RLRM control method of single entrance ramp for highway

WANG Xing-ju; GAO Gui-feng; MIYAGI T

doi:10.19818/j.cnki.1671-1637.2012.03.015

Volume 12 Issue 3

Turn off MathJax

Article Contents

Article Navigation > Journal of Traffic and Transportation Engineering > 2012 > 12(3): 101-107

WANG Xing-ju, GAO Gui-feng, MIYAGI T. RLRM control method of single entrance ramp for highway[J]. Journal of Traffic and Transportation Engineering, 2012, 12(3): 101-107. doi: 10.19818/j.cnki.1671-1637.2012.03.015

Citation:

WANG Xing-ju, GAO Gui-feng, MIYAGI T. RLRM control method of single entrance ramp for highway[J]. Journal of Traffic and Transportation Engineering, 2012, 12(3): 101-107. doi: 10.19818/j.cnki.1671-1637.2012.03.015

Citation:

PDF( 904 KB)

RLRM control method of single entrance ramp for highway

doi: 10.19818/j.cnki.1671-1637.2012.03.015

WANG Xing-ju^{1, 2
,},
GAO Gui-feng^{1, 2},
MIYAGI T³

1.
School of Traffic and Transportation, Shijiazhuang Tiedao University, Shijiazhuang 050043, Hebei, China
2.
Traffic Safety and Control Laboratory of Hebei Province, Shijiazhuang 050043, Hebei, China
3.
Graduate School of Information Sciences, Tohoku University, Sendai 9808578, Miyagi, Japan

More Information

Author Bio:
WANG Xing-ju (1978-), male, associate professor, PhD, +86-311-87939527, wangxingju@stdu.edu.cn
Received Date: 2011-12-27
Publish Date: 2012-06-25

Abstract

Abstract

In order to relieve freeway traffic congestion, reinforcement learning ramp metering(RLRM) control method for single entrance ramp of highway under the incomplete information was proposed based on the artificial intelligence theories of reinforcement learning.Average speeds, average densities, traffic outflows and travel times of numerical cases 1-6 were calculated, and the control effect of RLRM was compared with no control and fixed-time control.Simulation result shows that in case 1 with the lowest traffic inflow, the congestion relief rates of fixed-time control and RLRM control depending on travel time are-6.25% and-9.38% respectively, which indicates that the control effect is not significant.When the traffic inflow increases in case 3, the congestion relief rates of fixed-time control and RLRM control depending on travel time are-8.19% and 3.51% respectively, which indicates that the control has some effect, and RLRM control performs better than fixed-time control.In case 6 with the highest traffic inflow, the congestion relief rates of fixed-time control are 8.20%, 0.39%, 18.97% and 23.99% respectively, and those of RLRM control are 18.18%, 3.42%, 30.65% and 44.41% taking average speed, average density, traffic outflow and travel time as evaluating indexes respectively, which shows that RLRM control effect is more significant than fixed-time control.So the greater the traffic inflow is, the better the control effect of RLRM is.
- traffic control,
- ramp,
- traffic flow simulation,
- artificial intelligence,
- reinforcement learning,
- RLRM control

FullText(HTML)

References(16)

