Structural Analysis of How Urban Form Impacts Travel Demand: Evidence from Taipei

Abstract

This study empirically examines the connections between urban form and travel demand at the aggregate level using traffic analysis zone data from Taipei, Taiwan, for the year 2000. Nine latent variables and 26 observed variables were analysed using structural equation modelling. By clarifying the direct and indirect effects, the empirical evidence indicates that density is positively related to trip generation and negatively associated with private mode split; mixed land use reduces trip generation and indirectly increases private mode split and a pedestrian-friendly built environment significantly reduces private mode split. Empirical evidence indicates that land use density, diversity and design affect travel demand in urban areas both directly and indirectly.

Accessibility in Cities: Transport and Urban Form

“…In addition, strong evidence exists regarding the positive impact of more compact, mixed-use cities on physical activity levels (Saelens, Sallis et al 2003;Heath, Brownson et al 2006;Sallis, Saelens et al 2009). Higher density urban neighbourhoods and fine-grain street design are related and important predictors for the use of active travel modes such as walking and cycling (Zhang 2004;Khattak and Rodriguez 2005;Cervero, Sarmiento et al 2009;Lin and Yang 2009;Lotfi and Koohsari 2011), with a recent study of US cities estimating the elasticity between walking and land-use mix alone at between 0.15 and 0.25 (Ewing and Cervero 2010).…”

Low-Carbon Transportation Oriented Urban Spatial Structure: Theory, Model and Case Study

“…Although fiercely debated, a large body of literature suggests there is a relationship between urban density and vehicle travel behaviour [46][47][48], and there is a significant negative statistical correlation between urban density and transport-related energy consumption per capita. These findings indicate that increasing the density of cities will reduce the energy consumed and CO 2 emissions produced by transportation.…”

Agent-based modelling of the spatial pattern of leisure visitation in forests: A case study in Wallonia, south Belgium

“…Most existing empirical studies on the distance travelled for green space recreation consider factors operating at the individual level about visitors' profile and travel behaviour (Mercado and P aez, 2009;Barbieri and Sotomayor, 2013), or higher levels such as residential sociodemographics (Lin and Yang, 2009) or destination land use attributes (Nicolau and M as, 2006;Barbieri and Sotomayor, 2013). However, the integration of these multi-level drivers in the spatial modelling of forest visits has been quite limited, probably due to either different research objectives or difficulties in acquiring visitor-level data.…”