Exploring the Effects of Urban Built Environment on Road Travel Speed Variability with a Spatial Panel Data Model

Abstract

Road traffic congestion is a common problem in most large cities, and exploring the root causes is essential to alleviate traffic congestion. Travel behavior is closely related to the built environment, and affects road travel speed. This paper investigated the direct effect of built environment on the average travel speed of road traffic. Taxi trajectories were divided into 30 min time slot (48 time slots throughout the day) and matched to the road network to obtain the average travel speed of road segments. The Points of Interest (POIs) in the buffer zone on both sides of the road segment were used to calculate the built environment indicators corresponding to the road segment, and then a spatial panel data model was proposed to assess the influence of the built environment adjacent to the road segment on the average travel speed of the road segment. The results demonstrated that the bus stop density, healthcare service density, sports and leisure service density, and parking entrance and exit density are the key factors that positively affect the average road travel speed. The residential community density and business building density are the key factors that negatively affect the average travel speed. Built environments have spatial correlation and spatial heterogeneity in their influence on the average travel speed of road segments. Findings of this study may provide useful insights for understanding the correlation between road travel speed and built environment, which would have important implications for urban planning and governance, traffic demand forecasting and traffic system optimization.

The Impact of Road Functions on Road Congestions Based on POI Clustering: An Empirical Analysis in Xi’an, China

“…However, the relationship between the number of road lanes and trafc congestion in realistic environments is more complex, considering various factors such as the saturation [11], the spatial location of roads [13], and the restriction of trafc management measures for roads [14]. In addition, external factors, such as time of day and weather, may also afect the relationship between the number of lanes and trafc congestion [15][16][17][18]. On the other hand, the rank of the road is another criterion for evaluating the road capacity, and there are signifcant diferences in the capacity of the diferent ranks of roads [19].…”

“…Moreover, the spatial location of the road, road network structure, and adjacent road properties such as the rank of the road, the number of road lanes, and the length of the road will signifcantly afect the trafc fow on the road. As a result, the road congestion levels of diferent ranks of roads usually have signifcant distinctions [12,16,17,19]. In addition, microscopic features of roads, such as the duration of road signals [20], the distribution of turn lanes [21], the length of the road [17,22], and the number of public transport facilities on the road [23], are correlated with the trafc congestion [24,25].…”

“…As a result, the road congestion levels of diferent ranks of roads usually have signifcant distinctions [12,16,17,19]. In addition, microscopic features of roads, such as the duration of road signals [20], the distribution of turn lanes [21], the length of the road [17,22], and the number of public transport facilities on the road [23], are correlated with the trafc congestion [24,25].…”

“…Furthermore, commuting time and average delay time has a signifcant negative correlation with the mixing of land use. However, the overcompact urban structure may also induce urban trafc congestion due to the density of travel demand [2,9]; On the other hand, the urban built environment signifcantly impacts the state of urban trafc [17,28].…”

“…Moreover, the urban built environment can impact urban residents' travel behavior [28] and the choice of residents' travel patterns may impact trafc congestion [41]. Furthermore, at the road level, existing studies have discussed that chronically congested roads are usually associated with the number of bus stops and shopping mall density [17]. However, these researches are limited and mainly focus on the built environment on the road.…”