There are likely to be individual differences in bus driver behaviour when adhering to strict schedules under time pressure. A reliable and valid assessment of these individual differences would be useful for bus companies keen to mitigate risk of crash involvement. This paper reports on three studies to develop and validate a self-report measure of bus driver behaviour. For study 1, two princi...

This paper aims to provide reliable indications of driver drowsiness based on the characteristics of driver–vehicle interaction. A test bed was built under a simulated driving environment, and a total of 12 subjects participated in two experiment sessions requiring different levels of sleep (partial sleepdeprivation versus no sleep-deprivation) before the experiment. The performance of the subj...

Semi-autonomous vehicles are increasingly serving critical functions in various settings from mining to logistics to defence. A key characteristic of such systems is the presence of the human (drivers) in the control loop. To ensure safety, both the driver needs to be aware of the autonomous aspects of the vehicle and the automated features of the vehicle built to enable safer control. In this ...

Statistics have shown that 20% of all road accidents are fatigue-related, and drowsy detection is a car safety algorithm that can alert a snoozing driver in hopes of preventing an accident. This paper proposes a deep architecture referred to as deep drowsiness detection (DDD) network for learning effective features and detecting drowsiness given a RGB input video of a driver. The DDD network co...

Purpose: Driving fatigue has become one of the important causes of road accidents, there are many researches to analyze driver fatigue. EEG is becoming increasingly useful in the measuring fatigue state. Manual interpretation of EEG signals is impossible, so an effective method for automatic detection of EEG signals is crucial needed. Method: In order to evaluate the complex, unstable, and non-...

The accurate evaluation of crash causal factors can provide fundamental information for effective transportation policy, vehicle design, and driver education. Naturalistic driving (ND) data collected with multiple onboard video cameras and sensors provide a unique opportunity to evaluate risk factors during the seconds leading up to a crash. This paper uses a National Academy of Sciences-sponso...

With self-driving vehicles announced for the 2020s, today’s challenges in Intelligent Transportation Systems (ITS) lie in problems related to negotiation and decision making in (spontaneously formed) car collectives. Due to the close coupling and interconnectedness of the involved driver-vehicle entities, effects on the local level induced by cognitive capacities, behavioral patterns, and the s...

An injury risk factor (IRF), which indicates the risk of adverse health effect to lumbar rachis arising from mechanical vibrations, is developed. Experiments have been conducted that consider acceleration levels at the seat of drivers, posture, morphology, density, damping rate and body mass as independent variables. A parametric finite-element model of the lumbar rachis has been generated. It ...

In order to give a warning to the drowsy driver, this paper proposes a new Fatigue Driving Detection Algorithm. AdaBoost algorithm is applied to fast detect and track human faces, and the algorithm is implemented in FPGA; differential template-based multi-algorithms are used to localize human eyes and recognize eye states; PERCLOS algorithm is adopted to analyze and determine whether a person i...