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Title:

Investigating the Impacts of Land-Use Patterns on Traffic Safety at Traffic Analysis Zone Level

Accession Number:

01663024

Record Type:

Component

Abstract:

This study aimed to investigate how land-use pattern affects the crash frequency at the traffic analysis zone (TAZ) level. Traffic, road network, land use, population and crash data were collected from Los Angeles County, California in 2014. K-means clustering analysis was first conducted to divide land use at each TAZ into five different patterns. Geographically weighted Poisson regression (GWPR) models were then developed to investigate the associations between crash counts and land use patterns. Traffic flow, road and demographic characteristics were compared across the five land-use patterns to identify the underlying phenomena that made certain land-use patterns more hazardous than others. Separate GWPR models were further developed for each land-use pattern to identify how traffic, road network and demographic characteristics affect crash frequencies in different land-use patterns. The results of this study indicated that land-use combinations at TAZs can be divided into different patterns using land-use mix and proportions of different land-use types, and that each land-use combination can be assigned with a certain safety level. The effects of contributing factors on crash frequency are different across different land-use patterns. The Bayesian discriminant analysis was finally conducted to identify land-use patterns given land-use data at TAZ level. Cross-validation results indicated that the developed method can accurately identify land-use patterns.

Supplemental Notes:

This paper was sponsored by TRB committee ANB20 Standing Committee on Safety Data, Analysis and Evaluation.

Report/Paper Numbers:

18-04562

Language:

English

Authors:

Xu, Chengcheng
Ding, Wei
Liu, Pan
Zhu, Yiran

Pagination:

7p

Publication Date:

2018

Conference:

Transportation Research Board 97th Annual Meeting

Location: Washington DC, United States
Date: 2018-1-7 to 2018-1-11
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References (21) ; Tables

Subject Areas:

Data and Information Technology; Highways; Safety and Human Factors

Source Data:

Transportation Research Board Annual Meeting 2018 Paper #18-04562

Files:

TRIS, TRB, ATRI

Created Date:

Jan 8 2018 11:07AM