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Ph.D. Defense Friday, September 15, 2006 Bourns Hall – A171 10:00AM Title: Decentralized Traffic Information System Design Based on Inter-Vehicle Communication Abstract: As traffic congestion continues to grow on our roadway systems, trip travel times are becoming less consistent and less predictable. To help travelers conduct better trip planning, traffic information systems are becoming increasingly valuable. These traffic information systems can be used both off-board (e.g., on the Internet prior to trip departure) or on-board, where several navigation systems exist that can provide real-time traffic information. Most traffic information systems are based on a centralized architecture focused around a traffic management center that collects, processes, and disseminates traffic data. As an alternative approach, there has been recent interest in decentralized traffic information systems, i.e., those that are based on using inter-vehicle communications (IVC). This dissertation presents a decentralized traffic information system design based on inter-vehicle communication. As IVC-equipped vehicles travel the roadways, they can share information on network traffic conditions and regional traffic information can be soon established. Decentralized systems avoid potential single point failures that a TMC-based system might have and are capable of covering roadways that do not have embedded loop detectors. In this dissertation, several traffic estimation algorithms have been investigated. An adaptive dissemination mechanism has been proposed and evaluated. An analytical model has been developed to examine the effect of the key parameters on system performance. An integrated traffic/communication simulation environment has been implemented to simulate the effectiveness of this decentralized traffic information system. Based on the simulation results, it can be seen that by using the proposed adaptive dissemination scheme together with a well-design estimation algorithm, a 5% IVC-equipped vehicle penetration rate can achieve more than 90% road traffic information accuracy under typical conditions. |
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