Genetic algorithm for optimization in adaptive bus signal priority control
DOI:
https://doi.org/10.11121/ijocta.01.2013.00138Keywords:
Optimization, signal control, genetic algorithm, priorityAbstract
This paper firstly proposes an improved genetic algorithm (GA) for optimization in adaptive bus signal priority control at signalized intersections. Unlike conventional genetic algorithms with slow convergence speed, this algorithm can increase the convergence speed by utilizing the compensation rule between consecutive signal cycles to narrow new possible generated population spaces. Secondly, the paper would like to present a way to apply the algorithm to a simple adaptive bus signal priority control as well as compare how much the computation time is saved when applying the improved algorithm. Then the research thirdly investigates the efficiency of the proposed algorithm under various flow rate situations. The results show that the improved genetic algorithm can reduce the computation time considerably, by up to 48.39% for the studied case. With high saturation degrees on the cross street, the convergence rate performance of the improved genetic algorithm is significantly good. The figure can be up to 36.2% when compared with the convergence rate of the conventional GA.
Downloads
References
Ayad, M. T., Mohd, S. A. and Mohd, Z. M. Y., The Use of Genetic Algorithm for Traffic light and Pedestrian Crossing Control, International Journal of Computer Science and Network Security, Vol.9, No.2 (2009).
David, B., David, R., Ralph, R.M., An overview of genetic algorithm, University Computing, 15(2), pp58-69 (1993).
Der-Hong, L., Xu, Y., Chandrasekar, P., Parameter Calibration for Paramics Using Genetic Algorithm, TRB, ID Number: 01-2399 (2001).
Der-Horng L., Wei H., A new methodology for multi-level bus prioritization at signalized intersections, TRB Annual Meeting CD-ROOM (2005).
Eleni C. and Alexander. S., Traffic Signal Optimization with Transit Signal Priority: Application to an Isolated intersection , TRB Annual Meeting (2011).
Geetha, N., W., Shamas, u. I. B., Masao, K. and Majid, S., An improved Bus signal Priority Model, Seisan-kenkyu, Vol.60, No.4, p.59-63, (2008).
Guangwei, Z., Albert, G. and Shen, L.D., Optimization of adaptive transit signal priority using parallel Genetic Algorithm, Tsinghua science and technology, ISSN 1007-0214 02/14, pp131-140, Vol.12, No.2 (2007).
Halim, C., Michael, G.H. B., Traffic signal timing optimisation based on genetic algorithm approach, including drivers’routing, Transportation Research Part B 38, 329-342, (2004). CrossRef
Henry X.L., Lianyu. C., Will. R., Paramics API Development Document for Actual Signal, Signal Coordination and Ramp Control, California PATH ATMIS Center, University of California, Irvine, (2003).
Heydar, T. S., Mohsen, K. and Mahsa, D., Intelligent Transport System based on Genetic Algorithm, World Applied Sciences Journal 6 (7): 908-913 (2009).
Highway Capacity Manual, TRB, National Research Council, Washington D.C.,USA (2000).
Jitendra, A. and Tom, V.M., Transit Route Network Design Using Parallel Genetic Algorithm, Journal of computing in civil engineering (ASCE), Vol.18, No.3 (2004).
Leena, S., et al., Time Optimization for Traffic Signal Control Using Genetic Algorithm, International Journal of Recent Trends in Engineering, Vol.2, No.2 (2009).
Li, M., Development and applications of adaptive transit signal priority system, doctoral Dissertation, (2010).
Liu, H., Zhang, J. and Cheng, D., Analytical Approach to Evaluating Transit Signal Priority, Journal of Transportation systems engineering and information technology, Vol.8, Issue 2 (2008).
Liviu, C. and Andreea, D., Public Transport Route Finding using Hybrid Genetic Algorithm, Informative Economicca, Vol.15, No.1 (2011).
Melanie, M., Genetic Algorithm Overview, Santa Fe Institute, (1995).
Qing H., K Larry, H., Jun, D., A Heuristic algorithm for Priority traffic signal control, TRB Annual Meeting (2011).
Regina, M., Traffic signal timing manual, U.S. Department of Transportation, Federal Highway Administration, Publication Number: FHWA-HOP-08-024, June (2008).
Richard, J.P. and Xin, F., Improving genetic algorithms perforamce by hashing fitness values, Department of Electrical and Computer Engineering, Marquette University, USA.
Rui W., Sunghyu, B., Okamura, T., Nakamura, F., A practical approach for design of bus signal priority strategy, 12th WCTR, Lisbon, Portugal (2010).
Ryohei, T., et al., Trial Operation of a new public transportation Prirority system using Infrared beacons for two-way communication, 3rd Annual World Congress on ITS, Orland (1996).
Wanjing M., Yue, L., Xiao-Guang, Y., A dynamic Programming Model for Bus Signal Priority with Multi request, TRB Annual Meeting (2011).
Downloads
Published
How to Cite
Issue
Section
License
Articles published in IJOCTA are made freely available online immediately upon publication, without subscription barriers to access. All articles published in this journal are licensed under the Creative Commons Attribution 4.0 International License (click here to read the full-text legal code). This broad license was developed to facilitate open access to, and free use of, original works of all types. Applying this standard license to your work will ensure your right to make your work freely and openly available.
Under the Creative Commons Attribution 4.0 International License, authors retain ownership of the copyright for their article, but authors allow anyone to download, reuse, reprint, modify, distribute, and/or copy articles in IJOCTA, so long as the original authors and source are credited.
The readers are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material
- for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
under the following terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
This work is licensed under a Creative Commons Attribution 4.0 International License.