Survey of Bayesian Networks Applications to Intelligent Autonomous Vehicles
It addresses the problem of enabling fully autonomous decision-making for vehicles, but is incremental as it synthesizes existing research without new results.
This survey reviews applications of Bayesian Networks for decision-making in Intelligent Autonomous Vehicles, identifying them as a promising model based on lab efforts, but notes that further real-world testing is needed.
This article reviews the applications of Bayesian Networks to Intelligent Autonomous Vehicles (IAV) from the decision making point of view, which represents the final step for fully Autonomous Vehicles (currently under discussion). Until now, when it comes making high level decisions for Autonomous Vehicles (AVs), humans have the last word. Based on the works cited in this article and analysis done here, the modules of a general decision making framework and its variables are inferred. Many efforts have been made in the labs showing Bayesian Networks as a promising computer model for decision making. Further research should go into the direction of testing Bayesian Network models in real situations. In addition to the applications, Bayesian Network fundamentals are introduced as elements to consider when developing IAVs with the potential of making high level judgement calls.