Uncovering pedestrian midblock crash severity patterns using association rules mining-Reference-Cited by-同舟云学术

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Uncovering pedestrian midblock crash severity patterns using association rules mining

Published:2024-07-18 Issue: Volume: Page:1-48
ISSN:2324-9935
Container-title:Transportmetrica A: Transport Science
language:en
Short-container-title:Transportmetrica A: Transport Science

Author:

Chakraborty Rohit¹^ORCID,Das Subasish²^ORCID,Khan Md Nasim³^ORCID

Affiliation:

1. Graduate Student, Texas State University, 601 University Drive, San Marcos, TX, USA

2. Assistant Professor, Civil Engineering, Texas State University, 601 University Drive, San Marcos, TX, USA

3. Sr Engineer I, Transportation Planning West, Austin, TX, USA

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/23249935.2024.2379948

Reference48 articles.

1. Abdullah M. T. Oguchi and C. Dias. 2019. Self-Reported Pedestrian Mid-Block Crossing Behavior: Effects of Gender Age and Region. p. 15p.

2. Mining association rules between sets of items in large databases

3. The implications of situation and route familiarity for driver-pedestrian interaction at uncontrolled mid-block crosswalks

4. Evaluation of driver performance with a prototype cyber physical mid-block crossing advanced warning system

5. Evaluation of pedestrian safety margin at mid-block crosswalks in India

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