Development and Testing of Optimized Autonomous and Connected Vehicle Trajectories at Signalized Intersections

Elefteriadou, Lily; Pourmehrab, Mahmoud; Emami, Patrick; Omidvar, Aschkan; Letter, Clark; Neal, Patrick; Kiriazis, Rebecca; Ranka, Sanjay; Crane, Carl; Ridgeway, Shannon; University of Florida. Transportation Institute

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Development and Testing of Optimized Autonomous and Connected Vehicle Trajectories at Signalized Intersections

2017-11-01
By Elefteriadou, Lily ; Pourmehrab, Mahmoud ; Emami, Patrick ; ...

[PDF-3.44 MB]

English

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Details:

Creators:

Elefteriadou, Lily ; Pourmehrab, Mahmoud ; Emami, Patrick ; Omidvar, Aschkan ; Letter, Clark ; ... More +

Elefteriadou, Lily ; Pourmehrab, Mahmoud ; Emami, Patrick ; Omidvar, Aschkan ; Letter, Clark ; Neal, Patrick ; Kiriazis, Rebecca ; Ranka, Sanjay ; Crane, Carl ; Ridgeway, Shannon Less -
Corporate Creators:

University of Florida. Transportation Institute
Corporate Contributors:

Florida. Dept. of Transportation
Subject/TRT Terms:

[+]

Algorithms Automated Vehicles Connected Vehicles Intelligent Vehicles Mobile Communication Systems Optimization Signal Control Signalized Intersections Testing Traffic Signal Control Systems Vehicle Design Vehicle Trajectories
Resource Type:

Tech Report
Geographical Coverage:

United States ; Florida

United States ; Florida Less -
TRIS Online Accession Number:

01655951
Edition:

Final Report (August 2015 - November 2017)
Corporate Publisher:

University of Florida. Transportation Institute ; Florida. Dept. of Transportation

University of Florida. Transportation Institute ; Florida. Dept. of Transportation Less -
NTL Classification:

NTL-INTELLIGENT TRANSPORTATION SYSTEMS-INTELLIGENT TRANSPORTATION SYSTEMS;NTL-OPERATIONS AND TRAFFIC CONTROLS-Traffic Control Devices;
Abstract:

Significant improvements in automated and connected vehicle technologies are expected to create a revolution in how we move and move things. Automated vehicles can operate using a variety of sensors such as GPS, lidar, radar, and smart cameras, as well as terrain information, and they have the ability to communicate with infrastructure as well as surrounding vehicles. The objectives of this research were to develop, test, and deploy an intelligent real-time intersection traffic control system in order to optimize simultaneously signal control and automated vehicle trajectories when the traffic stream consists of autonomous, connected, and conventional vehicles. The system developed was first simulated in MATLAB. Simulation showed that the proposed system can minimize the total travel time at an isolated intersection. The system developed was also tested at the Florida Department of Transportation’s Traffic Engineering Research Laboratory (FDOT TERL) facility. This report provides an overview of the hardware and software developed for the project, including a local server, DSRC (dedicated short range communications) receiver for the server, interface to the signal controller, sensor fusion system, radio communication software and hardware for vehicle to infrastructure communications. The system was tested under different scenarios. The outputs and video footage (http://avian.essie.ufl.edu/gallery/) showed that the system is capable of providing optimal trajectories to automated vehicles in order to reduce delays. Future work should expand the algorithm to consider congested conditions, lane changing within the communications range, and the presence of pedestrians and bicycles.
Format:

PDF
Funding:

FDOT Contract BDV31-977-45
Collection(s):

US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:b41f0f7531907e9bdfca482d91af65e4616a39ca274977fb0ea6d78427ad8f56
Download URL:

https://rosap.ntl.bts.gov/view/dot/36636/dot_36636_DS1.pdf
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Development and Testing of Optimized Autonomous and Connected Vehicle Trajectories at Signalized Intersections

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