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An experiment was conducted in a fixed-base driving simulator to observe young drivers' their physiology changes under high mental workload, while responding to two sets of mental tasks: n-back and sound counting. 20 drivers (9 of them younger than 25 (range 21–24) and 11 older than 25 (range 29–33) were instructed to drive along two sections on a highway at a constant speed. NASA-TLX scores for workload...
Never Stop is an intelligent transportation system with sensor to control the traffic lights at intersection automatically. It utilizes fuzzy control method and genetic algorithm to adjust the waiting time for the traffic lights, consequently the average waiting time can be significantly reduced. A prototype system has been implemented at an EBox-II terminal device, running the fuzzy control and genetic...
The assessment index system of emergency maintenance guarantee capability at vehicle equipments of armed police force is set up and the principles are put forward. The weight of every index is determined by applying AHP method. Finally, depending on fuzzy mathematics, a comprehensive assessment model of emergency maintenance guarantee capability at vehicle equipments for armed police force is built...
Vehicular ad hoc networks (VANETs) have become a promising application of mobile ad-hoc networks (MANETs). Since an inaccurate traffic warning message will impact drivers' decisions, and misguide drivers' behavior, one of the main challenges in VANETs is to forward messages in such a way that the information content can be trusted by receiving nodes. In this paper, we proposed a reputation management...
This paper is to propose a fault knowledge acquisition method for metro vehicles fault diagnosis at present, the lack of metro vehicles fault diagnosis knowledge and the difficulty of acquiring the fault diagnosis knowledge hinder the development of fault diagnosis for metro vehicles. On the basis of profounding analysis of the mechanism for the forming of metro vehicle faults, this method is to design...
Motion analysis is a very attractive research direction in computer vision field. In this paper, we propose a framework for analyzing real vehicle motion in visual traffic surveillance by using Segment Model (SM), which is a kind of probabilistic model. SM can grasp the underlying information of observation sequence by using segment distribution. It has been proved to be more precise than that of...
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