Likelihood Parameterization of Bicycle Crash Injury Severities

Journal of Transportation Technologies

ISSN Print: 2160-0473
ISSN Online: 2160-0481
www.scirp.net/journal/jtts
E-mail: [email protected]

Citations

"Likelihood Parameterization of Bicycle Crash Injury Severities"
written by Deo Chimba, Daniel Emaasit, Boniphace Kutela,
published by Journal of Transportation Technologies, Vol.2 No.3, 2012

has been cited by the following article(s):

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[2]	Exploring the need to model severity of single-and multi-occupant vehicles crashes separately: A case of crashes at highway-rail grade crossings
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[3]	Factors impacting bike crash severity in urban areas
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[4]	Analysis of residents' stated preferences of shared micro-mobility devices using regression-text mining approach
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[5]	Exploring pre-crash gate violations behaviors of drivers at highway-rail grade crossings using a mixed multinomial logit model
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[6]	Assessment of Methodological Alternatives for Modeling the Spatiotemporal Crossing Compliance of Pedestrians at Signalized Midblock Crosswalks
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[7]	Spatial characteristics of bicycle–motor vehicle crashes in Christchurch, New Zealand: A case-control approach
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[8]	Towards an understanding of the factors associated with severe injuries to cyclists in crashes with motor vehicles
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[9]	Spatial characteristics of bicycle–motor vehicle crashes in Christchurch, New Zealand
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[10]	Investigating characteristics in a spatial context that contribute to where bicycle accidents occur
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[11]	Advances in Transportation Studies
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[12]	Examining in-vehicle distraction sources in relation to crashes using a Bayesian Multinomial Logit model

[1]	Cyclist-Involved Crashes and Level of Traffic Stress: Evidence from Arizona Transportation Research Record: Journal of the Transportation Research Board, 2025 DOI:10.1177/03611981251322611

[2]	Exploring pre-crash gate violations behaviors of drivers at highway-rail grade crossings using a mixed multinomial logit model International Journal of Injury Control and Safety Promotion, 2022 DOI:10.1080/17457300.2021.1990348

[3]	Analysis of residents’ stated preferences of shared micro-mobility devices using regression-text mining approach Transportation Planning and Technology, 2022 DOI:10.1080/03081060.2022.2089145

[4]	Factors impacting bike crash severity in urban areas Journal of Safety Research, 2022 DOI:10.1016/j.jsr.2022.08.010

[5]	Assessment of Methodological Alternatives for Modeling the Spatiotemporal Crossing Compliance of Pedestrians at Signalized Midblock Crosswalks Journal of Transportation Engineering, Part A: Systems, 2020 DOI:10.1061/JTEPBS.0000300

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