An algorithm to design signal coordination for networks with oversaturated intersections is presented. The basic concept of signal coordination applied to oversaturated single arterials is extended for a grid network of arterials, which involves greater analytical and computing complexity. In this algorithm, signal coordination is formulated as a dynamic optimization problem. The problem is developed to coordinate oversaturated signals along an arterial that crosses multiple, parallel coordinated arterials. Signals along crossing arterials are also oversaturated. During an oversaturated period, the algorithm manages local queues by spatially distributing them over a number of signalized intersections and by temporarily spreading them over signal cycles. Depending on the traffic demand's variation and the position of critical signals, the algorithm intelligently generates optimal signal timing (green times and offsets) along individual arterials. If critical signals are located at the exit points, the algorithm sets the optimal signal timing that protects them from becoming excessively loaded. If critical signals are located at the entry points, the algorithm ensures that queues are reduced or cleared before released platoons arrive at a downstream signal system. In addition, the algorithm eventually finds a set of common cycles propagated from upstream signals, thus promoting traffic progression. The micro-genetic algorithm was used to solve the signal optimization problem. The algorithm was tested on a one-way arterial system with 20 signals. The results indicate that the algorithm successfully managed queues along coordinated arterials, made the signals share the burden of traffic, and created the opportunity for traffic progression in specified directions.
