We investigate robustness properties of the Generalized Proportional Allocation (GPA) policy that has been recently proposed for traffic signal control in urban networks. The GPA policy is fully decentralized, relies only on local information on the current congestion state, and requires no knowledge of the routing, the exogenous inflows, or the network structure. In previous work, we proved throughput optimality of the GPA policy, by showing that it is able to stabilize the traffic network dynamics whenever any controller is able to do so. In this paper, we first extend these results by showing that even when the measurements have offsets, the GPA policy maintains the same stability properties as with exact measurements. A comparison between the GPA and the MaxPressure traffic signal controllers with respect to robustness is also performed in a microscopic traffic simulator, where it is shown that while the GPA can handle offsets in the measurements, the MaxPressure controller may mak...
We investigate robustness properties of the Generalized Proportional Allocation (GPA) policy that has been recently proposed for traffic signal control in urban networks. The GPA policy is fully decentralized, relies only on local information on the current congestion state, and requires no knowledge of the routing, the exogenous inflows, or the network structure. In previous work, we proved throughput optimality of the GPA policy, by showing that it is able to stabilize the traffic network dynamics whenever any controller is able to do so. In this paper, we first extend these results by showing that even when the measurements have offsets, the GPA policy maintains the same stability properties as with exact measurements. A comparison between the GPA and the MaxPressure traffic signal controllers with respect to robustness is also performed in a microscopic traffic simulator, where it is shown that while the GPA can handle offsets in the measurements, the MaxPressure controller may make vehicles wait forever.
On Robustness of the Generalized Proportional Controller for Traffic Signal Control / Nilsson, G.; Como, G.. - 2020-:(2020), pp. 1191-1196. ( 2020 American Control Conference, ACC 2020 usa 2020) [10.23919/ACC45564.2020.9147471].
On Robustness of the Generalized Proportional Controller for Traffic Signal Control
Nilsson G.;
2020-01-01
Abstract
We investigate robustness properties of the Generalized Proportional Allocation (GPA) policy that has been recently proposed for traffic signal control in urban networks. The GPA policy is fully decentralized, relies only on local information on the current congestion state, and requires no knowledge of the routing, the exogenous inflows, or the network structure. In previous work, we proved throughput optimality of the GPA policy, by showing that it is able to stabilize the traffic network dynamics whenever any controller is able to do so. In this paper, we first extend these results by showing that even when the measurements have offsets, the GPA policy maintains the same stability properties as with exact measurements. A comparison between the GPA and the MaxPressure traffic signal controllers with respect to robustness is also performed in a microscopic traffic simulator, where it is shown that while the GPA can handle offsets in the measurements, the MaxPressure controller may mak...I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione
