Abstract

With an increasing number of vehicles on road the quantity of CO2 emissions and the amount of fuel wasted because of traffic congestion have been rising. Use of alternate means of transport that generate fewer emissions does not resolve the problem of congestions and vehicle wait time at traffic signal whereas further expansion of existing network of roads is not only constrained by finite space, but any network can get saturated as the number of vehicles increase. V2X technology allows vehicles and traffic infrastructure to communicate with each other, and could facilitate better use of existing resources by providing vehicles information about their surroundings and traffic signals. The information regarding the phase of traffic signal, vehicles’ position and vehicles’ speed can be used by drivers and autonomous vehicle control algorithms to make informed decisions as they approach traffic signals. This research proposes and analyzes system level impacts of implementing a coordination heuristic over single-vehicle optimization to realize the true potential of V2X technology. The results of this research can help policymakers choose the most suitable control strategy depending on the traffic conditions and the penetration rate of V2X technology. The analysis indicates that at 900 vehicles per hour for either of the two driving strategies: coordination heuristic or single-vehicle optimization, to be more preferred over baseline driver behavior, at least 50% of the vehicles should be V2X capable. Once a threshold penetration rate of V2X vehicles is achieved, vehicles following coordination heuristic generate nearly 10% fewer CO2 emissions than vehicles following baseline driver behavior, a 30% improvement over the reduction in CO2 emissions obtained using single-vehicle optimization. The vehicles following the coordination heuristic also have less travel time than vehicles following single-vehicle optimization, and less wait times than vehicles following baseline driver behavior.

Library of Congress Subject Headings

Vehicle-infrastructure integration; Vehicles--Automatic control; Intelligent transportation systems

Publication Date

1-2018

Document Type

Thesis

Student Type

Graduate

Degree Name

Industrial and Systems Engineering (MS)

Department, Program, or Center

Industrial and Systems Engineering (KGCOE)

Advisor

Katie McConky

Advisor/Committee Member

Michael E. Kuhl

Campus

RIT – Main Campus

Plan Codes

ISEE-MS

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