{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/78611"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/78611","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Understanding and Modeling New Transportation Markets with Emerging Vehicle Technologies","abstract":"Ph.D.","abstract_html":"Ph.D.","abstract_has_math":false,"creators":["Zhang, Anpeng"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Kang, Jee Eun","Industrial and Systems Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-10-26T02:56:40Z","date_published":"2018-10-26T02:56:40Z","updated_at":"2026-07-27T19:05:12Z","subjects":["operations research","transportation"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/78611","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Kang, Jee Eun","Industrial and Systems Engineering"]},{"key":"dc:creator","label":"Author","values":["Zhang, Anpeng"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-10-26T02:56:40Z","2018","2018-08-10 04:32:29"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["operations research","transportation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/78611"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Ph.D.","Recent emerging vehicle technologies create new markets with new requirements for owning and operating these vehicles including battery electric vehicles (BEVs) and autonomous vehicles (AVs). BEVs with lower fuel consumption and emissions were successful in the automobile market in the past decade and continue to be. In order to support the growth of BEV market, understanding of feasibility and planning for charging infrastructure are necessary as BEVs are subjected to range limitations and charging opportunities. More recently, the potential deployment (or adoption) of AVs promises better utilization of fleet in addition to increased comfort and safety. This driver-less technology makes vehicle sharing easier and AVs may be co-owned among multiple people, creating a new form of ownership. This study provides insights on these new and growing transportation markets, focusing on the scenario analysis of BEV feasibility, parking-based charging infrastructure planning as well as modeling of AV co-ownership programs.In the first part of this work, a scenario analysis is designed to provide insights on feasibility and charging infrastructure requirements under different conditions. Multi-day activity-travel patterns are important in this work, since they help create potential vehicle usage profiles, including potential vehicle operations and battery charging status. However, multi-day travel data is usually not typically available. Thus, a sampling method is proposed to generate multi-day activity-travel patterns from readily available single-day household travel survey data, based on the observation that the distribution of interpersonal variability in single-day travel activity datasets is similar to the distribution of intrapersonal variability in multi-day datasets. Using the generated multi-day sample patterns, a scenario analysis for BEV feasibility is conducted based on the number of people covered with positive State-Of-Charge level.In addition, average number of chargers needed in different activity locations are derived to provide guidelines for parking-based charging infrastructure planning.The second part of this work investigates a new form of car sharing system that can be introduced in the market for AVs, called fractional ownership or co-ownership. Driver-less property of AVs enables co-owning a vehicle between users with compatible schedules. Thus, an AV can be shared by a group of users, which is only accessible by the group. Stable matching theory is considered in this work to help users find an appropriate group to share an AV and a generalized stable matching model is presented to allow flexible sizes of groups as well as various alternative objectives. A heuristic algorithm is developed to improve the computational time due to the combinatorial property of the problem."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Understanding and Modeling New Transportation Markets with Emerging Vehicle Technologies"]}]}],"canonical_facts":{"dc:contributor":["Kang, Jee Eun","Industrial and Systems Engineering"],"dc:creator":["Zhang, Anpeng"],"dc:date":["2018-10-26T02:56:40Z","2018","2018-08-10 04:32:29"],"dc:description":["Ph.D.","Recent emerging vehicle technologies create new markets with new requirements for owning and operating these vehicles including battery electric vehicles (BEVs) and autonomous vehicles (AVs). BEVs with lower fuel consumption and emissions were successful in the automobile market in the past decade and continue to be. In order to support the growth of BEV market, understanding of feasibility and planning for charging infrastructure are necessary as BEVs are subjected to range limitations and charging opportunities. More recently, the potential deployment (or adoption) of AVs promises better utilization of fleet in addition to increased comfort and safety. This driver-less technology makes vehicle sharing easier and AVs may be co-owned among multiple people, creating a new form of ownership. This study provides insights on these new and growing transportation markets, focusing on the scenario analysis of BEV feasibility, parking-based charging infrastructure planning as well as modeling of AV co-ownership programs.In the first part of this work, a scenario analysis is designed to provide insights on feasibility and charging infrastructure requirements under different conditions. Multi-day activity-travel patterns are important in this work, since they help create potential vehicle usage profiles, including potential vehicle operations and battery charging status. However, multi-day travel data is usually not typically available. Thus, a sampling method is proposed to generate multi-day activity-travel patterns from readily available single-day household travel survey data, based on the observation that the distribution of interpersonal variability in single-day travel activity datasets is similar to the distribution of intrapersonal variability in multi-day datasets. Using the generated multi-day sample patterns, a scenario analysis for BEV feasibility is conducted based on the number of people covered with positive State-Of-Charge level.In addition, average number of chargers needed in different activity locations are derived to provide guidelines for parking-based charging infrastructure planning.The second part of this work investigates a new form of car sharing system that can be introduced in the market for AVs, called fractional ownership or co-ownership. Driver-less property of AVs enables co-owning a vehicle between users with compatible schedules. Thus, an AV can be shared by a group of users, which is only accessible by the group. Stable matching theory is considered in this work to help users find an appropriate group to share an AV and a generalized stable matching model is presented to allow flexible sizes of groups as well as various alternative objectives. A heuristic algorithm is developed to improve the computational time due to the combinatorial property of the problem."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/78611"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["operations research","transportation"],"dc:title":["Understanding and Modeling New Transportation Markets with Emerging Vehicle Technologies"],"dc:type":["Text","Dissertation"]},"updated_at":"2026-07-27T19:05:12Z"}