An improved cellular automaton with axis information for microscopic traffic simulation. (May 2017)

• Record Type: Journal Article
• Authors: Ruan, Xin; Zhou, Junyong; Tu, Huizhao; Jin, Zeren; Shi, Xuefei
• Is Part Of: Transportation research. Volume 78(2017)
• Page Start: 63
• Page End: 77
• Publication Date: 2017-05
• Subjects: Bridge -- Traffic load -- Microsimulation -- Cellular automaton (CA) -- Weigh-in-motion (WIM) -- Multi-axle single-cell cellular automaton (MSCA); Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2017.02.023
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: An improved multi-axle single-cell cellular automaton (MSCA) is proposed. MSCA generates microscopic axle sequences for precise assessment. Time step and cell size that are fixed in STCA are user-defined in MSCA. MSCA is verified through traffic parameters and load effects based on WIM data. Abstract: Cellular Automaton (CA), an efficient dynamic modeling method that is widely used in traffic engineering, is newly introduced for traffic load modeling. This modeling method significantly addresses the modest traffic loads for long-span bridges. It does, however, require improvement to calculate precise load effects. This paper proposed an improved cellular automaton with axis information, defined as the Multi-axle Single-cell Cellular Automaton (MSCA), for the precise micro-simulation of random traffic loads on bridges. Four main ingredients of lattice, cells' states, neighborhoods and transition rules are redefined in MSCA to generate microscopic vehicle sequences with detailed vehicle axle positions, user-defined cell sizes and time steps. The simulation methodology of MSCA is then proposed. Finally, MSCA is carefully calibrated and validated using site-specific WIM data. The results indicate: (1) the relative errors (REs) for the traffic parameters, such as volumes, speeds, weights, and headways, from MSCA are basically no more than ±10% of those of WIM data; (2) the load effects of three typical influence lines (ILs) with varied lengths of 50, 200 and 1000 m are also confidently comparable, both of which validate the rationality and precision of MSCA. Furthermore, the accurate vehicle parameters and gaps generated from MSCA can be applied not only for precise traffic loading on infrastructures but also for the accurate estimation of vehicle dynamics and safety. Hence, wide application of MSCA can potentially be expected.