Modeling gap acceptance at freeway merges

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. Thesis Supervisor: Moshe E. Ben-Akiva Title: Edmund K. Turner Professor of Civil and Environmental Engineering Acknowledgements I would like to thank my advisor Professor Moshe Ben-Akiva and Dr. Tomer Toledo. I could not continue to study here without their invaluable guidance, advice, support, and patience. I have learned lots of things in the coursework and in the research from them for two years. I am thankful to faculty members, especially Professor Nigel Wilson and Professor Joseph Sussman, in MST program for their dedication during the courses and their approach ways to solve transportation problems in the courses. I am also thankful to the staff in CEE for their kindness and encouragement. I especially thank to Leanne, Cynthia, and Jeanette. I thank to ITS lab mates: Rama, Yang, Maya, Varun, Vikrant, Vaibhav (called 3V), Anita, and Charisma for their friendship and help. I am especially thankful to NGSIM group and NGSIM project for the financial support. I am thankful to my class mates in MST program. Especially thank to Alex, Tzu-Ching, and Thierry for their friendship. I would like to thank Professor Ikki Kim in Hanyang University for his valuable advice and encouragement. Thank to faculty member in my undergraduate major. Thank my friends in Incheon, classmates in my college, HYU Transportation alumni studying in the U.S.A and Korean graduate students at MIT. I especially thank to my roommate, Kang Hyeun Ji, for his encouragement, advice, and haircut. Above all, I am grateful to my parents and sister in my sweet home, Korea, and grandmother in heaven for their endless love and support throughout my life. Lastly, I especially thank to my love, Hyunjoo.