This chapter suggests a formulation for the problem of localizing a vehicle convoy using a Bayesian network (BN). It reviews the theoretical tools of multisensor data fusion. A method proposed for fault‐tolerant data fusion for the localization of a single vehicle is described. The chapter presents an approach for the modeling and localization of a vehicle convoy. The task of navigating a convoy involves moving a set of vehicles in a queue from one point to another by keeping a predefined gap between the vehicles. Each vehicle in the convoy must be able to place itself with respect to the reference path and to the preceding vehicles. Practically, we only need these two pieces of information for the management of the convoy. The BN proves to be a formalism that is potentially very useful because it can integrate the data fusion, diagnostics, learning and control in the same formalism. belief networks; fault tolerance; sensor fusion
Fault‐tolerant Data‐fusion Method: Application on Platoon Vehicle Localization
2012-09-01
39 pages
Article/Chapter (Book)
Electronic Resource
English
Wiley | 2021
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