Dominique Lord

Professor of Civil Engineering

Texas A&M University

United States

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Dominique Lord is a Professor of Civil Engineering at Texas A&M University, United States. His research primarily focuses on traffic safety, including the analysis of crash risk factors and the impact of environmental conditions on vehicle collisions. Recent publications investigate various aspects of traffic safety, such as driver distraction, wildlife-vehicle collisions, and the role of automated vehicles in mixed traffic environments.

Articles (13)

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2025

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2024

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2023

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2022

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2021

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2021

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2021

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2021

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2021

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2021

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2021

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2020

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2020

Collaborators (3)

Xiaoyu Guo

Texas A&M University Transportation Institute

UNITED STATES

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Bahar Dadashova

Texas A&M University Transportation Institute

UNITED STATES

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JOSE MANUEL MIRA MCWILLIAMS

Universidad Politécnica de Madrid

SPAIN

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Dominique Lord

Research Interests

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Articles (13)

Leveraging Textual Description and Structured Data for Estimating Crash Risks of Traffic Violation: A Multimodal Learning Approach

Does wildlife-vehicle collision frequency increase on full moon nights? A case-crossover analysis

Local Spatial Analysis of the Crash Frequency of Food Delivery Motorcyclists vs. Nondelivery Motorcyclists in relation to Points of Interest

The impact of the great recession on the spatial patterns of traffic fatalities in Texas: a spatial point pattern test

Examining driver distraction in the context of driving speed: An observational study using disruptive technology and naturalistic data

A visual approach for defining the spatial relationships among crashes, crimes, and alcohol retailers: Applying the color mixing theorem to define the colocation pattern of multiple variables

Application of different negative binomial parameterizations to develop safety performance functions for non-federal aid system roads

Comparison of confidence and prediction intervals for different mixed-Poisson regression models

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

Quantifying the automated vehicle safety performance: A scoping review of the literature, evaluation of methods, and directions for future research

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

A simulation analysis to study the temporal and spatial aggregations of safety datasets with excess zero observations

Analysis of crash injury severity on two trans-European transport network corridors in Spain using discrete-choice models and random forests

Collaborators (3)

Xiaoyu Guo

Bahar Dadashova

JOSE MANUEL MIRA MCWILLIAMS

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