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Local ramp metering with distant downstream bottlenecks: a comparative study

Wang Yibing, Kan Yuheng, Papageorgiou Markos, Papamichail Ioannis

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/9A613301-0261-49EC-85C0-1B6C7A3F01FD
Έτος 2014
Τύπος Πλήρης Δημοσίευση σε Συνέδριο
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά Y. Wang, Y. Kan, M. Papageorgiou, I. Papamichail, "Local ramp metering with distant downstream bottlenecks: a comparative study," in 17th International IEEE Conference on Intelligent Transportation Systems (ITSC 2014), Qingdao, China, 8-11 October 2014, pp. 768-773. https://doi.org/10.1109/ITSC.2014.6957782
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Περίληψη

The well-known feedback ramp metering algorithm ALINEA can be applied for local ramp metering or included as a key component in a coordinated ramp metering system. ALINEA uses real-time occupancy measurements from the ramp flow merging area that may be at most few hundred meters downstream of the metered on-ramp nose. In many practical cases, however, bottlenecks with smaller capacity than the merging area may exist further downstream for various reasons, which suggests using measurements from those further downstream bottlenecks. Recent theoretical and simulation studies indicate that ALINEA may lead to a poorly damped closed-loop behavior in this case, but PI-ALINEA, a suitable Proportional-Integral (PI) extension of ALINEA, can lead to satisfactory control performance. This paper addresses the same local ramp-metering problem in the presence of downstream bottlenecks, with a particular focus on the general capacity of PI-ALINEA with three distinct types of bottleneck that may often be encountered in practice, i.e. (1) an uphill case; (2) a lane-drop case; (3) an un-controlled on-ramp case. Extensive simulation studies are conducted using a macroscopic traffic flow model to demonstrate that the performance of ALINEA indeed deteriorates in each of these bottleneck cases,while significant improvement is obtained using PI-ALINEA in all cases. Moreover, with its control parameters appropriately tuned beforehand, PI-ALINEA is found to be universally applicable, with little fine-tuning required for field applications.

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