Analysis of Traffic Crashes Involving Pedestrians Using Big Data: Investigation of Contributing Factors and Identification of Hotspots

Risk Analysis

Volumn 37, Issue 8, 2017, Pages 1459-1476

  Xie, Kun ^a   Ozbay, Kaan ^a   Kurkcu, Abdullah ^a   Yang, Hong ^b  

^a POLYTECHNIC UNIVERSITY   (United States)

^b Old Dominion University   (United States)

Author keywords

Big data; grid cell analysis; pedestrian risk

Indexed keywords

CELLS; COSTS; CYTOLOGY; FACTOR ANALYSIS; LAND USE; MOTOR TRANSPORTATION; PEDESTRIAN SAFETY; RISK ANALYSIS; RISK ASSESSMENT; RISK PERCEPTION; TAXICABS;

CONTRIBUTING FACTOR; CONVENTIONAL METHODS; GRID CELLS; IDENTIFICATION METHOD; KERNEL DENSITY FUNCTION; PEDESTRIAN CRASHES; SAFETY IMPROVEMENT; TRAFFIC ANALYSIS ZONES;

BIG DATA;

CENSUS; DATA SET; IDENTIFICATION METHOD; MODELING; PEDESTRIAN; RISK ASSESSMENT; ROAD TRAFFIC; TRAFFIC CONGESTION;

KANSAS; MANHATTAN; UNITED STATES;

EID: 85016436528     PISSN: 02724332     EISSN: 15396924     Source Type: Journal    
DOI: 10.1111/risa.12785     Document Type: Article

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