Synchronization-based cooperative trajectory planning of networked vehicles

Kloock, Maximilian Martin; Kowalewski, Stefan (Thesis advisor); Althoff, Matthias (Thesis advisor)

Aachen : RWTH Aachen University (2023)
Book, Dissertation / PhD Thesis

In: Aachener Informatik-Berichte (AIB) 2023,02
Page(s)/Article-Nr.: 1 Online-Ressource : Illustrationen, Diagramme

Dissertation, RWTH Aachen University, 2023


Centralized decision-making for a Networked Control System (NCS) suffers from a high computational burden on the planning agent. Distributed agents, which compute distributed decision-making, increase the computational performance of the NCS. In distributed decision-making, agents consider a subset of all agents in their planning. Due to only local system knowledge of the agents, these local plans are potentially inconsistent with the local plans of other agents. Such an inconsistency may lead to the infeasibility of local plans. This thesis proposes an algorithm that utilizes synchronization methods to achieve consistency of local plans in distributed decision-making. The algorithm enables fast computations due to parallel decision-making and achieves feasible decisions. The parallel and iterative algorithm alternates two steps: local planning and global synchronization. In the local planning step, the agents parallelly compute local plans. Subsequently, consistency of the local plans across agents is achieved using global synchronization. The globally synchronized plans act as reference decisions for the local planning step in the next iteration. In each iteration, the local planning guarantees locally feasible plans, while the synchronization guarantees globally consistent plans. The parallel algorithm converges to globally feasible decisions if the coupling topology is feasible. This thesis introduces requirements for the coupling topology to achieve convergence to globally feasible decisions and proposes a centralized and a distributed method to generate coupling topologies that fulfill these requirements. The centralized coupling topology generation method uses its knowledge about all agents to generate time-invariant coupling topologies in a greedy manner. The distributed coupling topology generation method generates time-variant coupling topologies using game-theory. In order to demonstrate the distributed decision-making algorithm in experiments, this thesis proposes an architecture for networked control systems that achieves deterministic and reproducible experiments, even with non-deterministic computation and communication times. The Cyber-Physical Mobility Lab (CPM Lab), an open-source and remotely accessible platform for networked and autonomous vehicles, implements this architecture. Moreover, the CPM Lab provides a suitable interface for rapid prototyping with seamless simulations and experiments. This thesis demonstrates the complete pipeline from uncoupled agents to globally feasible solutions. The distributed decision-making uses a Model Predictive Control (MPC) framework. The evaluation of this thesis uses the CPM Lab as an evaluation platform to evaluate the Distributed MPC (DMPC) algorithm using the coupling topologies generated from the centralized and distributed generation methods. The evaluation shows that the proposed DMPC algorithm achieves feasible solutions while requiring lower computation times and lower communication demands than Centralized MPC (CMPC). The resulting trajectories show only small deviations from the globally optimal trajectories generated by CMPC.


  • Department of Computer Science [120000]
  • Chair of Computer Science 11 (Embedded Software) [122810]