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- 저자 : Agbolosu-Amison, Seli James (검색결과 2 건)
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Agbolosu-Amison, Seli James,Yun, Ilsoo,Park, Byungkyu Brian 대한토목학회 2012 KSCE Journal of Civil Engineering Vol.16 No.3
Traffic signal timing optimization and control are one of the most cost-effective ways of improving urban arterial network congestions. Among various control modes, actuated traffic signal control is designed to provide green times where they are needed and it uses a pre-specified gap-out time to determine early termination of current phase green time. However, the effectiveness of its signal state decisions is limited by its dependence on vehicular information from fixed point sensors. With the emerging wireless communication technology based on cooperative vehicle-infrastructure system known as IntelliDrive, individual vehicular information (e.g., speed, acceleration, and location) is needed to be fully utilized for traffic signal control applications. This paper presents a dynamic gap-out approach that uses individual vehicular information and quantified benefits of the proposed approach via simulation. The timing plans were optimized by the genetic algorithm for both the traditional and the proposed gap-out cases. The results based on a four-leg intersection indicated that the dynamic gap-out reduced vehicular delays by 12.5% over existing regular gap-out.
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Seli James Agbolosu-Amison,윤일수,박병규 대한토목학회 2012 KSCE JOURNAL OF CIVIL ENGINEERING Vol.16 No.3
Traffic signal timing optimization and control are one of the most cost-effective ways of improving urban arterial network congestions. Among various control modes, actuated traffic signal control is designed to provide green times where they are needed and it uses a pre-specified gap-out time to determine early termination of current phase green time. However, the effectiveness of its signal state decisions is limited by its dependence on vehicular information from fixed point sensors. With the emerging wireless communication technology based on cooperative vehicle-infrastructure system known as IntelliDrive, individual vehicular information (e.g., speed, acceleration, and location) is needed to be fully utilized for traffic signal control applications. This paper presents a dynamic gap-out approach that uses individual vehicular information and quantified benefits of the proposed approach via simulation. The timing plans were optimized by the genetic algorithm for both the traditional and the proposed gap-out cases. The results based on a four-leg intersection indicated that the dynamic gap-out reduced vehicular delays by 12.5% over existing regular gap-out.
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