AIMC Topic: Automobile Driving

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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...

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...

Alzheimer's disease and driving: review of the literature and consensus guideline from Belgian dementia experts and the Belgian road safety institute endorsed by the Belgian Medical Association.

Acta neurologica Belgica
Alzheimer's disease (AD) is a highly prevalent condition and its prevalence is expected to further increase due to the aging of the general population. It is obvious that the diagnosis of AD has implications for driving. Finally, driving discussions ...

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...

Driver behavior profiling: An investigation with different smartphone sensors and machine learning.

PloS one
Driver behavior impacts traffic safety, fuel/energy consumption and gas emissions. Driver behavior profiling tries to understand and positively impact driver behavior. Usually driver behavior profiling tasks involve automated collection of driving da...

Counterfactual simulations applied to SHRP2 crashes: The effect of driver behavior models on safety benefit estimations of intelligent safety systems.

Accident; analysis and prevention
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 ...

Multi-vehicle detection with identity awareness using cascade Adaboost and Adaptive Kalman filter for driver assistant system.

PloS one
Vision-based vehicle detection is an important issue for advanced driver assistance systems. In this paper, we presented an improved multi-vehicle detection and tracking method using cascade Adaboost and Adaptive Kalman filter(AKF) with target identi...

Support Vector Machine Classification of Drunk Driving Behaviour.

International journal of environmental research and public health
Alcohol is the root cause of numerous traffic accidents due to its pharmacological action on the human central nervous system. This study conducted a detection process to distinguish drunk driving from normal driving under simulated driving condition...