BACKGROUND Noise is one of the more widespread pollutions of road transportation system, which can cause deterioration in performance. This experimental study was designed to assess the effect of road traffic noise on performance with regard to extra/introversion and sex of participants. The personality trait of extra/introversion has been remarked as relevant factor to mental performance. RE...

Map matching is not always perfect and sometimes produces mismatches. Thus, there is a degree of uncertainty for how well a map-matching algorithm will perform under certain circumstances. Circumstantial factors include accuracies of sensor data and surrounding road network structure, among others. This paper attempts to shed light on this uncertainty and proposes a methodology for predicting p...

We examined whether participants who failed to complete a simulated drive because of simulator sickness (dropouts) differed from those who completed the simulation (completers). Thirteen healthy older adult dropouts (mean age = 74.8 yr) and 12 comparable completers were compared on the following variables: on-road driving performance, the Useful Field of View test, the Attention Network Test, a...

This paper aims at improving two main uncertain factors in neural networks training in developing a composite road safety performance indicator. These factors are the initial value of network weights and the iteration time. More specially, rough sets theory is applied for rule induction and feature selection in decision situations, and the concepts of reduct and core are utilized to generate de...

As part of the Army's Demo III project, a sensor-based system has been developed to identify roads and to enable a mobile robot to drive along them. A ladar sensor, which produces range images, and a color camera are used in conjunction to locate the road surface and its boundaries. Sensing is used to constantly update an internal world model of the road surface. The world model is used to pred...

The long production cycle and huge cost of collecting road network data often leave the data lagging behind the latest real conditions. However, this situation is rapidly changing as the positioning techniques ubiquitously used in mobile devices are gradually being implemented in road network research and applications. Currently, the predominant approaches infer road networks from mobile locati...

Vehicular multi-hop ad hoc networks (VANETs) are an important technology for future developments of vehicular communication systems. Vehicles are able to exchange information within these networks without the need of installing any infrastructure along the roadside. VANETs can be used to improve the road safety by e.g. warning drivers about accidents in front of the road or to provide Internet ...

Reinforcement learning (RL) is the problem faced by a controller that must learn and improve behavior through trial-and-error interactions with a dynamic environment. It is completely an on-line procedure and thus requires no model of the plant nor of the environment. Hence, it seems ideal for vehicle control where uncertainty abounds in terms of the ever-changing vehicle dynamics during its co...

For safe urban driving, one prerequisite is to keep a car within a road-lane boundary. This requires human and robotic drivers to recognize the boundary of a road-lane and the location of the vehicle with respect to the boundary of a road-lane that the vehicle happens to be driving in. We present a new computer vision system that analyzes a stream of perspective images to produce information ab...

The performance of a prototype Ring Imaging Cherenkov Detector is studied using a charged particle beam. The detector performance, using CF4 and air as radiators, is described. Cherenkov angle precision and photoelectron yield using hybrid photodiodes and multi-anode PMTs agree with simulations and are assessed in terms of the requirements of the LHCb experiment. University of Cambridge, Cavend...