The International Arab Journal of
Information Technology
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Mohammed Hassan and Malik Al-Amayreh Department of Information Systems and Computer Science, Amman Al-Ahliya University, Jordan
Abstract: This paper provides a novel approach for car traffic control by applying a Web-based Traffic System (WTS). This approach was applied for navigation and traffic information services that are able to inform drivers about the most efficient routes to use in order to avoid traffic delays and roundabout directions. This paper provides a solution for the dynamic changes of the road density and high/low traffic by mean of web and mobile technology. It was applied to the problem of traffic control in the city of Amman-Jordan, and a system is built in cooperation with the Traffic Engineering Department of the Amman City Municipality. In particular, this system is suitable to be uploaded to the Internet and to work online to help drivers and traffic management personnel to be more informed, based on intelligent transport control decisions. This simplifies the control of city transport and makes it more efficient and economical. In this paper, we illustrate the overall architecture of the system and the algorithm used to solve the optimal path problem. WTS represents an online guide traffic status navigation, which may be an important part of any traffic control system and will be a very useful tool for the next generation cars. Keywords: Traffic control, dynamic data, routing algorithm, GIS, optimal path. Received April 11, 2004; accepted October 10, 2004 |
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Rectilinear Follow-up of Trajectory per Robot
Youcef Dahmani and Abdelkader Benyettou Laboratoire SIMPA, Ibn Khaldoun University Tiaret, Algeria Department of Computer Sciences, University of Sciences and Technology of Oran, Algeria
Abstract: Knowing the action space of an order, the objective consists in distributing this space in a certain set of actions equitably in order to choose the famous action among the candidate ones. This process is ensured by reinforcement learning aided by fuzzy logic. We have established an algorithm applying the fuzzy Q-learning with a fuzzy limited lexicon. We have applied it to a robot for the training of the follow-up of a rectilinear trajectory from a starting point “D” at an unspecified arrival point "A", while avoiding with the robot butting against a possible obstacle. The goal of this work tries to answer the question, in what the reinforcement learning applied to fuzzy logic can be of interest in the field of the reactive navigation of a mobile robot. Keywords: Mobile robot, navigation, reinforcement learning, fuzzy logic, fuzzy Q-learning, fuzzy inference system. Received April 21, 2004; accepted August 21, 2004 |