Joint modelling of propensity and distance for walking-trip generation

Habib, Khandker Nurul; Xiao, Han; Lin, William Haoyang

doi:10.1080/23249935.2013.778356

Cited by 14 publications

(9 citation statements)

References 20 publications

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“…For example, Greenwald and Boarnet (2001) found that transit-oriented land use had a positive effect, at the neighborhood level, on nonwork walk trip generation. Habib et al (2014) presented investigations into walk trip generation based on a large-scale household travel survey. They showed that population density and socio-economic attributes were significant determinants of walk trip generation in an urban region in Canada.…”

Section: Walkability and Walk Trip Generationmentioning

confidence: 99%

“…This outcome may be because perceiving the environment as walkable is not a sufficient condition for walking behavior. According to a conceptual framework integrating neighborhood environment into walk trip generation models (Tian & Ewing, 2017), accurately accounting for walking behavior may also entail land use (e.g., population density and jobpopulation balance) and household and individual socio-demographics (e.g., household size, children number, employment, driving license possession, and income) (Habib et al, 2014;Olojede et al, 2017;Tian & Ewing, 2017). Unfortunately, little empirical research has completely integrated those factors because of difficulty in identifying objective neighborhood environments varying across individuals in different neighborhoods or even in the same one for large-scale quantitative individual-level data collection.…”

Section: 2mentioning

confidence: 99%

“…However, it is impracticable for constructing individual models to collect the actual "objective street quality attributes" of all individuals who have different daily activity areas, even living in the same neighborhood. Thus, most walk trip generation models only incorporated the macro environment such as zonal population and employment density (Habib, Han, & Lin, 2014) or average objective street quality attributes in the road-network area, which is, however, inconsistent with individual actual daily activity areas (Tian & Ewing, 2017). To bridge the gap, perceived environment walkability (PEW), which plays a mediator between individual objective environment and walking generation (Ewing & Handy, 2009) as psychological reactions to the environment, could be substituted for objective environment walkability, despite that researchers do not capture the objective environment areas.…”

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confidence: 99%

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Association of perceived environment walkability with purposive and discursive walking for urban design strategies

Hsieh

Chuang²

2021

JTLU

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The relationship between the built environment and walking behavior has been explored extensively. However, little research has been done to either differentiate between walking for transport and walking as activity or that applies urban design tools to walkability improvement based on environment-walking associations. Therefore, this study constructed perceived environment walkability factors to replace unidentified physical environments that varied among individuals and examined their associations with walking to a destination (purposive walking) and walking as activity (discursive walking), using factor analysis and structural equation modeling. Results suggest that residential density, land-use mix diversity, and pedestrian/traffic safety were associated with purposive walking while aesthetics and crime safety were associated with discursive walking. Land-use mix access and street connectivity were common correlates of both walking patterns. This study also explored how to apply urban design tools, including land-use plans, zoning control, and urban design guidelines, to shape a walkable environment based on the environment-walking associations.

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Section: Walkability and Walk Trip Generationmentioning

confidence: 99%

Section: 2mentioning

confidence: 99%

mentioning

confidence: 99%

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Association of perceived environment walkability with purposive and discursive walking for urban design strategies

Hsieh

Chuang²

2021

JTLU

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“…There has been a great deal of research which has considered the relation between how far people cycle and their travel choices (Dill & Carr, 2003;Ehrgott, Wang, Raith, & van Houtte, 2012;Garc ıa-Palomares, Guti errez, & Latorre, 2012;Habib, Han, & Lin, 2014;Landis, Vattikuti, & Brannick, 1997;Larsen, Patterson, & El-Geneidy, 2013;Parkin, 2004;Parkin, Wardman, & Page, 2007;Pooley, 2013;Rybarczyk & Wu, 2010;Smith & Kauermann, 2011;Stinson & Bhat, 2004;Wadud, 2014). In these works, physical capability may be assumed to have been an implicit constraint in the making of choices, but was not considered explicitly.…”

Section: Literature Informing Construction Of the Ipc Modelmentioning

confidence: 99%

Estimating individual physical capability (IPC) to make journeys by bicycle

Philips

Watling

Timms

2018

International Journal of Sustainable Transportation

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We propose a novel method to estimate capability to make bicycle journeys, specifically considering the individual physical capability (IPC) of entire populations of individuals from all population segments of an area, not just current cyclists. IPC considers the physical constraints on the maximum distance people could cycle given the typical topography of where they live (Distance IPC), and then estimates their ability to make a particular journey (Journey IPC). IPC, when estimated in this way for a particular point in time, may be informed by antecedent behavioral choices and capabilities, and may be a constraint or enabler of subsequent capabilities, potential adaptations and behavior. The focus of the present paper is on explaining a generic method of estimating Distance IPC and Journey IPC by constructing an individually based spatially fine-grained model. We show how such an individual-level model may be implemented for a population resident in many small spatial zones by use of spatial micro-simulation (population synthesis), to generate the individual attributes required as inputs to the model. We present a case-study for the city of Leeds, UK. We explain the range of data sources used, explore sensitivity of the results to assumptions of the model, and illustrate the ability of the model to simulate the effects of policies. Finally, we identify several possible application areas and opportunities to further develop the model.

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“…Walking behaviour has increasingly been receiving attention in recent studies since walking is not only decreasing the car dependency (Gilderbloom et al 2015), but also yields advantages towards keeping the city sustainable and enhancing the urban inhabitants' physical health (Carlson et al 2015;Kang, 2015). Several recent studies employ simulation approaches and new technologies to understand pedestrian walking behaviour and to capture the pedestrian streams (Gehrke & Clifton 2017;Hussein & Sayed 2017;Yin & Wang 2016;Xie & Wong 2015;Nurul Habib et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Investigating pedestrian walkability using a multitude of Seoul data sources

Lee

Ectors

Bellemans

et al. 2017

Transportmetrica B: Transport Dynamics

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Investigating Pedestrian Walkability using a Multitude of Seoul Data Sources Currently walking is a multidisciplinary and emerging point of attention for urban sustainability and for ensuring the quality of pedestrian environments. In order to understand pedestrian behaviour, walkability researches estimate the factors which affect the level of pedestrian satisfaction. Past studies focused on the relationship between environmental factors and pedestrian behavioural outcomes. In this study, we developed pedestrian satisfaction multinomial logit models using various datasets, examining the relative impact of five differently themed sets of attributes: personal, walk-facilities, land-use, pedestrian volumes, and weather-related variables. The results show that the personal variability attributes were selected as most significant. We investigated effects of personal variability, such as the spatial cognition level and travel purpose, and detailed effects of environmental features. In addition, crowdedness, land-use types, and residential information were investigated. The results from this study offer contributions by providing evidence of the importance of personal and contextual variables in influencing the pedestrian walkability.

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Joint modelling of propensity and distance for walking-trip generation

Cited by 14 publications

References 20 publications

Association of perceived environment walkability with purposive and discursive walking for urban design strategies

Association of perceived environment walkability with purposive and discursive walking for urban design strategies

Estimating individual physical capability (IPC) to make journeys by bicycle

Investigating pedestrian walkability using a multitude of Seoul data sources

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