@inproceedings{,
    author = {Salem, Sarah; Leonhardt, Axel},
    title = {Optimizing Traffic Adaptive Signal Control: A Multi-Objective Simulation-Based Approach for Enhanced Transportation Efficiency},
    editor = {},
    booktitle = {Proceedings of the 10th International Conference on Vehicle Technology and Intelligent Transport Systems VEHITS - Volume 1},
    series = {},
    journal = {},
    address = {},
    publisher = {SciTePress},
    edition = {},
    year = {2024},
    isbn = {978-989-758-703-0},
    volume = {},
    number =  {},
    pages = {344-351},
    url = {},
    doi = {10.5220/0012682100003702},
    keywords = {},
    abstract = {This research aims to improve traffic flow efficiency, reduce congestion, and enhance the overall performance of the transportation system for different road users, while keeping in mind the ease of implementation of the provided approach. That is achieved by optimizing the stage length parameter in the VAP files for VISSIM using ParMOO, a powerful optimization tool. The VAP files contain crucial information about traffic signal control logic, including signal timings, stage durations, and cycle lengths. The maximum stage length parameter within VAP files represents the maximum allowable time for a particular traffic signal stage before transitioning to the next stage. Optimizing this parameter can significantly impact traffic performance by reducing delays and improving overall traffic flow efficiency. Average delays for passenger cars and pedestrians are chosen as objective functions to be minimized. Sensitivity analysis is employed to validate the optimized solutions. Comparing the traffic performance measures using the optimized VAP files with the base case, we found that the optimized solutions consistently outperformed the observed performance. The research contributes by utilizing the ParMOO algorithm and integrating it within VISSIM software, enabling researchers to readily apply the methodology and advance the field of traffic signal control with practical and industry-relevant solutions.},
    note = {},
    institution = {Universität der Bundeswehr München, Fakultät für Bauingenieurwesen und Umweltwissenschaften, BAU 7 - Institut für Verkehrswesen und Raumplanung, Professur: Leonhardt, Axel},
    
    
}