AIMC Topic: Accidents, Traffic
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Self-Driving Cars and Engineering Ethics: The Need for a System Level Analysis.
Science and engineering ethics
Nov 13, 2017
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
Oct 17, 2017
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)
Sep 23, 2017
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
Sep 20, 2017
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
Sep 6, 2017
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...
Counterfactual simulations applied to SHRP2 crashes: The effect of driver behavior models on safety benefit estimations of intelligent safety systems.
Accident; analysis and prevention
Mar 16, 2017
As the development and deployment of in-vehicle intelligent safety systems (ISS) for crash avoidance and mitigation have rapidly increased in the last decades, the need to evaluate their prospective safety benefits before introduction has never been ...
Predictability and interpretability of hybrid link-level crash frequency models for urban arterials compared to cluster-based and general negative binomial regression models.
International journal of injury control and safety promotion
Feb 24, 2017
Machine learning (ML) techniques have higher prediction accuracy compared to conventional statistical methods for crash frequency modelling. However, their black-box nature limits the interpretability. The objective of this research is to combine bot...
A Novel Multilevel-SVD Method to Improve Multistep Ahead Forecasting in Traffic Accidents Domain.
Computational intelligence and neuroscience
Feb 5, 2017
Here is proposed a novel method for decomposing a nonstationary time series in components of low and high frequency. The method is based on Multilevel Singular Value Decomposition (MSVD) of a Hankel matrix. The decomposition is used to improve the fo...
Why public health should embrace the autonomous car.
Australian and New Zealand journal of public health
Oct 23, 2016
Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.
International journal of injury control and safety promotion
Sep 8, 2016
Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too...
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