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Accidents, Traffic

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Estimating helmet wearing rates via a scalable, low-cost algorithm: a novel integration of deep learning and google street view.

BMC public health
INTRODUCTION: Wearing a helmet reduces the risk of head injuries substantially in the event of a motorcycle crash. Countries around the world are committed to promoting helmet use, but the progress has been slow and uneven. There is an urgent need fo...

An Identification Method for Road Hypnosis Based on Human EEG Data.

Sensors (Basel, Switzerland)
The driver in road hypnosis has not only some external characteristics, but also some internal characteristics. External features have obvious manifestations and can be directly observed. Internal features do not have obvious manifestations and canno...

Analyzing speed-difference impact on freeway joint injury severities of Leading-Following vehicles using statistical and data-driven models.

Accident; analysis and prevention
Rear-end (RE) crashes are notably prevalent and pose a substantial risk on freeways. This paper explores the correlation between speed difference among the following and leading vehicles (Δν) and RE crash risk. Three joint models, comprising both unc...

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

Accident; analysis and prevention
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 associated with injury severity in speeding-related crashes is ess...

A hybrid Machine learning and statistical modeling approach for analyzing the crash severity of mobility scooter users considering temporal instability.

Accident; analysis and prevention
One of the main objectives in improving the quality of life for individuals with disabilities, especially those experiencing mobility issues such as the elderly, is to enhance their day-to-day mobility. Enabling easy mobility contributes to their ind...

Investigating the influence of streetscape environmental characteristics on pedestrian crashes at intersections using street view images and explainable machine learning.

Accident; analysis and prevention
Examining the relationship between streetscape features and road traffic accidents is pivotal for enhancing roadway safety. While previous studies have primarily focused on the influence of street design characteristics, sociodemographic features, an...

Optimizing vehicle Front-End structure for e-bike rider Safety: An advanced Multi-Objective approach using injury prediction models.

Accident; analysis and prevention
A multi-objective optimization method based on an injury prediction model is proposed to address the increasingly prominent safety issues for e-bike riders in Chinese road traffic. This method aims to enhance the protective effect of vehicle front-en...

Analyzing the heterogenous effects of factors on high-range speeding likelihood of taxi speeders: Does explainable deep learning provides more insights than random parameter approach?

Accident; analysis and prevention
The random parameters Generalized Linear Model (GLM) is frequently used to model speeding characteristics and capture the heterogenous effects of factors. However, this statistical approach is seldom employed for prediction and generalization due to ...

Considering multi-scale built environment in modeling severity of traffic violations by elderly drivers: An interpretable machine learning framework.

Accident; analysis and prevention
The causes of traffic violations by elderly drivers are different from those of other age groups. To reduce serious traffic violations that are more likely to cause serious traffic crashes, this study divided the severity of traffic violations into t...

Analysis of harsh braking and harsh acceleration occurrence via explainable imbalanced machine learning using high-resolution smartphone telematics and traffic data.

Accident; analysis and prevention
Harsh driving events such as harsh brakings (HBs) and harsh accelerations (HAs) are promising Surrogate Safety Measures, already extensively utilised in road safety research. However, their occurrence relative to normal driving conditions has not bee...