Constrained Route Optimization With Fleet Considerations for Electrified Heavy-Duty Freight Vehicles
Date of Award:
8-2023
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Computer Science
Committee Chair(s)
Mario Harper
Committee
Mario Harper
Committee
Steve Petruzza
Committee
John Edwards
Abstract
Almost 75% of traffic-related emissions are caused by heavy-duty freight trucks and significantly impact neighborhoods, schools, and communities around shipping and distribution lines. With poor air quality and respiratory health, many children in at-risk and disadvantaged communities experience high rates of asthma, lower attendance in school, and lower concentration. This research creates to improve the impacts of heavy-duty electric freight by improving the route efficiency (in terms of energy, time, or route distance) of EV trucks. Our software and algorithms are tested in a simulation environment using data from several thousand fleet trucks operating in the Salt Lake City area. The software shows an anticipated energy reduction of ~ 6% to ~ 10% at the cost of ~ 3% increases in vehicle travel distance. Further, we anticipate positive health impacts in areas of dense trucking as we reduce the energy needs of electrification for fleet operators.
Checksum
0864ca02f343d9c621ac825da9a293fa
Recommended Citation
Shamma, Zarin Subah, "Constrained Route Optimization With Fleet Considerations for Electrified Heavy-Duty Freight Vehicles" (2023). All Graduate Theses and Dissertations, Spring 1920 to Summer 2023. 8835.
https://digitalcommons.usu.edu/etd/8835
Included in
Copyright for this work is retained by the student. If you have any questions regarding the inclusion of this work in the Digital Commons, please email us at .