Fuzzy sets and systems for a motorway microscopic simulation model

• Published in: Fuzzy sets and systems Vol. 116; no. 1; pp. 65 - 76
• Main Authors: Wu, Jianping, Brackstone, Mark, McDonald, Mike
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Amsterdam Elsevier B.V 16-11-2000; Elsevier
• Subjects: Applied sciences; Engineering; Exact sciences and technology; Flows in networks. Combinatorial problems; General logic; Logic and foundations; Mathematical logic, foundations, set theory; Mathematical programming; Mathematics; Modelling; Operational research and scientific management; Operational research. Management science; Sciences and techniques of general use; Set theory; Transportation; Engineering; Transportation; Modelling; Validation; Operations research; Fuzzy system; Probabilistic approach; Network flow; Highway; Fuzzy programming; Calibration; Management; Fuzzy set; Modeling; Intelligent vehicule highway system; Simulation; Models; Fuzzy logic motorway simulation model; Mathematical programming
• DOI: 10.1016/S0165-0114(99)00038-X
• EISSN: 1872-6801
• ISSN: 0165-0114

Microscopic simulation modelling has recently become attractive to researchers in traffic engineering as it appears to offer a cost effective and ‘safe’ way of investigating intelligent vehicle-highway system (IVHS) at a fundamental level. However, the deterministic approach used assumes a consistency of behaviour which may severely detract from model validity. This may be overcome by using a ‘fuzzy’ approach to describe drivers’ decisions. This paper describes the development of the fuzzy logic motorway simulation model (FLOWSIM). Emphasis is placed on the research undertaken to establish fuzzy sets and systems for motorway driving behaviour models, the collection of data on appropriate motorway driving behaviour, fuzzy sets and systems calibration, and model validation. Model validation results have shown that the fuzzy model (FLOWSIM) can closely replicate real systems and in test cases have performed better than some common deterministic models such as the ‘GHR’, ‘Gipps’ and ‘MISSION’ models.