{"id":{"repo_id":"carleton","oai_identifier":"oai:carleton.scholaris.ca:20.500.14718/41887"},"canonical_url":"https://search.dev.ndltd.org/etd/carleton/oai:carleton.scholaris.ca:20.500.14718/41887","repository":{"repo_id":"carleton","name":"Carleton University","base_url":"https://carleton.scholaris.ca/server/oai/request"},"display":{"title":"Disaggregate Probabilistic Models to Predict Trip Generation Propensities and Mode Choice Behaviour","abstract":"Travel behaviour models serve as important tools to understand what factors affect trip generation and preferred mode of travel in different contexts. These models can be used to quantify the impacts and assess the consequences of development plans and policy actions. Growing populations and the increase in travel demand warrant investigation into determinants of travel behaviour that can guide policy changes and infrastructure investments. This thesis uses two cross-sectional datasets containing various socio-demographic and land-use attributes from 2015 and 2019. Trip-generation propensities for transit and automobile modes are predicted using a bivariate ordered probit approach which enables the determining of factors affecting the trip-generation propensity of each mode while establishing the correlation between their propensities. Further, a multinomial logit model is estimated to investigate the determinants of mode choice for home-based discretionary trips.","abstract_html":"Travel behaviour models serve as important tools to understand what factors affect trip generation and preferred mode of travel in different contexts. These models can be used to quantify the impacts and assess the consequences of development plans and policy actions. Growing populations and the increase in travel demand warrant investigation into determinants of travel behaviour that can guide policy changes and infrastructure investments. This thesis uses two cross-sectional datasets containing various socio-demographic and land-use attributes from 2015 and 2019. Trip-generation propensities for transit and automobile modes are predicted using a bivariate ordered probit approach which enables the determining of factors affecting the trip-generation propensity of each mode while establishing the correlation between their propensities. Further, a multinomial logit model is estimated to investigate the determinants of mode choice for home-based discretionary trips.","abstract_has_math":false,"creators":["Siddiqui, Abdul Basith"],"institution":"Carleton University","degree_name":"Master of Applied Science (M.App.Sc.)","degree_level":"Master's","degree_discipline":"Engineering, Civil","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022","date_published":"2022","updated_at":"2026-07-24T01:34:43Z","subjects":[],"languages":["en"],"rights":["Copyright © 2022 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner."],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.doi","label":"DOI","values":["10.22215/etd/2022-15011"],"render_values":[{"text":"10.22215/etd/2022-15011","href":"https://doi.org/10.22215/etd/2022-15011","code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/20.500.14718/41887","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Siddiqui, Abdul Basith"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-04-08T20:27:27Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2025-04-08T20:27:27Z"]},{"key":"dc:date.issued","label":"Date","values":["2022"]},{"key":"dc:publisher","label":"Institution","values":["Carleton University"]},{"key":"dc:type","label":"Dc Type","values":["thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering, Civil"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Master's"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Applied Science (M.App.Sc.)"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright © 2022 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["10.22215/etd/2022-15011"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/20.500.14718/41887"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Travel behaviour models serve as important tools to understand what factors affect trip generation and preferred mode of travel in different contexts. These models can be used to quantify the impacts and assess the consequences of development plans and policy actions. Growing populations and the increase in travel demand warrant investigation into determinants of travel behaviour that can guide policy changes and infrastructure investments. This thesis uses two cross-sectional datasets containing various socio-demographic and land-use attributes from 2015 and 2019. Trip-generation propensities for transit and automobile modes are predicted using a bivariate ordered probit approach which enables the determining of factors affecting the trip-generation propensity of each mode while establishing the correlation between their propensities. Further, a multinomial logit model is estimated to investigate the determinants of mode choice for home-based discretionary trips."]},{"key":"dc:title","label":"Title","values":["Disaggregate Probabilistic Models to Predict Trip Generation Propensities and Mode Choice Behaviour"]}]}],"canonical_facts":{"dc:creator":["Siddiqui, Abdul Basith"],"dc:date.accessioned":["2025-04-08T20:27:27Z"],"dc:date.available":["2025-04-08T20:27:27Z"],"dc:date.issued":["2022"],"dc:description.abstract":["Travel behaviour models serve as important tools to understand what factors affect trip generation and preferred mode of travel in different contexts. These models can be used to quantify the impacts and assess the consequences of development plans and policy actions. Growing populations and the increase in travel demand warrant investigation into determinants of travel behaviour that can guide policy changes and infrastructure investments. This thesis uses two cross-sectional datasets containing various socio-demographic and land-use attributes from 2015 and 2019. Trip-generation propensities for transit and automobile modes are predicted using a bivariate ordered probit approach which enables the determining of factors affecting the trip-generation propensity of each mode while establishing the correlation between their propensities. Further, a multinomial logit model is estimated to investigate the determinants of mode choice for home-based discretionary trips."],"dc:identifier.doi":["10.22215/etd/2022-15011"],"dc:identifier.uri":["https://hdl.handle.net/20.500.14718/41887"],"dc:language.iso":["en"],"dc:publisher":["Carleton University"],"dc:rights":["Copyright © 2022 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner."],"dc:title":["Disaggregate Probabilistic Models to Predict Trip Generation Propensities and Mode Choice Behaviour"],"dc:type":["thesis"],"thesis:degree_discipline":["Engineering, Civil"],"thesis:degree_level":["Master's"],"thesis:degree_name":["Master of Applied Science (M.App.Sc.)"]},"updated_at":"2026-07-24T01:34:43Z"}