DocumentCode :
157824
Title :
ACP based self-learning control for urban intersection
Author :
Feng Chen ; Lingyun Zhu ; Chuyue Han ; Gang Xiong
Author_Institution :
Univ. of Sci. & Technol. of China, Hefei, China
fYear :
2014
fDate :
8-10 Oct. 2014
Firstpage :
324
Lastpage :
328
Abstract :
The intersection models, such as delay models and queuing length models, are the foundations of optimal signal timing for urban intersection. Lack of the field data of intersection, it is highly difficult to calibrate parameters of the intersection models. Due to the effects of intersection topology, channelization and traffic conditions on these models, obviously it is impossible for single model to be suitable for optimal control of various intersections.
Keywords :
optimal control; road traffic control; self-adjusting systems; ACP; channelization; intersection topology; optimal control; optimal signal timing; self-learning control; traffic conditions; urban intersection; Computational modeling; Learning (artificial intelligence); Optical saturation; Queueing analysis; Silicon;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Service Operations and Logistics, and Informatics (SOLI), 2014 IEEE International Conference on
Conference_Location :
Qingdao
Type :
conf
DOI :
10.1109/SOLI.2014.6960744
Filename :
6960744
Link To Document :
بازگشت