DocumentCode :
2251310
Title :
A decentralized adaptive traffic signal control using V2I communication data
Author :
Priemer, Christian ; Friedrich, Bernhard
Author_Institution :
Inst. of Transp. & Urban Eng., Tech. Univ. Braunschweig, Braunschweig, Germany
fYear :
2009
fDate :
4-7 Oct. 2009
Firstpage :
1
Lastpage :
6
Abstract :
A novel concept for a decentralized adaptive traffic signal control in urban networks using in future available vehicle to infratructure (V2I) communication data is presented. The phase-based strategy takes advantage of the improved detection data and optimizes each time interval of 5 seconds the phase sequence in order to reduce the total queue length within a forecast horizon of 20 seconds. For optimization the methods of dynamic programming and complete enumeration are used. The methods are embedded in the simulation environment of the microscopic traffic simulator AIMSUN NG. The market penetration level is the critical factor that impacts the quality of the new signal control. Hence, various penetration levels are modelled. For reference TRANSYT-7F is used.
Keywords :
dynamic programming; traffic control; traffic engineering computing; AIMSUN NG microscopic traffic simulator; TRANSYT-7F; decentralized adaptive traffic signal control; dynamic programming; market penetration level; phase-based strategy; urban networks; vehicle to infratructure communication data; Adaptive control; Communication system traffic control; Dynamic programming; Economic forecasting; Microscopy; Optimization methods; Phase detection; Programmable control; Traffic control; Vehicles; Traffic Signal Control; V2I communication; decentralized networks; dynamic programming; microscopic simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems, 2009. ITSC '09. 12th International IEEE Conference on
Conference_Location :
St. Louis, MO
Print_ISBN :
978-1-4244-5519-5
Electronic_ISBN :
978-1-4244-5520-1
Type :
conf
DOI :
10.1109/ITSC.2009.5309870
Filename :
5309870
Link To Document :
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