[HTML][HTML] Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review

Y Ali, F Hussain, MM Haque - Accident Analysis & Prevention, 2024 - Elsevier
Accurately modelling crashes, and predicting crash occurrence and associated severities
are a prerequisite for devising countermeasures and develo** effective road safety …

Recent advances in traffic accident analysis and prediction: a comprehensive review of machine learning techniques

N Behboudi, S Moosavi, R Ramnath - arxiv preprint arxiv:2406.13968, 2024 - arxiv.org
Traffic accidents pose a severe global public health issue, leading to 1.19 million fatalities
annually, with the greatest impact on individuals aged 5 to 29 years old. This paper …

Transformer-based modeling of abnormal driving events for freeway crash risk evaluation

L Han, R Yu, C Wang, M Abdel-Aty - Transportation Research Part C …, 2024 - Elsevier
A crash risk evaluation model aims to estimate crash occurrence possibility by establishing
the relationships between traffic flow status and crash occurrence. Based upon which …

Post-pandemic shared mobility and active travel in Alabama: A machine learning analysis of COVID-19 survey data

N Xu, Q Nie, J Liu, S Jones - Travel behaviour and society, 2023 - Elsevier
The COVID-19 pandemic has had unprecedented impacts on the way we get around, which
has increased the need for physical and social distancing while traveling. Shared mobility …

Are first responders prepared for electric vehicle fires? A national survey

J Liu, N Xu, Y Shi, T Barnett, S Jones - Accident Analysis & Prevention, 2023 - Elsevier
Transitioning to electric vehicles (EVs) will create both opportunities and challenges.
Although some programs and resources related to EVs have been made available to first …

Linking short-and long-term impacts of the COVID-19 pandemic on travel behavior and travel preferences in Alabama: A machine learning-supported path analysis

N Xu, Q Nie, J Liu, S Jones - Transport policy, 2024 - Elsevier
This study examines the impacts of the COVID-19 pandemic on short-term travel behavior
and long-term travel preferences among residents of Alabama, using survey data. The study …

Exploring spatial heterogeneity in factors associated with injury severity in speeding-related crashes: An integrated machine learning and spatial modeling approach

Z Zhang, N Xu, J Liu, S Jones - Accident Analysis & Prevention, 2024 - Elsevier
Speeding, a risky act of driving a vehicle at a speed exceeding the posted limit, has
consistently emerged as a leading contributor to traffic fatalities. Identifying the risk factors …

[HTML][HTML] Enhancing autonomous vehicle hyperawareness in busy traffic environments: A machine learning approach

AR Alozi, M Hussein - Accident Analysis & Prevention, 2024 - Elsevier
As autonomous vehicles (AVs) advance from theory into practice, their safety and
operational impacts are being more closely studied. This study aims to contribute to the ever …

LSTM Transformer Real-Time Crash Risk Evaluation Using Traffic Flow and Risky Driving Behavior Data

L Han, M Abdel-Aty, R Yu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Crash risk evaluation studies mainly established the relationship between the macro traffic
status and crashes. However, the impact of risky driving behavior, a significant factor in …

[HTML][HTML] Transportation carbon reduction technologies: A review of fundamentals, application, and performance

X Wang, X Dong, Z Zhang, Y Wang - Journal of Traffic and Transportation …, 2024 - Elsevier
Transportation is one of the main sources of carbon emissions that cause climate change.
The reduction of traffic carbon emissions is urgently needed. With advancements in …