Improved Model for Estimating Incident Impact on Urban Street Travel Time with Consideration of Upstream Intersection Capacity Reduction

The estimations of incident and incident management impacts on urban street performance have been a challenging issue for signalized networks due to the interactions between traffic control and the drop in capacity due to incidents. This study proposes a methodology to calculate the incident delays at signalized networks, taking into consideration this interaction. Regression equations are developed, based on microscopic simulation modeling, to allow the estimation of the drop in capacity at upstream intersections considering the distance to a downstream incident location and the volume to capacity (V/C) ratio at the incident location. As expected, the drop in capacity increases as the incident location gets closer to the upstream signal and as the V/C ratio at the incident location increases. The incident delay impacts are calculated as a combination of the traffic delay at the incident location calculated using queuing equations plus the increase in control delay at the upstream intersection resulting from the queue spilling back due to the incident. The increase in control delay is calculated using the signalized intersection control delay equations of the Highway Capacity Manual (HCM). Comparison with microscopic simulation results shows that estimating the delay using this method produces better results than those produced when using the deterministic queuing method procedure by it. The derived regression models are recommended to be used in sketch planning tools, macroscopic and mesoscopic simulation models, and data analytics tools to calculate incident delays on urban streets.