Genetic algorithm optimizations of traffic signal timings have been shown to be effective, continually outperforming traditional optimization tools such as Synchro and TRANSYT-7F. However, their application has been limited to scholarly research and evaluations. Only one tool has matured to a commercial deployment: direct CorSim optimization, a feature of TRANSYT-7F. A genetic algorithm formulation, VisSim-based genetic algorithm optimization of signal timings (VISGAOST), is presented; it builds on the best of the recorded methods by extending their capabilities. It optimizes four basic signal timing parameters with VisSim microsimulation as an evaluation environment. The program brings new optimization features not available in the direct CorSim optimization, such as the optimization of phasing sequences, multiple coordinated systems and uncoordinated intersections, fully actuated isolated intersections, and multiple time periods. The formulation has two features that enhance and reduce computational time: optimization resumption and parallel computing. The program has been tested on two VisSim networks: a hypothetical grid network and a real-world arterial of actuated–coordinated intersections in Park City, Utah. The results show that timing plans optimized by the genetic algorithm outperformed the best Synchro plans in both cases, reducing delay and stops by at least 5%.

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Most individuals living in cold climates realize that on snowy days their commute will take longer. Although traffic volumes are often lower, the combination of reduced speeds and capacity causes severe congestion, particularly on signalized urban networks. Signal coordination that reduces traffic congestion in typical clear conditions results in an uncoordinated and suboptimal timing plan. Traffic parameters for developing signal timings during inclement weather conditions are examined. With the completion of the Utah Department of Transportation (UDOT) advanced transportation management system, there is an opportunity to change signal timing plans by communicating with each controller from the Transportation Operations Center. This operation makes feasible a library of special signal timing plans, with one allocated for inclement weather. Traffic flow data were collected over a range of seven inclement weather severity conditions at two intersections for the 1999–2000 winter season. The data indicate that the largest decrease in vehicle performance occurs when snow and slush begin to accumulate on the road surface. Saturation flows decrease by 20 percent, speeds decrease by 30 percent, and start-up lost times increase by 23 percent. UDOT is now developing and implementing modified inclement weather coordinated signal timing plans for the major signalized corridors in the Salt Lake Valley. The determination of when to implement an inclement weather signal timing plan is based on four general criteria: storm severity, projected duration, area of influence, and immediately projected running speeds. With these considerations, traffic engineers can determine whether to implement an inclement weather signal timing plan.

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This paper presents an analysis of different transit signal priorities (TSPs) for a future bus rapid transit (BRT) corridor in West Valley City, Utah. The goal was to find the optimal TSP strategy for estimated and planned traffic and transit operations. The study used VISSIM microsimulation software in combination with ASC/3 software-in-the-loop simulation. Four models were used in the analysis: no TSP, TSP, TSP with phase rotation, and custom TSP. The results showed that TSP with phase rotation and custom TSP could both be considered for implementation. TSP with phase rotation would provide significant benefits for BRT, with minimum impacts on vehicular traffic. Custom TSP would provide major benefits for BRT in travel times, delays, and stops. However, this strategy has more impact on vehicular traffic. Custom TSP is an advanced strategy that still needs examination and improvement. The study provides a set of instructions on how the described strategies can be implemented in field traffic controllers.