YEN-HSIANG CHENHartono, Michael FranciudiMichael FranciudiHartono2024-03-132024-03-132023-01-01979835036966308917736https://scholars.lib.ntu.edu.tw/handle/123456789/640840The recent advancement in hardware computation speed has allowed stochastic microscopic traffic simulators to be embedded in signal optimization systems. In this study, stochastic perturbation simulation approximations (SPSA), an efficient difference-typed gradient-based searching, has been applied in the signal solver of a signal optimization system due to (i) its lower required total number of replications and (ii) the capability to conduct a variance reduction technique (VRT). The case study has shown that the objective value, in terms of road users' delay, indeed improves over iterations. Since the gradient-based method may be trapped in a local optimum, this study has further applied the shotgun mechanism that provides better solutions in the subject stage to proceed to the next stage. By offering the shotgun process, the quality of the solution can be further improved.[SDGs]SDG11conference paper10.1109/WSC60868.2023.104078632-s2.0-85185376327https://api.elsevier.com/content/abstract/scopus_id/85185376327