Modeling the Impact of Downstream Conditions on Discharging Behavior of Vehicles at Signalized Intersections Using Micro-Simulation

Abstract

© 2020, King Fahd University of Petroleum & Minerals. In areas where traffic demand is high and intersections are closely spaced, the drivers’ desire for quick discharge is demotivated by negative downstream conditions, such as long queues and poorly coordinated traffic signals, which may lead to lower saturation flow rate (SFR) for upstream lane groups. However, existing models do not consider this phenomenon. This paper proposes an improved intelligent driver model for reproducing the impacts of downstream traffic conditions on the discharging behavior of vehicles and the estimated SFR. A micro-simulation platform for two closely spaced signalized intersections is built to test the improved car-following model and to simulate the influenced SFR. Results from the sensitivity analysis and the comparison with empirical data show that the developed model could rationally and reliably reproduce the SFR reduction under different downstream conditions. As the queue in the downstream segment becomes longer and the offset becomes larger due to poor coordination, the SFR at the upstream intersection deteriorates. The developed model can be applied in traffic simulations to provide more realistic discharging behavior considering the downstream conditions.