative binomial, and logistic regression methods, to more state-of-the-art approaches, such as the empirical Bayesian (EB), spatial autoregressive, and full Bayesian methods. A considerable drawback of classical methods is that they cannot account for the regression-to-the-mean bias and potential unobserved heterogeneity, which can result in unstable and biased parameter estimates. Additionally, EB and spatial autoregressive methods are unable to address multilevel data and group-level random effects. By contrast, the full Bayesian framework is more flexible and can be easily extended to include random effect terms that can act as proxies for unobserved or missing covariates that have a spatial or temporal structure. Although the full Bayesian framework appears to be a promising methodology for dealing with crash data, the few previous studies in the area of road traffic safety that used this framework had some major limitations. Some studies performed their analyses in DEDICATION This dissertation is lovingly dedicated to my family. Your support and encouragement mean so much to me, and I am forever grateful. Thank you! v ACKNOWLEDGMENTS First, I would like to thank my advisor, Dr. V. Dimitra Pyrialakou. I am deeply honored to be her first Ph.D. student. I appreciate all her contributions in terms of her time, ideas, and efforts to make my Ph.D. experience truly productive and stimulating. The joy and enthusiasm she has for research were contagious and motivational for me, especially during the tough times in my Ph.D. pursuit. I also thank my committee members, namely, Drs. David Martinelli, Kakan Dey, Sijin Wen, Ashish Nimbarte, and Steven Lavrenz, for all their advice and support. Finally, I thank my family for their love, care, and support. Specifically, I express my immense gratitude to my lovely wife, Hanieh, for her patience and unparalleled support. My family is my biggest support system, materially and morally. vi

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Section: Generalizability and Transferabilitymentioning

confidence: 99%

Bayesian Spatio-Temporal Analysis of Road Traffic Crashes

Azimian¹

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“…Those cities are similar in economic development and have well-collected data sources for transport planning purposes. At this phase of studying the transferability of ABM models for HCMC, we do not consider the transferability of design features of the model system that is the modeling components and the structure, linkage and sequence of all component [2]. Because the modeling framework with a daily pattern, tour and stop levels of either econometric or rule-based models have shown a high possibility to be transferred to many geographical regions where data resource is limited.…”

Section: Activity-based Travel Demand Modelsmentioning

confidence: 99%

“…Sikder et. al did an extensive review on the transferability studies of ABMs in literature [2]. The authors also proposed a framework with two levels to assess the spatial transferability of ABMs.…”

Section: Introductionmentioning

confidence: 99%

“…For more general cases, the foremost task is to investigate if the underlying assumptions used in the base model are applicable in different contexts. There is, however, no empirical study on transferring the assumptions on the decision making mechanism [2]. For cross-culture context, Lee et.al [4] summarized several issues including the differences in zoning system, transport system and life-style in a study to transfer FEATHERS [5], an operational ABM model for Flanders [5] (a region in Western country) to Seoul, a region in a developed Asian country.…”

Section: Introductionmentioning

confidence: 99%

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Exploring the Transferability of FEATHERS – An Activity Based Travel Demand Model – For Ho Chi Minh City, Vietnam

Linh¹,

Adnan²,

Ectors³

et al. 2020

(JTTM)

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This paper presents descriptive analyses to investigate the transferability of FEATHERS, an activity-based travel demand model developed for Flanders (Belgium), to a region in a developed country to Ho Chi Minh City (Vietnam), a metropolitan area of a developing country, using personal and household travel survey data. The transferability was tested by using indicators which represent individuals' activity and travel behaviors. The results confirm the transferability of the FEATHERS modelling structure to Ho Chi Minh City (HCMC), yet all sub-models require recalibration due to the different cultural settings between the two study areas. The differences in transport mode options, land use patterns and individuals' location choice preferences make transport mode and location choice the least transferable models.

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“…While it is generally considered good practice to develop models based on locally collected data, there are situations where spatial transfer of models may be of interest. Some regions, particularly small and medium-sized planning organizations, may not have the resources and staff time necessary to undertake large scale survey data collection efforts and thus borrow models from other regions (Sikder et al, 2012). When such model transfer is considered, it is important to ensure that the transferred model offers useful and valid information in the application context (Koppelman and Wilmot, 1982).…”

Section: Introductionmentioning

confidence: 99%

Latent-Segmentation-Based Approach to Investigating Spatial Transferability of Activity-Travel Models

Wafa

Bhat

Pendyala

et al. 2015

Transportation Research Record

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Spatial transferability of travel demand models has been an issue of considerable interest, particularly for small and medium sized planning areas that often do not have the resources and staff time to collect large scale travel survey data and estimate model components native to the region. With the advent of more sophisticated microsimulation-based activity-travel demand models, the interest in spatial transferability has surged in the recent past as smaller metropolitan planning organizations seek to take advantage of emerging modeling methods within the limited resources they can marshal. Traditional approaches to identifying geographical contexts that may borrow and transfer models between one another involve the exogenous a priori identification of a set of variables or criteria that are used to characterize the similarity between geographic regions. However, this ad hoc procedure presents considerable challenges as it is difficult to identify the most appropriate criteria a priori. To address this issue, this paper proposes a latent segmentation approach whereby the most appropriate criteria for identifying areas with similar profiles are determined endogenously within the model estimation phase. In other words, the relationships embedded in the data set help identify the optimal set of criteria that can be used to cluster regions according to their similarity with respect to activity-travel characteristics of interest. The methodology is demonstrated and its efficacy established through a case study in this paper that utilizes the National Household Travel Survey (NHTS) data set. It is found that the methodology offers a robust mechanism for identifying latent segments and establishing criteria for assessing transferability of models between areas.

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Spatial transferability of travel forecasting models: a review and synthesis

Cited by 40 publications

References 24 publications

Bayesian Spatio-Temporal Analysis of Road Traffic Crashes

Bayesian Spatio-Temporal Analysis of Road Traffic Crashes

Exploring the Transferability of FEATHERS – An Activity Based Travel Demand Model – For Ho Chi Minh City, Vietnam

Latent-Segmentation-Based Approach to Investigating Spatial Transferability of Activity-Travel Models

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