Influence diagrams for the optimization of a vehicle speed profile
  Influence diagrams are decision theoretic extensions of Bayesian networks.
They are applied to diverse decision problems. In this paper we apply influence
diagrams to the optimization of a vehicle speed profile. We present results of
computational experiments in which an influence diagram was used to optimize
the speed profile of a Formula 1 race car at the Silverstone F1 circuit. The
computed lap time and speed profiles correspond well to those achieved by test
pilots. An extended version of our model that considers a more complex
optimization function and diverse traffic constraints is currently being tested
onboard a testing car by a major car manufacturer. This paper opens doors for
new applications of influence diagrams.
