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Ιδρυματικό Αποθετήριο [SANDBOX]
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
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| URI: | http://purl.tuc.gr/dl/dias/B36CF5D1-2B51-4BF0-8891-BBB79360CB31 | ||
| Έτος | 2011 | ||
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | ||
| Άδεια Χρήσης |
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| Βιβλιογραφική Αναφορά | A. Kouvelas, M. Papageorgiou, E.B. Kosmatopoulos, I. Papamichail, "A learning technique for deploying self-tuning traffic control systems," in 14th International IEEE Conference on Intelligent Transportation Systems, 2011, pp. 1646-1651. doi: 10.1109/ITSC.2011.6082968 https://doi.org/10.1109/ITSC.2011.6082968 | ||
| Εμφανίζεται στις Συλλογές |
Currently, a considerable amount of human effort and time is spent for initialization or calibration of operational traffic control systems. Typically, this optimization (fine-tuning) procedure is conducted manually, via trial-and-error, relying on expertise and human judgment and does not always lead to a desirable outcome. This paper presents a new learning/adaptive algorithm that enables automatic fine-tuning of general traffic control systems. The efficiency and online feasibility of the algorithm is investigated through extensive simulation experiments. The fine-tuning problem of three mutually-interacting control modules - each one with its distinct design parameters - of an urban traffic signal control strategy is thoroughly investigated. Simulation results indicate that the learning algorithm can provide efficient automatic fine-tuning, guaranteeing safe and convergent behavior.
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