{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,26]],"date-time":"2026-09-26T04:49:59Z","timestamp":1790398199062,"version":"4.1.0"},"reference-count":30,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T00:00:00Z","timestamp":1685491200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004595","name":"Research University Team (RUTeam)","doi-asserted-by":"publisher","award":["1001\/PMATHS\/8580071"],"award-info":[{"award-number":["1001\/PMATHS\/8580071"]}],"id":[{"id":"10.13039\/501100004595","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Urbanised city transportation simulation needs a wide range of factors to reflect the influence of certain real-life events accurately. The vehicle composition and the timing of the traffic light signal scheduling play an important role in controlling the traffic flow and facilitate road users, particularly in densely populated urban cities. Since road capacity in urban cities changes throughout the day, an optimal traffic light signal duration might be different. Hence, in this paper, the effect of vehicle composition and traffic light phases on traffic flow during peak and off-peak hours in Georgetown, Penang, one of the highly populated cities in Malaysia, is investigated. Through Agent-Based Modelling (ABM), this complex system is simulated by integrating the driver\u2019s behaviour into the model using the GIS and Agent-Based Modelling Architecture (GAMA) simulation platform. The result of predicted traffic flow varies significantly depending on the vehicle composition while the duration of the traffic signal timing has little impact on traffic flow during peak hours. However, during off-peak hour, it is suggested that 20 s duration of green light provides the highest flow compared to 30 s and 40 s duration of green light. This concludes that the planning for traffic light phasing should consider multiple factors since the vehicle composition and traffic light timing for an effective traffic flow varies according to the volume of road users.<\/jats:p>","DOI":"10.3390\/ijgi12060226","type":"journal-article","created":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T02:12:45Z","timestamp":1685585565000},"page":"226","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Controlling Traffic Congestion in Urbanised City: A Framework Using Agent-Based Modelling and Simulation Approach"],"prefix":"10.3390","volume":"12","author":[{"given":"Raihanah Adawiyah","family":"Shaharuddin","sequence":"first","affiliation":[{"name":"School of Mathematical Sciences, Universiti Sains Malaysia, Gelugor 11800, Pulau Pinang, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7869-0345","authenticated-orcid":false,"given":"Md Yushalify","family":"Misro","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, Universiti Sains Malaysia, Gelugor 11800, Pulau Pinang, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"102613","DOI":"10.1016\/j.trc.2020.102613","article-title":"A multi-class urban traffic model considering heterogeneous vehicle composition: An extension of the s model","volume":"115","author":"Portilla","year":"2020","journal-title":"Transp. 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