Influence diagrams for the optimization of a vehicle speed profile
This work addresses vehicle speed optimization for racing and automotive applications, representing an incremental application of existing methods to a new domain.
The paper tackled the problem of optimizing a vehicle speed profile by applying influence diagrams to a Formula 1 race car at the Silverstone circuit, resulting in computed lap times and speed profiles that closely matched those achieved by test pilots.
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.