2026-09-19T03:43:40Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/346072022-01-13T07:54:23Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Moshe E. Ben-Akiva.
Lee, Gunwoo
Massachusetts Institute of Technology. Dept. of Civil and Environmental Engineering.
Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
2006-11-07T13:34:08Z
2006-11-07T13:34:08Z
2006
2006
http://hdl.handle.net/1721.1/34607
71301166
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2006.
Includes bibliographical references (p. 103-105).
This thesis develops a merging model that captures the gap acceptance behavior of drivers that merge from a ramp into a congested freeway. Merging can be classified into three types: normal, forced and cooperative lane changing. The developed merging model uses a single critical gap function, which incorporates explanatory variables that capture all three types of merging behavior. Thus, the model combines all three types in a single model. The merging gap acceptance model is estimated using the maximum likelihood method with detailed trajectory data that was collected on two freeway sections in California. Estimation results show that the merging gap acceptance model is affected by traffic conditions such as average speed in the mainline, interactions with lead and lag vehicles, and urgency of the merge. Transferability tests for the stability of the model parameters between the two datasets are conducted. The single level gap acceptance model is implemented and compared with an existing gap acceptance model in the microscopic traffic simulation model, MITSIMLab. The results show that the proposed model is better than the existing gap acceptance model.
by Gunwoo Lee.
S.M.
105 p.
3987482 bytes
3993185 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Civil and Environmental Engineering.
Modeling gap acceptance at freeway merges
Thesis
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Publication
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<Abstract>This thesis develops a merging model that captures the gap acceptance behavior of drivers that merge from a ramp into a congested freeway. Merging can be classified into three types: normal, forced and cooperative lane changing. The developed merging model uses a single critical gap function, which incorporates explanatory variables that capture all three types of merging behavior. Thus, the model combines all three types in a single model. The merging gap acceptance model is estimated using the maximum likelihood method with detailed trajectory data that was collected on two freeway sections in California. Estimation results show that the merging gap acceptance model is affected by traffic conditions such as average speed in the mainline, interactions with lead and lag vehicles, and urgency of the merge. Transferability tests for the stability of the model parameters between the two datasets are conducted. The single level gap acceptance model is implemented and compared with an existing gap acceptance model in the microscopic traffic simulation model, MITSIMLab. The results show that the proposed model is better than the existing gap acceptance model.</Abstract>
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