On Centroid Connectors in Static Traffic Assignment: Their Effects on Flow Patterns and How to Optimize

In this paper, the authors investigate to what extent the results of static traffic assignment (STA) are influenced by centroid connectors and how to optimize their selections. Three networks are used to evaluate the impact of different centroid connector configurations on the resulting traffic flow pattern: a synthetic grid network, the California SR-41 corridor network and a large Sacramento area network. From the STA results of these three networks, the authors observe large fluctuations on resultant link volumes, maximum volume capacity (V/C) ratios, average V/C ratios and total travel time with respect to randomized connector selections. The fluctuations seem to indicate that STA results are unstable with respect to arbitrary connector selections, and this cannot be improved by simply increasing the number of connectors. In fact, more connectors often result in serious under-estimation of total travel time and average link load. The authors infer that, if provided little information of access/egress nodes of trips, randomly generated connectors lead to artificial over- or under-utilization on network links. The authors therefore propose a connector optimization algorithm in which the connectors and their travel times are chosen in such a way that the maximum V/C ratio of some characteristic links, ``direct links'', is minimized. As the numerical example on the SR-41 network indicates, this connector optimization algorithm seems to reduce the artificial over- and under-utilization of network links, and obtain a flow pattern more consistent with the one derived from a more refined network where trip access/egress nodes are known in more details.