Crash dieting: The effects of eating and drinking on driving performance

Previous research suggests that compared to mobile phone use, eating and drinking while driving is more common and is seen as lower risk by drivers. Nevertheless, snacking at the wheel can affect vehicle control to a similar extent as using a hands-free phone, and is actually a causal factor in more crashes. So far, though, there has not been a controlled empirical study of this problem. In an effort to fill this gap in the literature, we used the Brunel University Driving Simulator to test participants on a typical urban scenario. At designated points on the drive, which coincided with instructions to eat or drink, a critical incident was simulated by programming a pedestrian to walk in front of the car. Whilst the driving performance variables measured were relatively unaffected by eating and drinking, perceived driver workload was significantly higher and there were more crashes in the critical incident when compared to driving normally. Despite some methodological limitations of the study, when taken together with previous research, the evidence suggests that the physical demands of eating and drinking while driving can increase the risk of a crash

Issues arising from the HASTE experiments

[FIRST PARAGRAPH] The HASTE project work discussed in the foregoing papers can be depicted as being aimed at answering two questions: “Does greater secondary task load from an In-Vehicle Information System (IVIS) lead to an identifiably worse performance in the primary task of driving?” and “How much distraction is too much?”. There is, of course, a huge amount of literature examining the effect of distraction on driving. Some of this concerns visual distraction (e.g. Holohan, Culler & Wilcox, 1978; Dingus, Antin, Hulse & Wierwille, 1989; Wierwille & Tijerina, 1996; Wallace, 2003), while other parts cover distraction from cognitive (auditory) tasks such as mobile phone use (e.g. Stevens & Paulo, 1999; Svenson & Patten, 2003). But, in spite of this large background of research, it can be argued that the HASTE work was pioneering in the sense that it attempted to differentiate between the effects of visual and cognitive distraction and at the same time it attempted to carefully control the “dose” of distraction administered at any one time. These dose-response studies were carried out in three common but quite different experimental settings, a laboratory set-up, advanced driving simulators, and in instrumented vehicles in the field. The project also examined the reliability of the evaluation, with for example six replications of the rural road studies across a variety of driving simulators in five different countries

Smart driving aids and their effects on driving performance and driver distraction

In-vehicle information systems have been shown to increase driver workload and cause distraction; both of which are causal factors for accidents. This simulator study evaluates the impact that two designs for a smart driving aid, and scenario complexity have on workload, distraction and driving performance. Results showed that real-time delivery of smart driving information did not increase driver workload or adversely effect driver distraction, while having the effect of decreasing mean driving speed in both the simple and complex driving scenarios. Subjective workload was shown to increase with task difficulty, as well as revealing important differences between the two interface designs

Surrogate in-vehicle information systems and driver behaviour: Effects of visual and cognitive load in simulated rural driving

The underlying aim of HASTE, an EU FP5 project, is the development of a valid, cost-effective and reliable assessment protocol to evaluate the potential distraction of an in-vehicle information system on driving performance. As part of this development, the current study was performed to examine the systematic relationship between primary and secondary task complexity for a specific task modality in a particular driving environment. Two fundamentally distinct secondary tasks (or surrogate in-vehicle information systems, sIVIS) were developed: a visual search task, designed such that it only required visual processing/demand and an auditory continuous memory task, intended to cognitively load drivers without any visual stimulus. A high fidelity, fixed-base driving simulator was used to test 48 participants on a car following task. Virtual traffic scenarios varied in driving demand. Drivers compensated for both types of sIVIS by reducing their speed (this result was more prominent during interaction with the visual task). However, they seemed incapable of fully prioritising the primary driving task over either the visual or cognitive secondary tasks as an increase in sIVIS demand was associated with a reduction in driving performance: drivers showed reduced anticipation of braking requirements and shorter time-to-collision. These results are of potential interest to designers of in-vehicle systems

Carbon dioxide Storage Potential in the North Sea

Imperial Users onl

A Wildfire Prediction Based on Fuzzy Inference System for Wireless Sensor Networks

The study of forest fires has been traditionally considered as an important application due to the inherent danger that this entails. This phenomenon takes place in hostile regions of difficult access and large areas. Introduction of new technologies such as Wireless Sensor Networks (WSNs) has allowed us to monitor such areas. In this paper, an intelligent system for fire prediction based on wireless sensor networks is presented. This system obtains the probability of fire and fire behavior in a particular area. This information allows firefighters to obtain escape paths and determine strategies to fight the fire. A firefighter can access this information with a portable device on every node of the network. The system has been evaluated by simulation analysis and its implementation is being done in a real environment.Junta de Andalucía P07-TIC-02476Junta de Andalucía TIC-570

Dynamic update of a virtual cell for programming and safe monitoring of an industrial robot

A hardware/software architecture for robot motion planning and on-line safe monitoring has been developed with the objective to assure high flexibility in production control, safety for workers and machinery, with user-friendly interface. The architecture, developed using Microsoft Robotics Developers Studio and implemented for a six-dof COMAU NS 12 robot, established a bidirectional communication between the robot controller and a virtual replica of the real robotic cell. The working space of the real robot can then be easily limited for safety reasons by inserting virtual objects (or sensors) in such a virtual environment. This paper investigates the possibility to achieve an automatic, dynamic update of the virtual cell by using a low cost depth sensor (i.e., a commercial Microsoft Kinect) to detect the presence of completely unknown objects, moving inside the real cell. The experimental tests show that the developed architecture is able to recognize variously shaped mobile objects inside the monitored area and let the robot stop before colliding with them, if the objects are not too small

Smart driving assistance systems : designing and evaluating ecological and conventional displays

In-vehicle information systems have been shown to increase driver workload and cause distraction; both are causal factors for accidents. This simulator study evaluates the impact that two designs for a smart driving aid and scenario complexity has on workload, distraction and driving performance. Results showed that real-time delivery of smart driving information did not increase driver workload or adversely affect driver distraction, while having the effect of decreasing mean driving speed in both the simple and complex driving scenarios. Important differences were also highlighted between conventional and ecologically designed smart driving interfaces with respect to subjective workload and peripheral detection