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Innovations-based priority assignment for control over CAN-like networks.In: 54th IEEE Conference on Abstract-We present an innovations-based prioritization mechanism to efficiently use network resources for data gathering, without compromising the real-time decision making capability of the control systems. In the envisioned protocol, each sensor assigns the Value of Information (VoI) contained in its current observations for the network as the priority. Tournaments are used to compare priorities and assign transmission slots, like in the CAN bus protocol. By using a rollout strategy, we derive feasible algorithms for computing the VoI-based priorities for the case of coupled and decoupled systems. In the case of decoupled systems, performance guarantees with regard to the control cost of the VoI-based strategy are identified. We illustrate the efficiency of the proposed approach on a platooning example in which the vehicles receive measurements from multiple sensors.

We propose an intersection crossing algorithm for autonomous vehicles with vehicle to infrastructure (V2I) communication capability. All vehicles attempting to cross the intersection share their expected time of entering a critical zone based on decentralized model predictive control (MPC) results. These time suggestions are collected at a central intersection management (IM) unit, which is responsible for coordinating the vehicles. A time-based negotiation process between vehicles and IM is conducted to find a safe solution. An advantage of the approach is that model-based vehicle data is kept private, while the computational burden of the intersection coordination is distributed between the central IM and the vehicles. We prove the existence of a feasible solution and illustrate the introduced negotiation algorithm by simulation of an intersection crossing scenario with disturbances. The results show that vehicles remain in a safe distance without sharing private data.

We introduce a distributed control method for coordinating multiple vehicles in the framework of an automated valet parking (AVP) system. The control functionality is distributed between an infrastructure server, called parking area management (PAM) system, and local autonomous vehicle control units. Via a vehicle-to-infrastructure (V2I) communication interface, model predictive control (MPC) decisions of the vehicles are shared with the coordination unit in the PAM. This unit in turn computes a coupling feedback which is shared with the vehicles. The control system is integrated in an automated test-system to cope with the high test requirements and short development cycles of highly automated systems. Evaluations conducted with the test-system show the functionality of the proposed distributed control method for multi-vehicle coordination. Results indicate safe coordination, and an efficiency increase compared to an uncoordinated method in an AVP simulation environment.