In view of system reliability, extraction of knowledge from models of artificial intelligence may
be more important than their forecasting ability. The elaboration of rules found by …

Achieving Zero Collision Probability in Vehicle Platooning under Cyber Attacks via Machine
Learning Page 1 M. Mongelli, M. Muselli Institute of Electronics, Computer and …

The study deals with intelligible analytics for performance modelling of vehicle platooning.
Knowledge extraction with rules is targeted to understand safety regions (collision …

Automated vehicles promise to be one of the most constructive inventions of late as they
promote road safety, fuel efficiency, and reduced time road travel, by decreasing traffic …

The paper deals with machine learning to accelerate model-checking of vehicle platooning.
The idea is to simulate collision events and provide a set of data for using machine learning …

The article presents theoretical approaches to the development of a methodology for
predicting the occurrence of road accidents on public roads that occur as a result of …

Abstract Automated Vehicles (AVs) are designed and programmed to follow traffic rules.
However, there is no separate and comprehensive regulatory framework dedicated to AVs …

The paper introduces the use of machine learning with rule generation to validate collision
avoidance in vehicle platooning. Cooperative Adaptive Cruise Control is under test over a …

The technological progress over the past decade has revolutionized the transportation
domain. Autonomous and semi-autonomous vehicles have now gained the global spotlight …

Justification of an Integrated Approach to Ensuring Information Security of Unmanned
Vehicles in Intelligent Transport Systems title Title Author Issue Keywords Current Issue …