Abstract
SummaryIn this article, we study the optimal coordination of automated vehicles at intersections. The problem can be stated as an optimal control problem (OCP), which can be decomposed as a bi‐level scheme composed by one nonlinear program (NLP) which schedules the access to the intersection and one OCP per vehicle which computes the appropriate vehicle commands. We discuss a practical implementation of the bi‐level controller where the NLP is solved with a tailored semi‐distributed sequential quadratic programming (SQP) algorithm that enables distribution of most computation to the vehicles. Results from an extensive experimental campaign are presented, where the bi‐level controller and the semi‐distributed SQP are implemented on a test setup consisting of three automated vehicles. In particular, we show that the vehicle‐level controller can enforce the scheduled intersection access beyond the accuracy admitted by the sensor system, and that the bi‐level controller can handle large perturbations and large communication delays, which makes the scheme applicable in practical scenarios. Finally, the use of wireless communication introduces delays in the outer control loop. To allow faster feedback, we introduce a real‐time iteration (RTI) like variation of the bi‐level controller. Experimental and simulated results indicate that the RTI‐like variation offers comparable performance using less computation and communication.
Highlights
The current trend toward automation of road vehicles can be expected to continue, and eventually most vehicles will be fully automated and communicating
Most importantly, such controllers must be able to guarantee that no collisions occur, and in particular, the guarantees must be applicable to scenarios with uncertainty
We proposed a semi-distributed sequential quadratic programming (SQP) approach for the solution of the time-slot nonlinear program (NLP).[26]
Summary
The current trend toward automation of road vehicles can be expected to continue, and eventually most vehicles will be fully automated and communicating This technology can be leveraged to obtain synergistic effects through cooperation between the automated vehicles, and thereby enable drastic improvements to the traffic system. There are several challenges that must be addressed before coordination algorithms can be applied in practice Most importantly, such controllers must be able to guarantee that no collisions occur, and in particular, the guarantees must be applicable to scenarios with uncertainty. This includes handling unexpected events and the online recoordination of vehicles in the presence of new information. A practically useful coordination algorithm must scale well in terms of both how often communication is required and the data volumes involved
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