Investigation of Centroid Connector Placement for Advanced Traffic Assignment Models with Added Network Detail

Abstract

Advanced traffic assignment models, such as simulation-based dynamic traffic assignment, typically incorporate more detailed network representations than do traditional planning models. In this context, the placement of centroid connectors may have a significant effect on model performance, and attention must be paid to their number and location to avoid unrealistic congestion or low utilization of minor roadways by local traffic. Given that the manual inspection of centroid connector placement may be too time-consuming in large regional networks, this paper proposes two simple automatic centroid connector placement strategies for dynamic traffic assignment applications. The first approach radially distributes the connectors to the nearest nodes and is intended to exemplify some limitations of the most common techniques in practice. The second strategy involves dividing the centroid and subsequent demand into two parts, distributing the demand across one sub-centroid linked to nearby nodes and one linked to the periphery, and thus effectively establishing a bilevel distribution. A modification of this strategy involves eliminating nodes at signalized intersections as viable candidates for connection. As part of the evaluation of the methods, a new metric, the locality factor, has been introduced to describe the use of minor streets by local traffic. The numerical experiments, conducted on two real-world networks, exemplify the effects of the incorporation of local streets and the placement of centroid connectors on model results. Sensitivity testing and limited field data comparisons suggest that the bilevel centroid connector placement strategy achieves more realistic results.