The use of space–time constraints for the selection of discretionary activity locations

Justen, Andreas; Martínez, Francisco; Cortés, Cristián E.

doi:10.1016/j.jtrangeo.2013.10.009

Cited by 22 publications

(16 citation statements)

References 12 publications

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“…Commuting efficiency in Beijing appears to be lower than in Western countries, and few residents appear to take routes that are the same as the shortest routes (Papinski and Scott, 2013). For those who do not perform any non-work activities during their commutes (meaning that they take unnecessary detours), the average commuting distance is longer and RDI is lower -perhaps because people with longer commuting distances prefer to go directly home (Justen et al, 2013). The lower RDI values for commuting without stops indicate that commuting efficiency is related to the number of stops made during commuting and that individuals prefer to make fewer unnecessary detours than necessary detours.…”

Section: Analytical Strategy and Modellingmentioning

confidence: 98%

“…Trip-chaining significantly impacts commuters' travel times and route choices (McGuckin et al, 2005). Individuals who make stops along their commuting trips live farther from work and travel longer distances than those who do not make such stops (Justen et al, 2013;McGuckin et al, 2005). Commuting flexibility is a concept first introduced by De Palma and Lindsey's (2002) comparison of morning and evening commuters.…”

Section: First Introduced Bymentioning

confidence: 99%

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Built environment, peak hours and route choice efficiency: An investigation of commuting efficiency using GPS data

Ying

Chai

2016

Journal of Transport Geography

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Commuting efficiency measures the impact of commuting on urban spatial and social environments. Urban policies aim to reduce commuting distances and improve commuting efficiency by supporting mixed land-use and job-housing balance. Many studies have addressed these issues by examining excess commuting at the aggregate level, and most aggregated measurements of excess commuting are based on home-to-work commuting flows between zones. However, residents' travel behaviour does not consist solely of rational attempts at minimizing commuting distances but is instead affected by commuting hours, the complexity of the commuting chain and the built environment. Thus, commuting efficiency must be studied at the individual or disaggregated levels. This paper examined individual commuting efficiency in suburban Beijing using a GPS-facilitated activity-travel survey and investigated the differences in commuting distance and route choice efficiency between morning and evening peaks. Notably, in so doing, we considered non-work stops, and also explored the impact of urban spatial factors-in both residential and working areas-on commuting efficiency using multilevel mixed effects generalized linear models. The findings suggest that there are significant differences in commuting distance and commuting efficiency between morning and evening peaks based on the nature of commutes. Residents working in city centres or with jobs near railway stations, with higher road network densities or with lower facility densities seem to be more adept at selecting optimal routes.

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Section: Analytical Strategy and Modellingmentioning

confidence: 98%

Section: First Introduced Bymentioning

confidence: 99%

Built environment, peak hours and route choice efficiency: An investigation of commuting efficiency using GPS data

Ying

Chai

2016

Journal of Transport Geography

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“…The distance travelled by an individual in his everyday mobility shall be the product of overlapping the potential of his built environment with his available space-time prism. The result is his activity space, usually, referred to as potential path area (Justen et al, 2013), a concept created by Horton and Reynolds (1971) to define the geographical area containing all the urban locations with which the individual has direct contact, as the result of day-to-day activities (Manaugh and El-Geneidy, 2012).…”

Section: Determinants Of Distance Travelled: Socioeconomics Access Tmentioning

confidence: 99%

Walking short distances. The socioeconomic drivers for the use of proximity in everyday mobility in Barcelona

Marquet

Miralles‐Guasch

2014

Transportation Research Part A: Policy and Practice

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“…Patterns of streets and roads are particularly important, allowing residents to navigate the different functional components of a city. Different street structures result in varying levels of efficiency, accessibility, and usage of transportation infrastructure [11][12][13][14][15][16][17]; consequently structural characteristics of roads have been of great interest in the literature [18][19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

From the betweenness centrality in street networks to structural invariants in random planar graphs

et al. 2018

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The betweenness centrality, a path-based global measure of flow, is a static predictor of congestion and load on networks. Here we demonstrate that its statistical distribution is invariant for planar networks, that are used to model many infrastructural and biological systems. Empirical analysis of street networks from 97 cities worldwide, along with simulations of random planar graph models, indicates the observed invariance to be a consequence of a bimodal regime consisting of an underlying tree structure for high betweenness nodes, and a low betweenness regime corresponding to loops providing local path alternatives. Furthermore, the high betweenness nodes display a non-trivial spatial clustering with increasing spatial correlation as a function of the edge-density. Our results suggest that the spatial distribution of betweenness is a more accurate discriminator than its statistics for comparing static congestion patterns and its evolution across cities as demonstrated by analyzing 200 years of street data for Paris.

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The use of space–time constraints for the selection of discretionary activity locations

Cited by 22 publications

References 12 publications

Built environment, peak hours and route choice efficiency: An investigation of commuting efficiency using GPS data

Built environment, peak hours and route choice efficiency: An investigation of commuting efficiency using GPS data

Walking short distances. The socioeconomic drivers for the use of proximity in everyday mobility in Barcelona

From the betweenness centrality in street networks to structural invariants in random planar graphs

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