{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/130231"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/130231","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Modeling lane-selection and lane-change frequency on congested urban freeways: empirical evidence from Chicago’s I-90/I-94 freeway","abstract":"Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01","abstract_html":"Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01","abstract_has_math":false,"creators":["Yousefi, Mahdi"],"institution":"University of Illinois Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Talebpour, Alireza"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-07-25","date_published":"2025-07-25","updated_at":"2026-07-22T22:25:06Z","subjects":["Lane-changing Behavior","Vehicle Trajectory Analysis","Multinomial Logit Modeling"],"languages":["en","eng"],"rights":["Copyright 2025 Mahdi Yousefi"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/130231","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Talebpour, Alireza"]},{"key":"dc:creator","label":"Author","values":["Yousefi, Mahdi"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-07-25","2025-08"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Lane-changing Behavior","Vehicle Trajectory Analysis","Multinomial Logit Modeling"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2025 Mahdi Yousefi"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/130231"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01","The student, Mahdi Yousefi, accepted the attached license on 2025-07-25 at 11:06.","The student, Mahdi Yousefi, submitted this Thesis for approval on 2025-07-25 at 11:07.","This Thesis was approved for publication on 2025-07-25 at 11:22.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22738 on 2025-10-25 at 15:54:39","Lane-changing behavior plays a significant role in traffic movement. It significantly impacts how well traffic flows, the safety of the roads, and the overall functioning of the system. This is a comprehensive study of lane-change behavior on a major urban freeway segment, focusing on vehicle trajectory data collected via aerial videography. The research utilized a 4-kilometer segment of the I-90/I-94 freeway in Chicago, Illinois, with data gathered during the afternoon using a helicopter-mounted camera at an altitude of 200 meters. The study aimed to uncover how traffic conditions, vehicle types, and segment-specific factors influence drivers’ lane choices. The data collection methodology involved tracking target vehicles over multiple trips using high-resolution video and extracting vehicle trajectories through a six-step process: image preprocessing, object detection, object tracking, image stabilization, trajectory construction, and data cleaning. The combination of RetinaNet and YOLOv5 models enabled the accurate detection and tracking of vehicles in both moving aerial and infrastructure-based video footage. Vehicle positions were stabilized using reference satellite imagery, feature-matching techniques (SIFT and FLANN), and homography transformations. The final trajectories were refined through Kalman filtering, manual ID stitching, and linear interpolation to ensure continuity across segments. The six-step extraction process provides detailed and reliable trajectory datasets, which are essential for analysis. The study explored the relationship between average speed and lane-change frequency using polynomial regression. Lane changes were most frequent at moderate average speeds around 14 kilometers per hour and decreased at both lower and higher average speed ranges. A third-degree polynomial model fit the data well, indicating that drivers change lanes most often during moderate congestion, as switching lanes helps them gain more speed. Similarly, a density-based analysis revealed that lane-change frequency increases sharply up to a critical density of 54 vehicles per kilometer per lane and then decreases as traffic becomes more congested. This pattern was also well captured by a third-degree polynomial, indicating that drivers change lanes more frequently at moderate traffic levels but do so less often in heavy traffic due to the limited availability of gaps. A joint analysis of density and average speed using contour maps revealed that lane changes peaked at 75 vehicles per kilometer per lane and 17.5 kilometers per hour. The analysis showed that lane changes vary by position along the freeway. Within the first 900 meters, most drivers shifted to the right to prepare for the I-94 exit. Beyond 900 meters, a multinomial logit lane-selection model is used, with density and average speed as predictors. This model estimated the probability of choosing each of six lanes and generated probability surfaces across the traffic state space. It confirmed that, accepted space gaps under 20 meters, while large vehicles preferred gaps of 20-50 meters and changed lanes more cautiously. These patterns reflect operational constraints such as braking distance and visibility. Time gap analysis showed that over 70% of all lane changes occurred when the available time gap was less than five seconds, with small vehicles making the majority of these quick maneuvers. The study also developed a multinomial logit lane-selection model using density and average speed as predictors. This model estimated the probability of choosing each of six lanes and generated probability surfaces across the traffic state space. It confirmed that in free-flow traffic, drivers prefer the outer lanes. The model's closed-form structure supports real-time traffic simulation and control. Key findings support the idea that lane-changing is a context-dependent behavior driven by traffic conditions, vehicle type, and upcoming route decisions. The modeling approach provides a practical tool for predicting lane-use patterns in real-time traffic management systems."