AI Medical Compendium Journal:
Accident; analysis and prevention

Showing 41 to 50 of 137 articles

Analyzing the transition from two-vehicle collisions to chain reaction crashes: A hybrid approach using random parameters logit model, interpretable machine learning, and clustering.

Accident; analysis and prevention
Chain reaction crashes (CRC) begin with a two-vehicle collision and rapidly intensify as more vehicles get directly involved. CRCs result in more extensive damage compared to two-vehicle crashes and understanding the progression of a two-vehicle coll...

Supporting equitable and responsible highway safety improvement funding allocation strategies - Why AI prediction biases matter.

Accident; analysis and prevention
The existing methodologies for allocating highway safety improvement funding closely rely on the utilization of crash prediction models. Specifically, these models produce predictions that estimate future crash hazard levels in different geographical...

Real-time crash prediction on express managed lanes of Interstate highway with anomaly detection learning.

Accident; analysis and prevention
To facilitate efficient transportation, I-4 Express is constructed separately from general use lanes in metropolitan area to improve mobility and reduce congestion. As this new infrastructure would undoubtedly change the traffic network, there is a n...

A spatiotemporal deep learning approach for pedestrian crash risk prediction based on POI trip characteristics and pedestrian exposure intensity.

Accident; analysis and prevention
Pedestrians represent a population of vulnerable road users who are directly exposed to complex traffic conditions, thereby increasing their risk of injury or fatality. This study first constructed a multidimensional indicator to quantify pedestrian ...

Lane-change intention recognition considering oncoming traffic: Novel insights revealed by advances in deep learning.

Accident; analysis and prevention
Lane-changing (LC) intention recognition models have seen limited real-world application due to a lack of research on two-lane two-way road environments. This study constructs a high-fidelity simulated two-lane two-way road to develop a Transformer m...

Predicting pedestrian-involved crash severity using inception-v3 deep learning model.

Accident; analysis and prevention
This research leverages a novel deep learning model, Inception-v3, to predict pedestrian crash severity using data collected over five years (2016-2021) from Louisiana. The final dataset incorporates forty different variables related to pedestrian at...

Can we trust our eyes? Interpreting the misperception of road safety from street view images and deep learning.

Accident; analysis and prevention
Road safety is a critical concern that impacts both human lives and urban development, drawing significant attention from city managers and researchers. The perception of road safety has gained increasing research interest due to its close connection...

Advancing proactive crash prediction: A discretized duration approach for predicting crashes and severity.

Accident; analysis and prevention
Driven by advancements in data-driven methods, recent developments in proactive crash prediction models have primarily focused on implementing machine learning and artificial intelligence. However, from a causal perspective, statistical models are pr...

A spatio-temporal deep learning approach to simulating conflict risk propagation on freeways with trajectory data.

Accident; analysis and prevention
On freeways, sudden deceleration or lane-changing by vehicles can trigger conflict risk that propagates backward in a specific pattern. Simulating this pattern of conflict risk propagation can not only help prevent crashes but is also vital for the d...

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

Accident; analysis and prevention
Accurately modelling crashes, and predicting crash occurrence and associated severities are a prerequisite for devising countermeasures and developing effective road safety management strategies. To this end, crash prediction modelling using machine ...