Platooning control – the automatic distance control in a chain of vehicles – has seen more than 2000 publications in the past 30 years, along with a corresponding number of different algorithms. However, comparisons between such controllers have rarely been done. Moreover, a fair comparison requires that all controller parameters are chosen to be optimal, often manually, which is a labor intensive and hard to replicate process. In this article we demonstrate the benefits of a methodology for parameter selection that encompasses: an evaluator employing a common metric, a simulator component, and an optimizer, all integrated into an optimization framework – along with an open-source reference implementation. We also discuss the trade-offs of different optimization algorithms, both from the literature and custom-built, for parameter optimization of platooning controllers.