R. Akcelik
This paper compares two analytical approaches for modelling signalised intersection networks in relation to the assessment of signal coordination quality as a fundamental element of network performance analysis. These are (i) the traditional model based on using “lane groups” or “links” through aggregation of individual lane conditions, and (ii) a new “lane-based” model of upstream departure and downstream arrival patterns as well as midblock lane changes between upstream and downstream intersections, and the resulting proportions of traffic arriving during the green period at an individual lane level. The latter is part of a lane-based network model that involves blockage of upstream intersection lanes by downstream queues (queue spillback) and capacity constraint applied to oversaturated upstream intersections. The differences between the two models are expected to be particularly important in evaluating closely-spaced intersections with high demand flows where vehicles have limited opportunities for lane changes between intersections. The lane-based model can make use of “special movement classes” (e.g. through movements at external approaches which become turning movements at downstream internal approaches, and the dogleg movements at staggered T intersections) to enhance the modelling of signal platoon patterns. This allows assignment of specific movements to separate lanes and separate signal phases, and tracking of their second-by-second platoon patterns through the network separately. The method also allows better estimation of unequal lane use cases at closely-spaced (paired) intersection systems, a factor which also affects signal platoon patterns. The paper presents a staggered T network example to demonstrate important aspects of modelling signal platoon patterns by approach lane use and movement class, and to compare the resulting traffic performance measures (delay, back of queue, level of service) with those estimated using the traditional method based on lane groups or links.
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Published on 05/04/17
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