Evaluating Incident Responsive Signal Control Plans using Multi-Resolution Modeling

Abstract

The implementation of incident responsive signal control strategies can be effective in relieving congestion during traffic incidents. The goal of this paper is to develop and evaluate a methodology to assess the impacts of incident responsive signal control. This study demonstrates the utilization of a multi-resolution and multi-scenario modeling approach to support the evaluation and design of incident management strategies and the associated incident responsive signal control. The approach utilizes the strength of mesoscopic simulation-based dynamic traffic assignment modeling to determine route diversion and microscopic simulation to estimate the traffic impacts of incident responsive signal timing. The methods also utilize detailed traffic and incident data to inform the analysis, modeling, and simulation. The utilized methods support the modeling of different traffic patterns, confirm the diversion estimated by modeling tools based on field detector data, provide estimation of capacity drop during arterial incidents with different locations from upstream and downstream signals, and address the need for accurate turning movement volumes resulting from the modeling. Results of the case study indicate that implementation of incident responsive signal control strategies provided a reduction in total delay of through movement in the incident direction of 18.5% and 24.5% for 30-min and 45-min incidents, respectively. The corresponding reductions in total delay of all movements in the segment were 7.5% and 9.5%, respectively. These values can be used to inform the return-on-investment as part of planning and operation analysis of active transportation management strategies.