Traffic Simulation in Urban Networks Using Stochastic Cell Transmission Model. (3rd April 2017)

• Record Type: Journal Article
• Authors: Hadfi, Rafik; Tokuda, Sho; Ito, Takayuki
• Is Part Of: Computational intelligence. Volume 33:Number 4(2017)
• Page Start: 826
• Page End: 842
• Publication Date: 2017-04-03
• Subjects: agent simulation -- multiagent systems -- route search -- stochastic cell transmission model -- traffic simulation -- urban network; Artificial intelligence -- Periodicals; Computational linguistics -- Periodicals; 006.3
• DOI: 10.1111/coin.12115
• Languages: English
• ISSNs: 0824-7935

Abstract

Abstract : The stochastic cell transmission model (SCTM) is a macroscopic traffic simulation model of high accuracy. One of its advantages is that it can represent the uncertainty of the traffic states and the changing travel demand and supply conditions. However, it has been applied to freeways and simple networks having only one origin‐destination pair. In this article, we propose a modified stochastic cell transmission model (M‐SCTM) that applies the conventional SCTM to urban networks. In M‐SCTM, we introduce vehicle agents as well as their route choice behavior on an urban network, which is more applicable to complex urban networks. Additionally, M‐SCTM was applied to networks in which the turning ratio is not priorly set through a route search algorithm. The results show that M‐SCTM can conduct simulations with as much accuracy as SCTM. Furthermore, we verified the appropriate reproducibility of the simulations based on M‐SCTM and compared the estimated value and the measured value in terms of the travel time of each vehicle.