Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Issue title: Special Section: Ambient advancements in intelligent computational sciences
Guest editors: Shailesh Tiwari, Munesh Trivedi and Mohan L. Kohle
Article type: Research Article
Authors: Giuffrè, Orazioa | Granà, Annaa; * | Tumminello, Maria Luisaa | Sferlazza, Antoninob
Affiliations: [a] Department of Civil, Environmental, Aerospace, and Material Engineering, Polytechnic School, University of Palermo, Palermo, Italy | [b] Department of Energy, Information Engineering and Mathematical Models, Polytechnic School, University of Palermo, Palermo, Italy
Correspondence: [*] Corresponding author. Anna Granà, Department of Civil, Environmental, Aerospace, and Material Engineering, Polytechnic School, University of Palermo, Italy, Viale delle Scienze, Ed 8, 90128 Palermo, Italy. Tel.: +39 09123899718; Fax: +39 091487568; E-mail: [email protected].
Abstract: The paper introduces a methodological approach based on genetic algorithms to calibrate microscopic traffic simulation models. The specific objective is to test an automated procedure utilizing genetic algorithms for assigning the most appropriate values to driver and vehicle parameters in AIMSUN. The genetic algorithm tool in MATLAB® and AIMSUN micro-simulation software were used. A subroutine in Python implemented the automatic interaction of AIMSUN with MATLAB®. Focus was made on two roundabouts selected as case studies. Empirical capacity functions based on summary random-effects estimates of critical headway and follow up headway derived from meta-analysis were used as reference for calibration purposes. Objective functions were defined and the difference between the empirical capacity functions and simulated data were minimized. Some model parameters in AIMSUN, which can significantly affect the simulation outputs, were selected. A better match to the empirical capacity functions was reached with the genetic algorithm-based approach compared with that obtained using the default parameters of AIMSUN. Overall, GA performs well and can be recommended for calibrating microscopic simulation models and solving further traffic management applications that practioners usually face using traffic microsimulation in their professional activities.
Keywords: Genetic algorithm, traffic microsimulation, AIMSUN, passenger car equivalent, roundabout
DOI: 10.3233/JIFS-169714
Journal: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 2, pp. 1791-1806, 2018
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]