Effect of urban street trees on pedestrian safety: A micro-level pedestrian casualty model using multivariate Bayesian spatial approach

Manman Zhu, N. N. Sze, Sharon Newnam

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)

Abstract

In the past decades, trees were considered roadside hazard. Street trees were removed to provide clear zone and improve roadside safety. Nowadays, street trees are considered to play an important role in urban design. Also, street tree is considered a traffic calming measure. Studies have examined the effects of urban street trees on driver perception, driving behaviour, and general road safety. However, it is rare that the relationship between urban street trees and pedestrian safety is investigated. In this study, a micro-level frequency model is established to evaluate the effects of tree density and tree canopy cover on pedestrian injuries, accounting for pedestrian crash exposure based on comprehensive pedestrian count data from a state in Australia, Melbourne. In addition, effects of road geometry, traffic characteristics, and temporal distribution are also considered. Furthermore, effects of spatial dependency and correlation between pedestrian casualty counts of different injury severity levels are accounted using a multivariate Bayesian spatial approach. Results indicate that road width, bus stop, tram station, on-street parking, and 85th percentile speed are positively associated with pedestrian casualty. In contrast, pedestrian casualty decreases when there is a pedestrian crosswalk and increases in tree density and canopy. Also, time variation in pedestrian injury risk is significant. To sum up, urban street trees should have favorable effect on pedestrian safety. Findings are indicative to optimal policy strategies that can enhance the walking environment and overall pedestrian safety. Therefore, sustainable urban and transport development can be promoted.

Original languageEnglish
Article number106818
JournalAccident Analysis and Prevention
Volume176
DOIs
Publication statusPublished - Oct 2022

Keywords

  • Multivariate random parameters model
  • Pedestrian count data
  • Pedestrian exposure
  • Pedestrian injury
  • Street tree
  • Tree canopy

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Safety, Risk, Reliability and Quality
  • Public Health, Environmental and Occupational Health

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