“Smart” vehicles of the future are envisioned to aid their drivers in reducing fuel consumption and emissions by wirelessly receiving phase-shifting information of the traffic lights in their vicinity and computing an optimized speed in order to avoid braking and acceleration maneuvers. Previous studies have demonstrated the potential environmental benefit in small-scale simulation scenarios. To assess the overall benefit, large-scale simulations are required. In order to ensure computational feasibility, the applied simulation models need to be simplified as far as possible without sacrificing credibility. Therefore this work presents the results of a sensitivity analysis and identifies gear choice and the distance from the traffic light at which vehicles are informed as key influencing factors. Our results indicate that a suboptimal gear choice can void the benefits of the speed adaptation. Furthermore, we present first results of a scale-up simulation using a real-world inner-city road network and discuss the range in which we expect the saving in fuel consumption to be in reality.