This paper studies and identifies driver`s steering manoeuvre behaviour in near rearend collision. Time-To-Collision (TTC) is utilized in defining driver’s emergency threat assessment. The target scenario is set up under real experimental environment and the naturalistic data from the experiment are collected. Four normal drivers are employed for the experiment to perform the manoeuvre. Artificial Neural Network (ANN) is proposed to model the behaviour of the driver`s steering manoeuvre. The results show that all drivers manage to perform steering manoeuvre within the safe TTC region and the modelling results from ANN are reasonably positive. With further studies and improvements, this model would benefit to evaluate the driving reliability...
The accuracy of the rear-end collision models is crucial for the early warning of potential traffic ...
This paper demonstrates the use of elementary neural networks for modelling and representing driver ...
This study aims at modelling drivers’ speed in car-following during braking situations at intersecti...
This paper studies and identifies driver's steering manoeuvre behaviour in near rear-end collision. ...
This paper describes a basic architecture of an intelligent driver warning system which embodies an ...
The role of automation is becoming increasingly important in the design of modern vehicles. This is ...
This paper provides an overview of the research into the driver behaviour in simulated near collisio...
Lane change behaviour recognition is one of the significant elements in advanced vehicle active syst...
An understanding of the scenario in complex traffic situations is essential in order to give an earl...
This study reviews the Artificial Intelligence and Machine Learning approaches developed thus far fo...
Rear-end crashes are one of the most frequent types of traffic accidents. As a response, in order to...
This paper describes the results of a study performed with the interactive fixed-base driving simula...
Driver’s intention of the front vehicle plays an important role in the automatic emergency braking (...
The present research aims to understand the safety over the midblock road sections and proposes a sa...
Globally, motor vehicle crashes account for over 1.2 million fatalities per year and are the leading...
The accuracy of the rear-end collision models is crucial for the early warning of potential traffic ...
This paper demonstrates the use of elementary neural networks for modelling and representing driver ...
This study aims at modelling drivers’ speed in car-following during braking situations at intersecti...
This paper studies and identifies driver's steering manoeuvre behaviour in near rear-end collision. ...
This paper describes a basic architecture of an intelligent driver warning system which embodies an ...
The role of automation is becoming increasingly important in the design of modern vehicles. This is ...
This paper provides an overview of the research into the driver behaviour in simulated near collisio...
Lane change behaviour recognition is one of the significant elements in advanced vehicle active syst...
An understanding of the scenario in complex traffic situations is essential in order to give an earl...
This study reviews the Artificial Intelligence and Machine Learning approaches developed thus far fo...
Rear-end crashes are one of the most frequent types of traffic accidents. As a response, in order to...
This paper describes the results of a study performed with the interactive fixed-base driving simula...
Driver’s intention of the front vehicle plays an important role in the automatic emergency braking (...
The present research aims to understand the safety over the midblock road sections and proposes a sa...
Globally, motor vehicle crashes account for over 1.2 million fatalities per year and are the leading...
The accuracy of the rear-end collision models is crucial for the early warning of potential traffic ...
This paper demonstrates the use of elementary neural networks for modelling and representing driver ...
This study aims at modelling drivers’ speed in car-following during braking situations at intersecti...