|Table of Contents|

[1] Li Yan, Guo Xiucheng, Tao Siran, Yang Jie, et al. NSGA-Ⅱ based traffic signal control optimization algorithmfor over-saturated intersection group [J]. Journal of Southeast University (English Edition), 2013, 29 (2): 211-216. [doi:10.3969/j.issn.1003-7985.2013.02.018]
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NSGA-Ⅱ based traffic signal control optimization algorithmfor over-saturated intersection group()
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
29
Issue:
2013 2
Page:
211-216
Research Field:
Traffic and Transportation Engineering
Publishing date:
2013-06-20

Info

Title:
NSGA-Ⅱ based traffic signal control optimization algorithmfor over-saturated intersection group
Author(s):
Li Yan1 Guo Xiucheng2 Tao Siran1 Yang Jie2
1School of Highway, Chang’an University, Xi’an 710064, China
2School of Transportation, Southeast University, Nanjing 210096, China
Keywords:
traffic signal control optimization algorithm intersection group over-saturated status NSGA-Ⅱ algorithm
PACS:
U491.51
DOI:
10.3969/j.issn.1003-7985.2013.02.018
Abstract:
In order to improve the efficiency of traffic signal control for an over-saturated intersection group, a non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)based traffic signal control optimization algorithm is proposed. The throughput maximum and average queue ratio minimum for the critical route of the intersection group are selected as the optimization objectives of the traffic signal control for the over-saturated condition. The consequences of the efficiency between traffic signal timing plans generated by the proposed algorithm and a commonly utilized signal timing optimization software Synchro are compared in a VISSIM signal control application programming interfaces(SCAPI)simulation environment by using real filed observed traffic data. The simulation results indicate that the signal timing plan generated by the proposed algorithm is more efficient in managing over-saturated flows at intersection groups, and, thus, it has the capability of optimizing signal timing under the over-saturated conditions.

References:

[1] Li Y, Guo X C, Yang J, et al. Mechanism analysis and implementation framework for over-saturated intersection group[J]. Journal of Transportation Systems Engineering and Information Technology, 2011, 11(5): 28-34.
[2] Papageorgiou M, Diakaki C, Dinopoulou V, et al. Review of road traffic control strategies[J]. Proceedings of the IEEE, 2003, 91(12):2043-2067.
[3] Zheng J Y, Wang Y H, Nihan N L, et al. Detecting cycle failures at signalized intersections using video image processing[J]. Computer-Aided Civil and Infrastructure Engineering, 2006, 21(6): 425-435.
[4] Washburn S S, Larson N. Signalized intersection delay estimation: case study comparison of TRANSYT-7F, synchro and HCS[J]. ITE Journal, 2002, 72(3): 30-35.
[5] TRB. Highway capacity manual 2010[M]. Washington DC: Transportation Research Board, 2010.
[6] Yang J, Guo X C, Li Y, et al. Modeling route correlation degree of urban signalized intersection group[J]. Journal of Transportation Systems Engineering and Information Technology, 2012, 12(1): 55-62.(in Chinese)
[7] Abbas M, Adam Z, Gettman D. Development and evaluation of optimal arterial control strategies for oversaturated conditions[J]. Transportation Research Record, 2011, 2259: 242-252.
[8] Denney R W, Head L, Spencer K. Signal timing under saturated conditions[R]. Washington DC: Federal Highway Administration, 2008.
[9] Wu X, Liu H X, Gettman D. Identification of oversaturated intersections using high-resolution traffic signal data[J]. Transportation Research Part C: Emerging Technologies, 2010, 18(4): 626-638.
[10] Ban X J, Hao P, Sun Z. Real time queue length estimation for signalized intersections using travel times from mobile sensors[J]. Transportation Research Part C: Emerging Technologies, 2011, 19(6): 1133-1156.
[11] Park B, Messer C J, Urbanik T. Traffic signal optimization program for oversaturated conditions: genetic algorithm approach[J]. Transportation Research Record, 1999, 1683: 133-142.
[12] Deb K, Pratap A, Agarwal S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197.
[13] Li P F, Abbas M. Stochastic dilemma hazard model at high-speed signalized intersections[J]. Journal of Transportation Engineering, 2010, 136(5): 448-456.
[14] Li Y, Guo X C, Yang J, et al. Routes classification method at intersections group using wavelet transform and spectrum analysis[J]. Journal of Southeast University:Natural Science Edition, 2012, 42(1): 168-172.(in Chinese)
[15] National Electrical Manufacturers Association. No. TS3.5—1996 National transportation communications for ITS protocol object definitions for actuated traffic signal controller units [S]. Washington DC, USA: NEMA, 1996.

Memo

Memo:
Biography: Li Yan(1983—), male, doctor, lecturer, lyan@chd.edu.cn.
Foundation item: The National Natural Science Foundation of China(No.51208054).
Citation: Li Yan, Guo Xiucheng, Tao Siran, et al.NSGA-Ⅱ based traffic signal control optimization algorithm for over-saturated intersection group[J].Journal of Southeast University(English Edition), 2013, 29(2):211-216.[doi:10.3969/j.issn.1003-7985.2013.02.018]
Last Update: 2013-06-20