Road Intersection Optimization Considering Spatial-Temporal Interactions Among Turning Movement Spillovers

Road intersections play an important role in the operation of an urban road transportation system. However, channelized segment (C-segment) spillovers frequently occur during peak hours, making the vehicle queue on a lane spatially and temporally interact with the queue on another lane. Intersection traffic efficiency is thus largely degraded. Unfortunately, most of the existing models cannot capture the spatial-temporal queue interactions and thus are incapable of developing efficient intersection optimization plans. To fill this gap, the paper proposes a highly efficient approach traffic flow model to capture C-segment spillovers. An optimization problem that takes C-segment spillovers into account is formulated as a nonlinear programming model, and it is solved by using a Markov chain Monte Carlo method. The proposed model and solution are tested in several scenarios with various intersection settings, and the effectiveness of the proposed models is demonstrated. This study is beneficial to understanding C-segment spillovers and the models can be applied to improve traffic efficiency at recurrently-congested intersections.