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SPACE-TIME GRAPH-BASED VEHICULAR TRAJECTORY PLANNER: AN AUTONOMOUS INTERSECTION MANAGEMENT SYSTEM

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Date Issued:
2024
Abstract/Description:
Every passenger vehicle must rely on a safe and optimal trajectory to eliminate traffic incidents and congestion as well as to reduce environmental impact, and travel time. Autonomous intersection management systems (AIMS) enable large scale optimization of vehicular trajectories with connected and autonomous vehicles (CAVs). The first contribution of this dissertation is the fastest trajectory planner (FTP) method which is geared for computing the fastest waypoint trajectories via performing graph search over a discretized space-time (ST) graph (Gt), thereby constructing collision-free space-time trajectories with variable vehicular speeds adhering to traffic rules and dynamical constraints of vehicles. The benefits of navigating a connected and autonomous vehicle (CAV) truly capture effective collaboration between every CAV during the trajectory planning step. This requires addressing trajectory planning activity along with vehicular networking in the design phase. For complementing the proposed FTP method in decentralized scenarios, the second contribution of this dissertation is an application layer V2V solution using a coordinator-based distributed trajectory planning method which elects a single leader CAV among all the collaborating CAVs without requiring a centralized infrastructure. The leader vehicular agent calculates and assigns a trajectory for each node CAV over the vehicular network for the collision-free management of an unsignalized road intersection. The proposed FTP method is tested in a simulated road intersection scenario for carrying out trials on scheduling efficiency and algorithm runtime. The resulting trajectories allow high levels of intersection sharing, high evacuation rate, with a low algorithm single-threaded runtime figures even with large scenarios of up to 1200 vehicles, surpassing comparable systems.
Title: SPACE-TIME GRAPH-BASED VEHICULAR TRAJECTORY PLANNER: AN AUTONOMOUS INTERSECTION MANAGEMENT SYSTEM.
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Name(s): Mutlu, Caner , author
Cardei, Ionut , Thesis advisor
Florida Atlantic University, Degree grantor
Department of Computer and Electrical Engineering and Computer Science
College of Engineering and Computer Science
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Date Created: 2024
Date Issued: 2024
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 148 p.
Language(s): English
Abstract/Description: Every passenger vehicle must rely on a safe and optimal trajectory to eliminate traffic incidents and congestion as well as to reduce environmental impact, and travel time. Autonomous intersection management systems (AIMS) enable large scale optimization of vehicular trajectories with connected and autonomous vehicles (CAVs). The first contribution of this dissertation is the fastest trajectory planner (FTP) method which is geared for computing the fastest waypoint trajectories via performing graph search over a discretized space-time (ST) graph (Gt), thereby constructing collision-free space-time trajectories with variable vehicular speeds adhering to traffic rules and dynamical constraints of vehicles. The benefits of navigating a connected and autonomous vehicle (CAV) truly capture effective collaboration between every CAV during the trajectory planning step. This requires addressing trajectory planning activity along with vehicular networking in the design phase. For complementing the proposed FTP method in decentralized scenarios, the second contribution of this dissertation is an application layer V2V solution using a coordinator-based distributed trajectory planning method which elects a single leader CAV among all the collaborating CAVs without requiring a centralized infrastructure. The leader vehicular agent calculates and assigns a trajectory for each node CAV over the vehicular network for the collision-free management of an unsignalized road intersection. The proposed FTP method is tested in a simulated road intersection scenario for carrying out trials on scheduling efficiency and algorithm runtime. The resulting trajectories allow high levels of intersection sharing, high evacuation rate, with a low algorithm single-threaded runtime figures even with large scenarios of up to 1200 vehicles, surpassing comparable systems.
Identifier: FA00014539 (IID)
Degree granted: Dissertation (PhD)--Florida Atlantic University, 2024.
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): Includes bibliography.
Subject(s): Autonomous vehicles
Computer engineering
Transportation
Persistent Link to This Record: http://purl.flvc.org/fau/fd/FA00014539
Use and Reproduction: Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
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Host Institution: FAU