Fuzzy logic is known to be suited for dealing with a complex optimization problem with many objectives, many constraints, unclear input information, and vague decision criteria. Controlling the timing of a traffic signal falls in this category of problem. Fuzzy logic is introduced for controlling the timing of a pedestrian crossing signal. The controller is designed to emulate the decision process of an experienced crossing guard. The performance of this control is tested against two types of conventional demand-actuated control: one that uses the traditional green extension and the other that uses modified extension rules. The criteria for evaluation are delays to the pedestrians and the vehicles, and the percentage of vehicles that are stopped. The fuzzy logic controller finds a compromise between two conflicting objectives: minimization of pedestrian delay and minimization of vehicular delay and stops. The evaluation was performed using a microscopic simulation called HUTSIM developed at the Helsinki University of Technology. The fuzzy logic controller performs equally well as or better than conventional demand-actuated control without requiring many parameter settings. Furthermore, the control rules are simple and a compilation of rational decision processes is expressed in natural language.