{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/78068"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/78068","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Household Use of Emerging Vehicle Technologies: Modeling Framework and Traveler Adaptation","abstract":"Ph.D.","abstract_html":"Ph.D.","abstract_has_math":false,"creators":["Khayati, Yashar"],"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":"2018-06-28T20:33:34Z","date_published":"2018-06-28T20:33:34Z","updated_at":"2026-07-27T19:05:07Z","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/10477/78068","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":["Khayati, Yashar"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-06-28T20:33:34Z","2018","2018-05-17 13:30:14"]},{"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/10477/78068"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Ph.D.","This dissertation introduces a new framework to assess people’s travel behavior using vehicles with new technologies at the household level. All new technologies introduce new risks and benefits, therefore, this research addresses some concerns on the impact of the new features of Battery Electric Vehicles (BEVs), Autonomous Vehicles (AVs) and Shared Autonomous Vehicles (SAVs) on household members’ travel decisions. Some insights are also provided for policy makers on the best practices of using BEVs, AVs and SAVs. The first part of this study develops a model to simulate household members’ behavioral changes while they replace their regular vehicles with BEVs. Aside from BEVs advantages, BEVs have some limitations such as range and charging rate. A new mixed integer pro-gram, Household Activity Pattern Problem with Electric Vehicles (HAPPEV), is developed to generate feasible activity patterns for household members where they use regular vehicles and/or BEVs to satisfy their travel demands. The mathematical program considers spatial, temporal and vehicle related constraints in addition to intra-household interactions. A novel 3-stage Activity Insertion Heuristic is proposed to solve the NP-hard HAPPEV. The heuris-tic makes a large improvement in solution time and quality. Four scenarios with different flexibility levels on schedule, activity and vehicle assignment are designed to analyze their impact on travel decisions. All four scenarios are applied to households which are randomly selected from a travel survey. Sensitivity analysis is also performed on BEV range, charging opportunity and electricity price. Finally, some practical suggestions on more efficient usage of BEVs are made. The second part of this research explores the household use of AVs. The self-driving at-tribute makes AVs able to pick-up and drop-off passengers, be flexible with parking availabil-ity, driving empty, etc. Therefore, a new mixed integer model, Household Activity Pattern Problem with Autonomous Vehicles (HAPPAV), is developed to simulate household mem-bers travel behavior using AVs. The model assigns daily activities to household members and routes AVs to make the required trips. The HAPPAV is an NP-hard problem which takes commercial solvers several days to solve real-world size problems. A decomposition method is developed to optimally solve HAPPAV instances which improves the solution time substantially. A scenario of replacing regular vehicles with only one AV is also tested on 300 households. The travel metrics and the proposed method’s performance is reported as well. Finally, this dissertation extends the HAPPAV model to incorporate using SAVs by households. The HAPPAV model is modified, Household Activity Pattern Problem with Shared Autonomous Vehicles (HAPPSAV), to generate feasible activity patterns for house-hold members where they can use a mix of AVs and SAVs. SAVs can be used to cover all or part of the required daily trips. Since, self-driving may affect SAV cost, a scenario based analysis is conducted to assess travel decision changes. The scenarios cover different SAV availability cases and AV/SAV costs. The scenarios are applied to a sample of households from a travel survey by HAPPSAV. Some important travel metrics such as activity pattern feasibility, household’s total travel disutility, travel mode VMT and AV-SAV trip coverage are reported to help policy makers find better AV-SAV adoption practices."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Household Use of Emerging Vehicle Technologies: Modeling Framework and Traveler Adaptation"]}]}],"canonical_facts":{"dc:contributor":["Kang, Jee Eun","Industrial and Systems Engineering"],"dc:creator":["Khayati, Yashar"],"dc:date":["2018-06-28T20:33:34Z","2018","2018-05-17 13:30:14"],"dc:description":["Ph.D.","This dissertation introduces a new framework to assess people’s travel behavior using vehicles with new technologies at the household level. All new technologies introduce new risks and benefits, therefore, this research addresses some concerns on the impact of the new features of Battery Electric Vehicles (BEVs), Autonomous Vehicles (AVs) and Shared Autonomous Vehicles (SAVs) on household members’ travel decisions. Some insights are also provided for policy makers on the best practices of using BEVs, AVs and SAVs. The first part of this study develops a model to simulate household members’ behavioral changes while they replace their regular vehicles with BEVs. Aside from BEVs advantages, BEVs have some limitations such as range and charging rate. A new mixed integer pro-gram, Household Activity Pattern Problem with Electric Vehicles (HAPPEV), is developed to generate feasible activity patterns for household members where they use regular vehicles and/or BEVs to satisfy their travel demands. The mathematical program considers spatial, temporal and vehicle related constraints in addition to intra-household interactions. A novel 3-stage Activity Insertion Heuristic is proposed to solve the NP-hard HAPPEV. The heuris-tic makes a large improvement in solution time and quality. Four scenarios with different flexibility levels on schedule, activity and vehicle assignment are designed to analyze their impact on travel decisions. All four scenarios are applied to households which are randomly selected from a travel survey. Sensitivity analysis is also performed on BEV range, charging opportunity and electricity price. Finally, some practical suggestions on more efficient usage of BEVs are made. The second part of this research explores the household use of AVs. The self-driving at-tribute makes AVs able to pick-up and drop-off passengers, be flexible with parking availabil-ity, driving empty, etc. Therefore, a new mixed integer model, Household Activity Pattern Problem with Autonomous Vehicles (HAPPAV), is developed to simulate household mem-bers travel behavior using AVs. The model assigns daily activities to household members and routes AVs to make the required trips. The HAPPAV is an NP-hard problem which takes commercial solvers several days to solve real-world size problems. A decomposition method is developed to optimally solve HAPPAV instances which improves the solution time substantially. A scenario of replacing regular vehicles with only one AV is also tested on 300 households. The travel metrics and the proposed method’s performance is reported as well. Finally, this dissertation extends the HAPPAV model to incorporate using SAVs by households. The HAPPAV model is modified, Household Activity Pattern Problem with Shared Autonomous Vehicles (HAPPSAV), to generate feasible activity patterns for house-hold members where they can use a mix of AVs and SAVs. SAVs can be used to cover all or part of the required daily trips. Since, self-driving may affect SAV cost, a scenario based analysis is conducted to assess travel decision changes. The scenarios cover different SAV availability cases and AV/SAV costs. The scenarios are applied to a sample of households from a travel survey by HAPPSAV. Some important travel metrics such as activity pattern feasibility, household’s total travel disutility, travel mode VMT and AV-SAV trip coverage are reported to help policy makers find better AV-SAV adoption practices."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/78068"],"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":["Household Use of Emerging Vehicle Technologies: Modeling Framework and Traveler Adaptation"],"dc:type":["Text","Dissertation"]},"updated_at":"2026-07-27T19:05:07Z"}