Traffic Signal Timing Optimization on Superstreet Using Ecology-Based Optimization

A Superstreet (or RCUT) represents a contemporary approach to intersection design with an unconventional geometric layout. This intersection model has gained significant traction owing to its capacity to mitigate control delays and enhance traffic safety by facilitating traffic flows on the major road without encountering traffic flows from the opposite direction. This study delves into the environmental ramifications of traffic associated with Superstreets, while also proposing an optimization strategy based on an ecology-driven performance metric. Leveraging Genetic Algorithms (GA), we formulate a mathematical framework for controlling Superstreets under fixed-time control conditions. The frequency of stops on the RCUT approach is assessed with varying penalty factors (K), contingent upon traffic and geometric parameters specific to each demand. To simulate the field-like Superstreets, we encode it into the VISSIM simulation model, utilizing this approach to evaluate both Genetic Algorithms and Webster signal plans. Webster's method, a widely employed technique for devising standard signal plans at signalized intersections, serves as a benchmark, having been extensively utilized in practical applications. Employing a range of traffic demand scenarios, we conduct comprehensive calculations. Our findings demonstrate notable enhancements in evaluation metrics, underscoring the viability of the proposed methodology.