Traffic Control with Connected Vehicle Routes in SURTRAC - Robotics Institute Carnegie Mellon University

Traffic Control with Connected Vehicle Routes in SURTRAC

Master's Thesis, Tech. Report, CMU-RI-TR-16-20, Robotics Institute, Carnegie Mellon University, May, 2016

Abstract

Connected vehicles are entering the market, but will not form the vast majority of all vehicles for a few decades. Traffic control that relies on information from connected vehicles (CVs) is thus challenging because it must cope with the current low market penetration rate of CVs. I devise a method to extend Surtrac, an existing distributed traffic controller, to incorporate CV information in the form of routes. Vehicle routes are converted to arrival times for all waypoint intersections, and then incorporated into Surtrac’s optimization. This method, when tested on a 36-intersection 1-way grid, improves vehicle delay by 25% for CVs at low penetration rates and by 37% when all vehicles are connected. The method also benefits non-CVs, even when nearly all other vehicles are connected. Results are also given for a 23-intersection area of Pittsburgh, where a comparison is made between this method, Surtrac, and existing well-tuned fixed timings. The extension of Surtrac to use CV routes improves traffic at all penetration rates, and provides motivation for early adoption of a route-sending system.

BibTeX

@mastersthesis{Hawkes-2016-5521,
author = {Allen Hawkes},
title = {Traffic Control with Connected Vehicle Routes in SURTRAC},
year = {2016},
month = {May},
school = {Carnegie Mellon University},
address = {Pittsburgh, PA},
number = {CMU-RI-TR-16-20},
}