Browsing by Author "Unsal, Cem"
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- Intelligent Navigation of Autonomous Vehicles in an Automated Highway System: Learning Methods and Interacting Vehicles ApproachUnsal, Cem (Virginia Tech, 1998-07-12)One of today's most serious social, economical and environmental problems is traffic congestion. In addition to the financial cost of the problem, the number of traffic related injuries and casualties is very high. A recently considered approach to increase safety while reducing congestion and improving driving conditions is Automated Highway Systems (AHS). The AHS will evolve from the present highway system to an intelligent vehicle/highway system that will incorporate communication, vehicle control and traffic management techniques to provide safe, fast and more efficient surface transportation. A key factor in AHS deployment is intelligent vehicle control. While the technology to safely maneuver the vehicles exists, the problem of making intelligent decisions to improve a single vehicle's travel time and safety while optimizing the overall traffic flow is still a stumbling block. We propose an artificial intelligence technique called stochastic learning automata to design an intelligent vehicle path controller. Using the information obtained by on-board sensors and local communication modules, two automata are capable of learning the best possible (lateral and longitudinal) actions to avoid collisions. This learning method is capable of adapting to the automata environment resulting from unmodeled physical environment. Simulations for simultaneous lateral and longitudinal control of an autonomous vehicle provide encouraging results. Although the learning approach taken is capable of providing a safe decision, optimization of the overall traffic flow is also possible by studying the interaction of the vehicles. The design of the adaptive vehicle path planner based on local information is then carried onto the interaction of multiple intelligent vehicles. By analyzing the situations consisting of conflicting desired vehicle paths, we extend our design by additional decision structures. The analysis of the situations and the design of the additional structures are made possible by the study of the interacting reward-penalty mechanisms in individual vehicles. The definition of the physical environment of a vehicle as a series of discrete state transitions associated with a "stationary automata environment" is the key to this analysis and to the design of the intelligent vehicle path controller. This work was supported in part by the Center for Transportation Research and Virginia DOT under Smart Road project, by General Motors ITS Fellowship program, and by Naval Research Laboratory under grant no. N000114-93-1-G022.
- Self-organization in large populations of mobile robotsUnsal, Cem (Virginia Tech, 1993)A homogeneous population of robots described as an Army-ant swarm is to be realized for material transportation. Robots envisioned in the Army-ant scenario are relatively small, independent autonomous mobile robots that can cooperatively carry palletized loads. In this thesis, the agents are treated as a self-organizing system of moving points. This characteristic makes the Army-ant swarm a modular, adaptive, and dynamic system. Several algorithms for the spatial self-organization of the robots are given. Self-organizing agents can arrange themselves geometrically in two- and three-dimensional space using only local information about teammates. The method is a distributed one: each agent uses only the information obtained by its own sensors. Algorithms are based on feasible assumptions. It is also shown possible to divide such a population into different groups around goals by communicating minimal data. Data transfer has a broadcast characteristic. Behavioral self-organization in the Army-ant scenario is also investigated. Activation and inhibition relations between robots determine the behavior (position in a behavioral space) of the agents, while in spatial self-organization force fields are in effect. Several problems which may be encountered and the solution to some of these problems are outlined. Methods for communication and cooperative decision systems — such as coupled van der Pol oscillators — in finding and carrying the pallets are proposed. Sensors and communication systems that may be used in the Army-ant scenario are also briefly discussed.