Automated estimation of the allocation of a driver’s visual attention may be a critical component of future Advanced Driver Assistance Systems. In theory, vision-based tracking of the eye can provide a good estimate of gaze location. In practice, eye tracking from video is challenging because of sunglasses, eyeglass reflections, lighting conditions, occlusions, motion blur, and other factors. E...

Abstract: A driver-vehicle interaction model consisting of a closed loop system, developed recently, has been used to simulate the behaviour of drivers having different values of driver error and driver day dream factors. Concept of Risk Time, Driver Error and Driver Daydream Factors is presented and used to evaluate the vehicle-driver model. A process cycle of a driver-vehicle model is set up ...

The paper presents a driver model, which can be used in a computer simulation of a curved ride of a car. The identification of the driver parameters consisted in a comparison of the results of computer calculations obtained for the driver-vehicle-environment model with different driver data sets with test results of the double lane-change manoeuvre (Standard No. ISO/TR 3888:1975, International ...

Intelligent Driver Model (IDM) is a well-known microscopic model of traffic flow within the traffic engineering societies. While it is a powerful technique for modeling traffic flows, the Intelligent Driver Model lacks the potential of accommodating the notion of drivers’ heterogeneous behavior whenever they are on roads. Concerning the above mentioned, this paper takes the lane to recognize th...

This paper presents a compact driver module for InP MachZehnder modulator (MZM). The size of the driver module is 14mm × 8mm × 2.8mm. We reduce the size of this driver module by integrating two channels for the driver IC, which doesn’t require any external bias tee, and by making the driver package small. With this driver module and InP MZM module mounted on evaluation board, we obtained a well...

A highly integrated system was constructed to assess, and react to, a driver's cognitive load. Sensors embedded throughout the car track a wide variety of driver activities, including driving conditions, driver reactions, control usage, driver reflexes, passenger interaction, and driver attention. The raw sensor readings are compiled and parsed, and used to assess the cognitive and stress load ...