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A divide-and-conquer approach can be used to partition the problem and optimized separately, which leads to faster convergence. However, the lack of coordination among the partial solutions may yield a poor-quality global solution. In this paper, we propose a new method for simulation-based optimization of traffic signal control, called spatially iterative coordination for parallel optimization (SICPO), to improve coordination among the partial solutions and reduce synchronization between the partitioned regions. The traffic scenario is simulated to obtain the interactions, which is used to spatially decompose the scenario into regions and identify interdependencies between the regions. Based on the regions, the problem is divided into subproblems which are optimized separately. To coordinate between the subproblems, the interactions between partial solutions are synchronized in two ways. First, multiple iterations of the optimization process can be executed to coordinate the partial solutions at the end of each optimization process. Second, the partial solutions can also be coordinated among the regions by synchronizing the trips across the regions. To reduce computational complexity, parallelism can be applied on two levels: each region is optimized concurrently, and each solution for a region is evaluated in parallel. We demonstrate our method on a real-world road network of Singapore, where SICPO converges to an average travel time 21.6% faster than global optimization at 62.8\u00d7 shorter wall-clock time.<\/jats:p>","DOI":"10.1177\/00375497231159944","type":"journal-article","created":{"date-parts":[[2023,3,17]],"date-time":"2023-03-17T06:56:40Z","timestamp":1679036200000},"page":"539-556","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["Spatial iterative coordination for parallel simulation-based optimization of large-scale traffic signal control"],"prefix":"10.1177","volume":"101","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2204-0639","authenticated-orcid":false,"given":"Wen Jun","family":"Tan","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Nanyang Technological University (NTU), Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0211-7136","authenticated-orcid":false,"given":"Philipp","family":"Andelfinger","sequence":"additional","affiliation":[{"name":"Modeling and Simulation Group, Institute for Visual and Analytic Computing, Universit\u00e4t Rostock, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wentong","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Nanyang Technological University (NTU), Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Eckhoff","sequence":"additional","affiliation":[{"name":"MoVES (Mobility in Virtual Environments at Scale) laboratory, TUMCREATE Limited, Singapore"},{"name":"School of Computation, Information and Technology, Technical University of Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alois","family":"Knoll","sequence":"additional","affiliation":[{"name":"School of Computation, Information and Technology, Technical University of Munich, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2023,3,17]]},"reference":[{"key":"e_1_3_3_2_2","article-title":"Analysis of road network pattern considering population distribution and central business district","volume":"11","author":"Zhao F","year":"2016","unstructured":"Zhao F, Sun H, Wu J, et al. 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