Driving is a complex task that requires constant attention, and intelligent transportation systems that support drivers in this task must continually infer driver intentions to produce reasonable, safe responses. In this paper we describe a technique for inferring driver intentions, specifically the intention to change lanes, using support vector machines (SVMs). The technique was applied to ex...

Vision for intelligent vehicles is a growing area of research [5] for many practical reasons including the relatively inexpensive nature of camera sensing units and even more the non-contact and non-intrusive manner of observation. The latter is of critical importance when observing the driver inside the vehicle cockpit because no sensing unit should impede the driver’s primary task of driving....

An optimal scheduling approach has been developed for coordinating product delivery activities using fuzzy mathematics. In this approach, optimal delivery scheduling is carried out at three different levels, for situations involving: (1) one driver and one load, (2) one driver and multiple loads, and (3) multiple drivers and multiple loads. Fuzzy-based clustering methods are employed to classif...

This article introduces the Alabama Freeway Incident Detection System-Incident Detection Module (AFIDS-IDM) as a methodology for the detection of freeway incidents. AFIDS-IDM invokes fuzzy cluster analysis in the identification of lane blocking incidents from comparisons of time varying patterns of incident induced and incident free traffic states. Lane traffic counts and density, collected at ...

Autonomously driven cars will combine a variety of technologies in the future, in order to keep an eye on their surroundings and driver at all times and respond appropriately. While fully autonomous driving is still limited to prototypes today, the first partly independently acting assistant systems are already in use on our roads. Optical sensors based on infrared lasers and LEDs are one of th...

this paper aims to investigate a new and intricate behavior of immediate follower during the lane change of leader vehicle. accordingly, the mentioned situation is a transient state in car following behavior during which the follower vehicle considerably deviates from conventional car following models for a limited time, which is a complex state including lateral and longitudinal movement simul...

The Internet of Things (IoT) in healthcare and medical applications promises to solve many problems which are currently challenging the sector, ranging from remotely caring for our aging population to medical discoveries on incurable diseases. However, the challenges and risks of having 50 billion Things and users connected together are complex and may be detrimental to control. Concerns have b...

Since electric vehicle (ELV) deployment can contribute to overall renewable energy sources, exploration of the heterogeneous influence factors (HIFs) affecting willingness accept ELVs assist in realization sustainable development goals, particularly universal access affordable for all. In this research, we explored HIFs that individuals (WAELV) within an integrated decision-making (IDM) framewo...

A monitoring system is designed in where it receives sensory data via wireless sensor network and further processes the data to indicate the current driving aptitude of the driver. Analyzing information related to fatigue using two distinct methods eye movement monitoring and bio signal processing. It is critical that several sensors are integrated and synchronized for a more realistic evaluati...

We seek a mechanism for the classification of the intentional behaviour of a cognitive agent, specifically a driver, in terms of a psychological Perception-Action (P-A) model, such that the resulting system would be potentially suitable for use in intelligent driver assistance. P-A models of human intentionality assume that a cognitive agent’s perceptual domain is learned in response to the out...