Although there is currently significant development in active vehicle safety (AVS) systems, the number of accidents, injury severity levels and fatalities has not reduced. In fact, human error, low performance, drowsiness and distraction may account for a majority in all the accident causation. Active safety systems are unaware of the context and driver status, so these systems cannot improve t...

In this paper we demonstrate a driver intent inference system (DIIS) based on lane positional information, vehicle parameters, and driver head motion. We present robust computer vision methods for identifying and tracking freeway lanes and driver head motion. These algorithms are then applied and evaluated on real-world data collected in a modular intelligent vehicle test-bed. Analysis of the d...

Modern safety systems are transforming vehicles from human-controlled passive devices into human-centric intelligent/ active systems. There is a wide range of systems from fully autonomous vehicles to humanaugmented control devices which have emerged in this field. In current trends, co-operative active systems have the driver in the decision and control processes are favored for their ‘human-c...

Obstacle detection is an active research area in the field of image processing. On road obstacle detection is an important problem in the area of intelligent transportation systems, driver assistance systems and automated guided vehicles. The proposed algorithm detects all obstacles on road using a single onboard camera which is mounted on a travelled vehicle in real-time for driver assistance....

This paper concerns research towards the provision of a rich set of road vehicle driver assistance modes to reduce the stress and improve the safety of negotiating both on-road and offroad terrain. These modes include navigation planning, potential collision warnings, blind spot and rear traffic monitoring, backing assistance, drowsiness detection and night vision enhancement. The approach take...

The quantitative measurement of driver behavior has been central to much of the systematic research underlying highway safety issues during the past forty years. It has contributed to the way in which we design roads, vehicles, training programs, signs and markings, and intelligent transportation systems. Yet the methods we use to conduct driver behavior experiments may result in a disconnect w...

This paper proposes a novel concept of intelligent navigator that can give the driver timely advice on safe and efficient driving. From both the current traffic condition obtained from visual data and the driver’s goal and preference in driving, it autonomously generates advice and give it to the driver. Not only operational level advice, such as emergency braking due to an abrupt deceleration ...

Digital identity management (IdM) for citizen-life processes requires trusted relationship among the service providers and users. Current IdM systems tend to lack the trust component in particular for online transactions. We propose the use of ePassport as a globally interoperable trust token to bridge the gap between offline and online environments. The paper analyses trust attributes of the e...