This paper presents a decentralised mechanism for traffic control of connected autonomous vehicles in settings where multiple road intersections have to be managed and optimised. We propose a solution based on the distributed constraint optimisation approach (DCOP). We build upon state of the art algorithm for single-intersection management in order to manage congestion both across and within intersections. Furthermore, to solve the DCOP, we propose an improved node ordering policy for the Max-sum_AD_VP algorithm. Empirical evaluation of our model and algorithm demonstrate that our approach outperforms existing benchmarks by up to 32% in terms of average delay for both single and multiple intersection setup.

Decentralised Multi-intersection Congestion Control for Connected Autonomous Vehicles

Alessandro Farinelli
2020-01-01

Abstract

This paper presents a decentralised mechanism for traffic control of connected autonomous vehicles in settings where multiple road intersections have to be managed and optimised. We propose a solution based on the distributed constraint optimisation approach (DCOP). We build upon state of the art algorithm for single-intersection management in order to manage congestion both across and within intersections. Furthermore, to solve the DCOP, we propose an improved node ordering policy for the Max-sum_AD_VP algorithm. Empirical evaluation of our model and algorithm demonstrate that our approach outperforms existing benchmarks by up to 32% in terms of average delay for both single and multiple intersection setup.
2020
978-3-030-66411-4
Congestion control, Connected vehicles, Distributed constraints optimisation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1041594
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