Bahar Dadashova

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Texas A&M University Transportation Institute

United States

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Quantifying the benefits and harms of connected and automated vehicle technologies to public health and equity

Open Date: 2019-06-15

Close Date: 2022-01-14

Articles (13)

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Collaborators (4)

xinyue ye

Professor

Texas A&M University

UNITED STATES

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Xiao Li

University of Oxford

UNITED KINGDOM

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Dominique Lord

Professor of Civil Engineering

Texas A&M University

UNITED STATES

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Subasish Das

Texas A&M University Transportation Institute

UNITED STATES

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Bahar Dadashova

Research Interests

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Recent Grants

Articles (13)

Clustering patterns of roadway departure related motorcycle crashes using dimension reduction analysis

Understanding patterns of factor influences in motorcycle crashes with fixed objects

Equity in non-motorist safety: Exploring two pathways in Houston

Diagnosis of Encroachment-Related Work-Zone Crashes by Applying Pattern Recognition

Investigation on the driver-victim pairs in pedestrian and bicyclist crashes by latent class clustering and random forest algorithm

Urban infrastructure audit: an effective protocol to digitize signalized intersections by mining street view images

Hot-spot analysis of motorcyclist crashes involving fixed objects using multinomial logit and data mining tools

Identifying Patterns of Key Factors in Sun Glare-Related Traffic Crashes

Mining patterns of autonomous vehicle crashes involving vulnerable road users to understand the associated factors

Investigating the safety and operational benefits of mixed traffic environments with different automated vehicle market penetration rates in the proximity of a driveway on an urban arterial

Toward a crowdsourcing solution to identify high-risk highway segments through mining driving jerks

Quantifying the health and health equity impacts of autonomous vehicles: A conceptual framework and literature review

Review of contextual elements affecting bicyclist safety

Collaborators (4)

xinyue ye

Xiao Li

Dominique Lord

Subasish Das

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