The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intelligent vehicle systems. Here we employ machine learning techniques to detect driver drowsiness. The system obtained 98% performance in predicting driver drowsiness. This is the highest prediction rate reported to date fo...

In today's life, everyone is in hurry to reach their destination as quickly as possible. So people intentionally or unintentionally take harsh driving events such as sudden acceleration, sudden turns or sudden brakes which further lead them to accidents or even loss of their lives. And it is a common belief that if a person behavior is being monitored, it would be relatively safer. To monitor d...

In this paper we examine the requirements for scenario control programming languages and consider approaches for designing textual-based scenario specification languages. By scenario programs, we mean the code that determines what objects are in the simulation environment and how object behaviors are coordinated to produce predictable experiences for the driver in a ground vehicle simulator. Sc...

An adaptive fuzzy logic controller is described which assists the driver in vehicle speed and distance control by offering a driving strategy via an active accelerator and brake pedal. In order to be accepted by the driver, the behavior of the system called ACC (Adaptive Cruise Control) has to meet the expectations of the human driver to a certain degree. The Fuzzy-ACC provides separate control...

Within the past decade, analyzing and modeling human behavior by processing large amounts of collected data has become an active research field in the area of human–machine interaction. The research community is striving to find principled ways to explain and represent important behavioral characteristics of humans, with the goal of developing more efficient and more effective cooperative inter...

Consider the problem of driver behavior recognition from images captured by a camera installed in a vehicle [4]. Recognition of driver behavior is crucial for driver assistance systems that make driving comfortable and safe. One notable requirement for real applicatioins is that we would like to predict and classify a behavior as quickly as possible: if we detect a sign of dangerous movements s...

In this research, a questionnaire survey was conducted to measure nap, drowsiness and fatigue of drivers who work for long shifts, to discuss about the work environment and health conditions for taxi and bus drivers who work at night-time. The questionnaire sheet used for this research was organized into the following categories: tension/tiredness, drowsiness while driving, and the nap situatio...

I n t e l l i g e n t T r a n s p o r t a t i o n S y s t e m s intervention. Many DAS applications are safety oriented, such as lane departure warning systems. Some are comfort oriented, such as automated parking assistants. Still others are designed to alleviate the driver's attentional load—for example, traffic signal detectors or the already deployed intelligent cruise control systems. Thes...

The aim of this study is research the impact of management level's charismatic leadership style on miners' unsafe behavior by using the questionnaires on charismatic leadership style, safety attitude and the miners' unsafe behavior measurement to investigate 200 employees in Shen Dong Company. The research results suggest that management level's charismatic leadership style have very important ...

Advanced driver assistance systems (ADAS) can be significantly improved with effective driver action prediction (DAP). Predicting driver actions early and accurately can help mitigate the effects of potentially unsafe driving behaviors and avoid possible accidents. In this paper, we formulate driver action prediction as a timeseries anomaly prediction problem. While the anomaly (driver actions ...