A Fuzzy Logic-based lane changing model was developed for mandatory lane changes at lane drops. Genetic Algorithm was used for optimizing the widths of membership functions. The Next Generation Simulation (NGSIM) dataset of vehicle trajectories was used for model development and validation. The model performed better than a comparable binary Logit model in terms of predicting the merge and non-merge events. The model has applications in traffic simulation and driver assistance systems.
A genetic fuzzy system for modeling mandatory lane changing
01.09.2012
644102 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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