DocumentCode :
1870753
Title :
Capability-Enhanced Microscopic Simulation with Real-time Traffic Signal Control
Author :
Fang, Fang Clara ; Elefteriadou, Lily
Author_Institution :
Univ. of Hartford, Hartford
fYear :
2007
fDate :
Sept. 30 2007-Oct. 3 2007
Firstpage :
308
Lastpage :
313
Abstract :
Application programming interface (API) is a feature to enhance traffic simulation model capabilities by allowing users to customize changes in simulation such as driver behaviors, ramp metering control strategies, and other ITS applications. This paper presented a method to develop an API in AIMSUN, a stochastic and microscopic simulation model, to evaluate a previously developed adaptive signal control algorithm, i.e., DP algorithm. The algorithm was coded in C++ by combing the functions and five routines available from the GETRAM extension module embedded in AIMSUN. The developed API created a dynamic link between the DP algorithm and the simulation environment. During simulation run time, the real-time traffic measurements provided by detectors in the network feed the DP algorithm that, after processing, made the decision of signal controls. These decisions were then transferred back to the simulated network, which emulated their operations through the signal controllers. The simulation results have exhibited that the DP algorithm is superior to other common off-line signal optimization tools to handle the demand fluctuations. This research has demonstrated the API function is a useful tool to assess external ITS applications when these innovative ides are not supported by the simulation program.
Keywords :
application program interfaces; automated highways; dynamic programming; stochastic processes; traffic control; DP algorithm; application programming interface; capability-enhanced microscopic simulation; dynamic programming; intelligent transport system; optimization tool; real-time traffic signal control; stochastic model; Adaptive control; Communication system traffic control; Detectors; Feeds; Microscopy; Programmable control; Signal processing; Stochastic processes; Time measurement; Traffic control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems Conference, 2007. ITSC 2007. IEEE
Conference_Location :
Seattle, WA
Print_ISBN :
978-1-4244-1396-6
Electronic_ISBN :
978-1-4244-1396-6
Type :
conf
DOI :
10.1109/ITSC.2007.4357794
Filename :
4357794
Link To Document :
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