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[HTML][HTML] Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review
Accurately modelling crashes, and predicting crash occurrence and associated severities
are a prerequisite for devising countermeasures and develo** effective road safety …
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
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 …
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
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 …
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
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 …
has increased the need for physical and social distancing while traveling. Shared mobility …
Are first responders prepared for electric vehicle fires? A national survey
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 …
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
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 …
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
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 …
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
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 …
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
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 …
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 …
The reduction of traffic carbon emissions is urgently needed. With advancements in …