Polling-Systems-Based Autonomous Vehicle Coordination in Traffic Intersections With No Traffic Signals

As autonomous vehicle technology advances rapidly, the design and operation of networks composed of fully autonomous vehicles have attracted immense interest. It is widely anticipated that fully autonomous vehicle networks will drastically improve performance. In this paper, we consider a widely stu...

Full description

Saved in:
Bibliographic Details
Published inIEEE transactions on automatic control Vol. 65; no. 2; pp. 680 - 694
Main Authors Miculescu, David, Karaman, Sertac
Format Journal Article
LanguageEnglish
Published New York IEEE 01.02.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Online AccessGet full text
ISSN0018-9286
1558-2523
2334-3303
1558-2523
DOI10.1109/TAC.2019.2921659

Cover

More Information
Summary:As autonomous vehicle technology advances rapidly, the design and operation of networks composed of fully autonomous vehicles have attracted immense interest. It is widely anticipated that fully autonomous vehicle networks will drastically improve performance. In this paper, we consider a widely studied problem, in which autonomous vehicles arriving at an intersection adjust their speeds to traverse the intersection as rapidly as possible, while avoiding collisions. We propose a coordination control algorithm, assuming stochastic models for the arrival times of the vehicles. The proposed algorithm extends the widely studied polling systems analysis to the case involving customers subject to second-order differential constraints. We provide provable guarantees on 1) safety, no collisions occur surely, and 2) performance, rigorous bounds on the expected delay. We also provide a stability analysis for the resulting queueing system. We demonstrate the algorithm in an extensive simulation study, providing one to two orders of magnitude improvement in delays over the traditional traffic light.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0018-9286
1558-2523
2334-3303
1558-2523
DOI:10.1109/TAC.2019.2921659