Distributed Model Predictive Control for Intersection Automation Using a Parallelized Optimization Approach

Katriniok, Alexander; Kleibaum, Peter; Joševski, Martina

doi:10.1016/j.ifacol.2017.08.1492

Cited by 63 publications

(82 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the literature, most control concepts rely on a formulation in which collision avoidance is tightly related to the intersection scenario, that is, through time slots or collision points [2], [3], [7]. For AV motion control, it is desirable to utilize a single controller for multiple scenarios.…”

Section: A Main Contribution and Outlinementioning

confidence: 99%

“…For AV motion control, it is desirable to utilize a single controller for multiple scenarios. Therefore, we take a first step to generalize our problem formulation in [7] to be able to cover a wider range of use cases. Instead of using joint collision points along the agents' path coordinate, we propose to formulate collision avoidance in a Cartesian frame by mapping the agents' path coordinate to their respective global Cartesian coordinates.…”

Section: A Main Contribution and Outlinementioning

confidence: 99%

“…For crossing agents, we introduce time-invariant priorities on the agents that are determined once and held constant during the maneuver [7]. We define the bijective prioritization function γ : A → A, which assigns a unique priority to every agent -a lower value corresponds to a higher priority.…”

Section: A Local Agent Objectives and Constraintsmentioning

confidence: 99%

“…To guarantee collision avoidance in the distributed setting, the spatial preview of every agent i has to be of sufficient length while crossing the intersection, see [7]. Particularly, if Agent i has approached its BSR, i.e., s…”

Section: Minimum Spatial Previewmentioning

confidence: 99%

“…Instead of using time slots, collision avoidance is ensured by bounding distances between agents from below. In [7], the authors have outlined a fully distributed MPC scheme where every agent solves a nonconvex quadratically constrained QP (QCQP). Instead of utilizing time slots, agents must keep a minimum distance to each otherdefined with respect to their joint collision point.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Nonlinear Model Predictive Control for Distributed Motion Planning in Road Intersections Using PANOC

Katriniok

Sopasakis

Schuurmans

et al. 2019

2019 IEEE 58th Conference on Decision and Control (CDC)

Self Cite

View full text Add to dashboard Cite

The coordination of highly automated vehicles (or agents) in road intersections is an inherently nonconvex and challenging problem. In this paper, we propose a distributed motion planning scheme under reasonable vehicleto-vehicle communication requirements. Each agent solves a nonlinear model predictive control problem in real time and transmits its planned trajectory to other agents, which may have conflicting objectives. The problem formulation is augmented with conditional constraints that enable the agents to decide whether to wait at a stopping line, if safe crossing is not possible. The involved nonconvex problems are solved very efficiently using the proximal averaged Newton method for optimal control (PANOC). We demonstrate the efficiency of the proposed approach in a realistic intersection crossing scenario. A. Katriniok is with Ford Research

show abstract

Section: A Main Contribution and Outlinementioning

confidence: 99%

Section: A Main Contribution and Outlinementioning

confidence: 99%

Section: A Local Agent Objectives and Constraintsmentioning

confidence: 99%

Section: Minimum Spatial Previewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Nonlinear Model Predictive Control for Distributed Motion Planning in Road Intersections Using PANOC

Katriniok

Sopasakis

Schuurmans

et al. 2019

2019 IEEE 58th Conference on Decision and Control (CDC)

Self Cite

View full text Add to dashboard Cite

show abstract

Experimental validation of a semi‐distributed sequential quadratic programming method for optimal coordination of automated vehicles at intersections

Hult

Zanon

Frison

et al. 2020

Optim Control Appl Methods

View full text Add to dashboard Cite

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.

show abstract

Automation of Road Intersections Using Distributed Model Predictive Control

Katriniok

Kleibaum

Joševski

2018

Control Strategies for Advanced Driver Assistance Systems and Autonomous Driving Functions

View full text Add to dashboard Cite

Distributed Model Predictive Control for Intersection Automation Using a Parallelized Optimization Approach

Cited by 63 publications

References 17 publications

Nonlinear Model Predictive Control for Distributed Motion Planning in Road Intersections Using PANOC

Nonlinear Model Predictive Control for Distributed Motion Planning in Road Intersections Using PANOC

Experimental validation of a semi‐distributed sequential quadratic programming method for optimal coordination of automated vehicles at intersections

Automation of Road Intersections Using Distributed Model Predictive Control

Contact Info

Product

Resources

About