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Modeling lane-selection and lane-change frequency on congested urban freeways: empirical evidence from Chicago’s I-90/I-94 freeway"]}]}],"canonical_facts":{"dc:contributor":["Talebpour, Alireza"],"dc:creator":["Yousefi, Mahdi"],"dc:date":["2025-07-25","2025-08"],"dc:description":["Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-08-01","The student, Mahdi Yousefi, accepted the attached license on 2025-07-25 at 11:06.","The student, Mahdi Yousefi, submitted this Thesis for approval on 2025-07-25 at 11:07.","This Thesis was approved for publication on 2025-07-25 at 11:22.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22738 on 2025-10-25 at 15:54:39","Lane-changing behavior plays a significant role in traffic movement. It significantly impacts how well traffic flows, the safety of the roads, and the overall functioning of the system. This is a comprehensive study of lane-change behavior on a major urban freeway segment, focusing on vehicle trajectory data collected via aerial videography. The research utilized a 4-kilometer segment of the I-90/I-94 freeway in Chicago, Illinois, with data gathered during the afternoon using a helicopter-mounted camera at an altitude of 200 meters. The study aimed to uncover how traffic conditions, vehicle types, and segment-specific factors influence drivers’ lane choices. The data collection methodology involved tracking target vehicles over multiple trips using high-resolution video and extracting vehicle trajectories through a six-step process: image preprocessing, object detection, object tracking, image stabilization, trajectory construction, and data cleaning. The combination of RetinaNet and YOLOv5 models enabled the accurate detection and tracking of vehicles in both moving aerial and infrastructure-based video footage. Vehicle positions were stabilized using reference satellite imagery, feature-matching techniques (SIFT and FLANN), and homography transformations. The final trajectories were refined through Kalman filtering, manual ID stitching, and linear interpolation to ensure continuity across segments. The six-step extraction process provides detailed and reliable trajectory datasets, which are essential for analysis. The study explored the relationship between average speed and lane-change frequency using polynomial regression. Lane changes were most frequent at moderate average speeds around 14 kilometers per hour and decreased at both lower and higher average speed ranges. A third-degree polynomial model fit the data well, indicating that drivers change lanes most often during moderate congestion, as switching lanes helps them gain more speed. Similarly, a density-based analysis revealed that lane-change frequency increases sharply up to a critical density of 54 vehicles per kilometer per lane and then decreases as traffic becomes more congested. This pattern was also well captured by a third-degree polynomial, indicating that drivers change lanes more frequently at moderate traffic levels but do so less often in heavy traffic due to the limited availability of gaps. A joint analysis of density and average speed using contour maps revealed that lane changes peaked at 75 vehicles per kilometer per lane and 17.5 kilometers per hour. The analysis showed that lane changes vary by position along the freeway. Within the first 900 meters, most drivers shifted to the right to prepare for the I-94 exit. Beyond 900 meters, a multinomial logit lane-selection model is used, with density and average speed as predictors. This model estimated the probability of choosing each of six lanes and generated probability surfaces across the traffic state space. It confirmed that, accepted space gaps under 20 meters, while large vehicles preferred gaps of 20-50 meters and changed lanes more cautiously. These patterns reflect operational constraints such as braking distance and visibility. Time gap analysis showed that over 70% of all lane changes occurred when the available time gap was less than five seconds, with small vehicles making the majority of these quick maneuvers. The study also developed a multinomial logit lane-selection model using density and average speed as predictors. This model estimated the probability of choosing each of six lanes and generated probability surfaces across the traffic state space. It confirmed that in free-flow traffic, drivers prefer the outer lanes. The model's closed-form structure supports real-time traffic simulation and control. Key findings support the idea that lane-changing is a context-dependent behavior driven by traffic conditions, vehicle type, and upcoming route decisions. The modeling approach provides a practical tool for predicting lane-use patterns in real-time traffic management systems."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/130231"],"dc:language":["en","eng"],"dc:rights":["Copyright 2025 Mahdi Yousefi"],"dc:subject":["Lane-changing Behavior","Vehicle Trajectory Analysis","Multinomial Logit Modeling"],"dc:title":["Modeling lane-selection and lane-change frequency on congested urban freeways: empirical evidence from Chicago’s I-90/I-94 freeway"],"dc:type":["text"],"thesis:degree_discipline":["Civil Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:06Z"}