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- W4310502044 abstract "As autonomous systems become more integrated into human lives, it is essential to ensure that they maintain high levels of safety and reliability to prevent accidents or injuries from occurring. One rapidly growing area is that of autonomous vehicles. One common scenario for autonomous vehicles is traveling down a roadway in a platoon or convoy. The vehicles need to communicate data between them to maintain their positions. However, unreliability in the network can lead to missing or late arriving data, which forces the cars to use stale data from earlier communications. This paper investigates the effects of stale data on autonomous platooning models. In particular, we investigate which parameters may need to be protected by performing sensitivity analysis and analyzing how the platooning model behaves in the presence of stale data. By increasing the understanding of how the model behaves and which input parameters are influential, algorithms can then be developed to specifically target the characteristics of the vulnerable systems." @default.
- W4310502044 created "2022-12-11" @default.
- W4310502044 creator A5003772863 @default.
- W4310502044 creator A5055376775 @default.
- W4310502044 date "2022-10-26" @default.
- W4310502044 modified "2023-09-24" @default.
- W4310502044 title "Stale Data Analysis in Intelligent Transportation Platooning Models" @default.
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- W4310502044 doi "https://doi.org/10.1109/uemcon54665.2022.9965630" @default.
- W4310502044 hasPublicationYear "2022" @default.
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