## Details

Original language | English |
---|---|

Article number | 52 |

Journal | Algorithms |

Volume | 13 |

Issue number | 3 |

Publication status | Published - 28 Feb 2020 |

## Abstract

This paper considers nonlinear model predictive control for simultaneous path-following and collision avoidance of connected autonomous vehicles. For each agent, a nonlinear bicycle model is used to predict a sequence of the states and then optimize them with respect to a sequence of control inputs. The objective function of the optimal control problem is to follow the planned path which is represented by a Bezier curve. In order to achieve collision avoidance among the networked vehicles, a geometric shape must be selected to represent the vehicle geometry. In this paper, an elliptic disk is selected for that as it represents the geometry of the vehicle better than the traditional circular disk. A separation condition between each pair of elliptic disks is formulated as time-varying state constraints for the optimization problem. Driving corridors are assumed to be also Bezier curves, which could be obtained from digital maps, and are reformulated to suit the controller algorithm. The algorithm is validated using MATLAB simulation with the aid of ACADO toolkit.

## Keywords

- Autonomous driving, Nonlinear model predictive control, Optimization, Path following

## ASJC Scopus subject areas

- Mathematics(all)
**Theoretical Computer Science**- Mathematics(all)
**Numerical Analysis**- Computer Science(all)
**Computational Theory and Mathematics**- Mathematics(all)
**Computational Mathematics**

## Cite this

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- Harvard
- Apa
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- BibTeX
- RIS

**Predictive Path Following and Collision Avoidance of Autonomous Connected Vehicles.**/ Abdelaal, Mohamed; Schön, Steffen.

In: Algorithms, Vol. 13, No. 3, 52, 28.02.2020.

Research output: Contribution to journal › Article › Research › peer review

*Algorithms*, vol. 13, no. 3, 52. https://doi.org/10.3390/a13030052

*Algorithms*,

*13*(3), Article 52. https://doi.org/10.3390/a13030052

}

TY - JOUR

T1 - Predictive Path Following and Collision Avoidance of Autonomous Connected Vehicles

AU - Abdelaal, Mohamed

AU - Schön, Steffen

N1 - Funding information: This research was funded by the German Research Foundation (DFG) as a part of the Research Training Group Integrity and Collaboration in dynamic SENSor networks (i.c.sens) [GRK2159].

PY - 2020/2/28

Y1 - 2020/2/28

N2 - This paper considers nonlinear model predictive control for simultaneous path-following and collision avoidance of connected autonomous vehicles. For each agent, a nonlinear bicycle model is used to predict a sequence of the states and then optimize them with respect to a sequence of control inputs. The objective function of the optimal control problem is to follow the planned path which is represented by a Bezier curve. In order to achieve collision avoidance among the networked vehicles, a geometric shape must be selected to represent the vehicle geometry. In this paper, an elliptic disk is selected for that as it represents the geometry of the vehicle better than the traditional circular disk. A separation condition between each pair of elliptic disks is formulated as time-varying state constraints for the optimization problem. Driving corridors are assumed to be also Bezier curves, which could be obtained from digital maps, and are reformulated to suit the controller algorithm. The algorithm is validated using MATLAB simulation with the aid of ACADO toolkit.

AB - This paper considers nonlinear model predictive control for simultaneous path-following and collision avoidance of connected autonomous vehicles. For each agent, a nonlinear bicycle model is used to predict a sequence of the states and then optimize them with respect to a sequence of control inputs. The objective function of the optimal control problem is to follow the planned path which is represented by a Bezier curve. In order to achieve collision avoidance among the networked vehicles, a geometric shape must be selected to represent the vehicle geometry. In this paper, an elliptic disk is selected for that as it represents the geometry of the vehicle better than the traditional circular disk. A separation condition between each pair of elliptic disks is formulated as time-varying state constraints for the optimization problem. Driving corridors are assumed to be also Bezier curves, which could be obtained from digital maps, and are reformulated to suit the controller algorithm. The algorithm is validated using MATLAB simulation with the aid of ACADO toolkit.

KW - Autonomous driving

KW - Nonlinear model predictive control

KW - Optimization

KW - Path following

UR - http://www.scopus.com/inward/record.url?scp=85083495147&partnerID=8YFLogxK

U2 - 10.3390/a13030052

DO - 10.3390/a13030052

M3 - Article

AN - SCOPUS:85083495147

VL - 13

JO - Algorithms

JF - Algorithms

IS - 3

M1 - 52

ER -