2026-09-19T16:41:38Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/922282022-01-13T07:54:05Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Domitilla Del Vecchio.
Ahn, Heejin
Massachusetts Institute of Technology. Department of Mechanical Engineering.
Massachusetts Institute of Technology. Department of Mechanical Engineering
2014-12-08T18:57:56Z
2014-12-08T18:57:56Z
2014
2014
http://hdl.handle.net/1721.1/92228
897472128
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 79-80).
This paper describes the design of a supervisory controller (supervisor) that manages multiple heterogeneous vehicles, i.e., multiple controlled and uncontrolled vehicles, to avoid intersection collisions. Two main problems are addressed: verification of the safety of all vehicles at an intersection, and management of the inputs of controlled vehicles. For the verification problem, we employ an inserted idle-time scheduling approach, where the "inserted idle-time" is a time interval when the intersection is deliberately held idle for uncontrolled vehicles to safely cross the intersection. For the management problem, we design a supervisor that is least restrictive in the sense that it overrides controlled vehicles only when a safety violation becomes imminent. We analyze computational complexity and propose an efficient version of the supervisor with a quantified approximation bound. To mitigate the abrupt changes of control inputs and to reduce the number of unnecessary interventions, we additionally design two optimization problems and provide the supervisor with a more conservative bound.
by Heejin Ahn.
S.M.
80 pages
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Mechanical Engineering.
Semi-autonomous control of multiple heterogeneous vehicles for intersection collision avoidance
Thesis
application/pdf
false
Publication
unknown
unknown
<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="a7de605a-c007-45cd-ae5b-c33658e504c2">
<Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type>
<Language>eng</Language>
<Title>Semi-autonomous control of multiple heterogeneous vehicles for intersection collision avoidance</Title>
<PublishedIn>
<Publication>
</Publication>
</PublishedIn>
<PublicationDate>2014</PublicationDate>
<Authors>
<Author>
<DisplayName>Ahn, Heejin</DisplayName>
<Affiliation>
<OrgUnit>
</OrgUnit>
</Affiliation>
</Author>
</Authors>
<Editors>
</Editors>
<Publishers>
<Publisher>
<DisplayName>Massachusetts Institute of Technology</DisplayName>
<OrgUnit />
</Publisher>
</Publishers>
<License>http://dspace.mit.edu/handle/1721.1/7582</License>
<Keyword>Mechanical Engineering.</Keyword>
<Abstract>This paper describes the design of a supervisory controller (supervisor) that manages multiple heterogeneous vehicles, i.e., multiple controlled and uncontrolled vehicles, to avoid intersection collisions. Two main problems are addressed: verification of the safety of all vehicles at an intersection, and management of the inputs of controlled vehicles. For the verification problem, we employ an inserted idle-time scheduling approach, where the "inserted idle-time" is a time interval when the intersection is deliberately held idle for uncontrolled vehicles to safely cross the intersection. For the management problem, we design a supervisor that is least restrictive in the sense that it overrides controlled vehicles only when a safety violation becomes imminent. We analyze computational complexity and propose an efficient version of the supervisor with a quantified approximation bound. To mitigate the abrupt changes of control inputs and to reduce the number of unnecessary interventions, we additionally design two optimization problems and provide the supervisor with a more conservative bound.</Abstract>
<Access xmlns="http://purl.org/coar/access_right"
>
</Access>
</Publication>