Dynamic contracts for distributed temporal logic control of traffic networks

Eric S. Kim, Sadra Sadraddini, Calin Belta, Murat Arcak, and Sanjit A. Seshia. Dynamic contracts for distributed temporal logic control of traffic networks. In 56th IEEE Annual Conference on Decision and Control (CDC), pp. 3640–3645, 2017.

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Abstract

Contract-based design is a method to synthesize distributed control strategies for large-scale networks of dynamically coupled systems. We propose a framework for using dynamic contracts for controlling traffic networks from temporal logic specifications. Given a traffic network, we partition it into a number of smaller sub-networks and compute a collection of assume-guarantee contracts for their dynamical interconnections. A central supervisor chooses the best contracts optimally according to the current state of the system. We use model predictive control (MPC) to find control sequences optimally for each sub-network subject to its contract obligations to and promises from its neighboring sub-networks. Our method is correct-by-design. A case study on a mixed urban-freeway network is presented, where the objective is infinite-time congestion avoidance and temporal requirements on the traffic lights in the urban intersections.

BibTeX

@inproceedings{kim-cdc17,
  author    = {Eric S. Kim and
               Sadra Sadraddini and
               Calin Belta and
               Murat Arcak and
               Sanjit A. Seshia},
  title     = {Dynamic contracts for distributed temporal logic control of traffic
               networks},
  booktitle = {56th {IEEE} Annual Conference on Decision and Control (CDC)},
  pages     = {3640--3645},
  year      = {2017},
  abstract  = {Contract-based design is a method to synthesize distributed control strategies for large-scale networks of dynamically coupled systems. We propose a framework for using dynamic contracts for controlling traffic networks from temporal logic specifications. Given a traffic network, we partition it into a number of smaller sub-networks and compute a collection of assume-guarantee contracts for their dynamical interconnections. A central supervisor chooses the best contracts optimally according to the current state of the system. We use model predictive control (MPC) to find control sequences optimally for each sub-network subject to its contract obligations to and promises from its neighboring sub-networks. Our method is correct-by-design. A case study on a mixed urban-freeway network is presented, where the objective is infinite-time congestion avoidance and temporal requirements on the traffic lights in the urban intersections.},
}