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Accidents, Traffic

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A trial of retrofitted advisory collision avoidance technology in government fleet vehicles.

Accident; analysis and prevention
In-vehicle collision avoidance technology (CAT) has the potential to prevent crash involvement. In 2015, Transport for New South Wales undertook a trial of a Mobileye 560 CAT system that was installed in 34 government fleet vehicles for a period of s...

Modeling when and where a secondary accident occurs.

Accident; analysis and prevention
The occurrence of secondary accidents leads to traffic congestion and road safety issues. Secondary accident prevention has become a major consideration in traffic incident management. This paper investigates the location and time of a potential seco...

Identification of significant factors in fatal-injury highway crashes using genetic algorithm and neural network.

Accident; analysis and prevention
Identification of the significant factors of traffic crashes has been a primary concern of the transportation safety research community for many years. A fatal-injury crash is a comprehensive result influenced by multiple variables involved at the mo...

Machine learning, social learning and the governance of self-driving cars.

Social studies of science
Self-driving cars, a quintessentially 'smart' technology, are not born smart. The algorithms that control their movements are learning as the technology emerges. Self-driving cars represent a high-stakes test of the powers of machine learning, as wel...

Self-Driving Cars and Engineering Ethics: The Need for a System Level Analysis.

Science and engineering ethics
The literature on self-driving cars and ethics continues to grow. Yet much of it focuses on ethical complexities emerging from an individual vehicle. That is an important but insufficient step towards determining how the technology will impact human ...

Towards social autonomous vehicles: Efficient collision avoidance scheme using Richardson's arms race model.

PloS one
This paper presents the concept of a social autonomous agent to conceptualize such Autonomous Vehicles (AVs), which interacts with other AVs using social manners similar to human behavior. The presented AVs also have the capability of predicting inte...

On-Board Detection of Pedestrian Intentions.

Sensors (Basel, Switzerland)
Avoiding vehicle-to-pedestrian crashes is a critical requirement for nowadays advanced driver assistant systems (ADAS) and future self-driving vehicles. Accordingly, detecting pedestrians from raw sensor data has a history of more than 15 years of re...

Examining accident reports involving autonomous vehicles in California.

PloS one
Autonomous Vehicle technology is quickly expanding its market and has found in Silicon Valley, California, a strong foothold for preliminary testing on public roads. In an effort to promote safety and transparency to consumers, the California Departm...

Comparison of four statistical and machine learning methods for crash severity prediction.

Accident; analysis and prevention
Crash severity prediction models enable different agencies to predict the severity of a reported crash with unknown severity or the severity of crashes that may be expected to occur sometime in the future. This paper had three main objectives: compar...