References

[1]	朱建国, 王朝辉. 高速公路建设精细化管理效果评价体系[J]. 长安大学学报: 自然科学版, 2012, 32(2): 52-57. https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL201202012.htm ZHU Jian-guo, WANG Chao-hui. Effect evaluation system of freeway construction meticulous management[J]. Journal of Chang'an University: Natural Science Edition, 2012, 32(2): 52-57. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL201202012.htm
[2]	干宏程, 陈建阳, 汪晴. 高速公路网路径诱导与匝道控制集成[J]. 系统工程, 2009, 27(6): 78-82. https://www.cnki.com.cn/Article/CJFDTOTAL-GCXT200906012.htm GAN Hong-cheng, CHEN Jian-yang, WANG Qing. Integrated routing and ramp metering control for freeway networks[J]. Systems Engineering, 2009, 27(6): 78-82. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GCXT200906012.htm
[3]	徐建闽, 李林, 林培群, 等. 高速公路交通管制策略仿真评价[J]. 公路, 2011(2): 83-87. https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL201102018.htm XU Jian-min, LI Lin, LIN Pei-qun, et al. Simulation-based evaluation for expressway traffic control strategies[J]. Highway, 2011(2): 83-87. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL201102018.htm
[4]	曹志威, 韩印. 基于模糊理论的高速公路入口匝道控制研究[J]. 交通与运输, 2011(7): 54-58. https://www.cnki.com.cn/Article/CJFDTOTAL-JTYH201101016.htm CAO Zhi-wei, HAN Yin. Study on freeway on-ramp control based on fuzzy theory[J]. Traffic and Transportation, 2011(7): 54-58. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JTYH201101016.htm
[5]	GOMES G, HOROWITZ R. Optimal freeway ramp metering using the asymmetric cell transmission model[J]. Transpor-tation Research Part C: Emerging Technologies, 2006, 14(4): 244-262. doi: 10.1016/j.trc.2006.08.001
[6]	庞明宝, 贺国光, 马宁. 基于遗传算法高速公路混沌系统模糊延迟反馈匝道控制[J]. 土木工程学报, 2009, 42(3): 125-131. doi: 10.3321/j.issn:1000-131X.2009.03.021 PANG Ming-bao, HE Guo-guang, MA Ning. On-ramp chaos control of freeway system with fuzzy delay feedback based on genetic algorithm[J]. China Civil Engineering Journal, 2009, 42(3): 125-131. (in Chinese). doi: 10.3321/j.issn:1000-131X.2009.03.021
[7]	张海军, 杨晓光, 张珏. 高速道路入口匝道控制方法综述[J]. 同济大学学报: 自然科学版, 2005, 33(8): 1051-1055, 1082. doi: 10.3321/j.issn:0253-374X.2005.08.012 ZHANG Hai-jun, YANG Xiao-guang, ZHANG Jue. Review of freeway on-ramp metering methodologies[J]. Journal of Tongji University: Natural Science, 2005, 33(8): 1051-1055, 1082. (in Chinese). doi: 10.3321/j.issn:0253-374X.2005.08.012
[8]	姜紫峰, 荆便顺, 韩锡令. 高速公路入口匝道控制的仿真研究[J]. 中国公路学报, 1997, 10(2): 83-89. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL199702014.htm JIANG Zi-feng, JING Bian-shun, HAN Xi-ling. Simulation study of on-ramp control in freeway[J]. China Journal of Highway and Transport, 1997, 10(2): 83-89. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL199702014.htm
[9]	PAPAGEORGIOU M, HADJ-SALEM H, MIDDELHAM F. ALINEA local ramp metering: summary of field results[J]. Transportation Research Record, 1997(1603): 90-98. doi: 10.3141/1603-12
[10]	郑飞, 杜豫川, 孙立军. 基于ALINEA算法快速路入口匝道单点动态控制[J]. 同济大学学报: 自然科学版, 2009, 37(6): 766-771. https://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ200906011.htm ZHENG Fei, DU Yu-chuan, SUN Li-jun. ALINEA-based on-ramp traffic-responsive local-metering strategy for express-way in Shanghai[J]. Journal of Tongji University: Natural Science, 2009, 37(6): 766-771. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ200906011.htm
[11]	贺敬凯, 徐建闽. 基于BP神经网络的入口匝道控制器的设计[J]. 华南理工大学学报: 自然科学版, 2002, 30(7): 24-27. https://www.cnki.com.cn/Article/CJFDTOTAL-HNLG200207006.htm HE Jing-kai, XU Jian-min. Design of on-ramp controller based on BP neural networks[J]. Journal of South China University of Technology: Natural Science Edition, 2002, 30(7): 24-27. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-HNLG200207006.htm
[12]	刘平, 任建亭. 基于PID神经网络的快速路入口匝道控制[J]. 科学技术与工程, 2011, 11(32): 7961-7966. doi: 10.3969/j.issn.1671-1815.2011.32.027 LIU Ping, REN Jian-ting. Freeway ramp metering based on PID neural network[J]. Science Technology and Engineering, 2011, 11(32): 7961-7966. (in Chinese). doi: 10.3969/j.issn.1671-1815.2011.32.027
[13]	陈德望, 王飞跃, 陈龙. 基于模糊神经网络的城市高速公路入口匝道控制算法[J]. 交通运输工程学报, 2003, 3(2): 100-105. http://transport.chd.edu.cn/article/id/200302017 CHEN De-wang, WANG Fei-yue, CHEN Long. Freeway ramp control algorithm based on neurofuzzy networks[J]. Journal of Traffic and Transportation Engineering, 2003, 3(2): 100-105. (in Chinese). http://transport.chd.edu.cn/article/id/200302017
[14]	赵明, 侯忠生, 晏静文. 受限迭代学习入口匝道控制收敛性分析[J]. 交通运输系统工程与信息, 2011, 11(2): 166-173. https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201102025.htm ZHAO Ming, HOU Zhong-sheng, YAN Jing-wen. Convergence analysis of ILC based ramp metering under constraints[J]. Journal of Transportation Systems Engineering and Informa-tion Technology, 2011, 11(2): 166-173. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-YSXT201102025.htm
[15]	侯忠生, 晏静文. 带有迭代学习前馈的快速路无模型自适应入口匝道控制[J]. 自动化学报, 2009, 35(5): 588-595. https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO200905022.htm HOU Zhong-sheng, YAN Jing-wen. Model free adaptive control based freeway ramp metering with feedforward itera-tive learning controller[J]. ACTA Automatica Sinica, 2009, 35(5): 588-595. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO200905022.htm
[16]	王兴举, 宫城俊彦. 强化学习型匝道控制模型的研究[J]. 石家庄铁道大学学报: 自然科学版, 2010, 23(2): 104-108. https://www.cnki.com.cn/Article/CJFDTOTAL-SJZT201002019.htm WANG Xing-ju, MIYAGI T. Reinforcement learning ramp metering[J]. Journal of Shijiazhuang Tiedao University: Natural Science Edition, 2010, 23(2): 104-108. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-SJZT201002019.htm

Relative Articles

Supplements(0)

Cited By

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Get Citation

PDF

XML

Article Metrics

Article views (987) PDF downloads(1062)

RLRM control method of single entrance ramp for highway

doi: 10.19818/j.cnki.1671-1637.2012.03.015

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Proportional views

Related

RLRM control method of single entrance ramp for highway

doi: 10.19818/j.cnki.1671-1637.2012.03.015

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Proportional views

Related

Export File

Citation

Format

Content