Abstract
Two new distributed speed advisory systems (SASs) are introduced in this paper. The systems implement consensus algorithms that guide a set of vehicles toward a common driving speed. A major innovation is that consensus is achieved over a multi-layer network, in which parallel network topologies of connected vehicles are superimposed. The reason for the use of these parallel networks is that, in this way, the state obfuscation is possible, with the benefit that common driving speed is attained with no vehicle knowing the exact state of other vehicles. Convergence of the SASs is formally proved and two new results for the consensus of multi-layer networks modeled via stochastic differential equations are introduced. The SASs are also validated via simulation and via a hardware-in-the-loop setup, in which a real vehicle interacts with simulated entities.
Original language | English |
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Pages (from-to) | 711-721 |
Number of pages | 11 |
Journal | IEEE Transactions on Intelligent Transportation Systems |
Volume | 19 |
Issue number | 3 |
DOIs | |
Publication status | Published - Mar 2018 |
Externally published | Yes |
Keywords
- advanced driver assistance
- algorithm design and analysis
- Automotive applications
- decentralized control
- systems simulation