DocumentCode :
2813253
Title :
An improved response surface methodology algorithm with an application to traffic signal optimization for urban networks
Author :
Joshi, Shirish S. ; Rathi, Ajay K. ; Tew, Jeffrey D.
Author_Institution :
Center for Transport. Anal., Oak Ridge Nat. Lab., TN, USA
fYear :
1995
fDate :
3-6 Dec 1995
Firstpage :
1104
Lastpage :
1109
Abstract :
Illustrates the use of the simulation-optimization technique of response surface methodology (RSM) in traffic signal optimization of urban networks. It also quantifies the gains of using the common random number (CRN) variance reduction strategy in such an optimization procedure. An enhanced RSM algorithm which employs conjugate gradient search techniques and successive second-order models is presented instead of the conventional approach. An illustrative example using an urban traffic network exhibits the superiority of using the CRN strategy over direct simulation in performing traffic signal optimization. The relative performance of the two strategies is quantified with computational results using the total network-wide delay as the measure of effectiveness
Keywords :
conjugate gradient methods; delays; digital simulation; optimisation; road traffic; search problems; signalling; traffic control; traffic engineering computing; common random number variance reduction strategy; conjugate gradient search techniques; effectiveness measure; relative performance; response surface methodology; simulation-optimization technique; successive second-order models; total network-wide delay; traffic signal optimization; urban traffic network; Computational modeling; Computer networks; Design for experiments; Laboratories; Optimization methods; Response surface methodology; Signal analysis; Telecommunication traffic; Traffic control; Transportation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Simulation Conference Proceedings, 1995. Winter
Conference_Location :
Arlington, VA
Print_ISBN :
0-78033018-8
Type :
conf
DOI :
10.1109/WSC.1995.478968
Filename :
478968
Link To Document :
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