A Capacity Model of Freeway Merging Areas with Partially Connected Automated Traffic

HU Jia; AN Lianhua; LI Xin

doi:10.3963/j.jssn.1674-4861.2021.01.016

Volume 39 Issue 1

Feb. 2021

Turn off MathJax

Article Contents

Article Navigation > Journal of Transport Information and Safety > 2021 > 39(1): 137-144

HU Jia, AN Lianhua, LI Xin. A Capacity Model of Freeway Merging Areas with Partially Connected Automated Traffic[J]. Journal of Transport Information and Safety, 2021, 39(1): 137-144. doi: 10.3963/j.jssn.1674-4861.2021.01.016

Citation:

HU Jia, AN Lianhua, LI Xin. A Capacity Model of Freeway Merging Areas with Partially Connected Automated Traffic[J]. Journal of Transport Information and Safety, 2021, 39(1): 137-144. doi: 10.3963/j.jssn.1674-4861.2021.01.016

Citation:

PDF( 1692 KB)

A Capacity Model of Freeway Merging Areas with Partially Connected Automated Traffic

doi: 10.3963/j.jssn.1674-4861.2021.01.016

HU Jia^1
,,
AN Lianhua¹,
LI Xin^{2
,
,}

1.
Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
2.
College of Transportation Engineering, Dalian Maritime University, Dalian 116026, Liaoning, China

Received Date: 2020-09-26
Publish Date: 2021-02-28

Abstract

Abstract

A capacity model is developed to study freeway merging areas of a novel mixed traffic with human-driven vehicles and connected automated vehicles equipped with cooperative adaptive cruise control. The interaction mechanism of factors, such as road traffic characteristics, road structure, and mainline traffic state before the merge, is considered. The probability and statistics theory is used to analyze coupling relationships between penetration rate and platoon length. Furthermore, based on the gap acceptance theory, reduction effects of ramp merging traffic on the capacity of the merging area is analyzed. The capacity model of freeway merging areas with partially connected automated traffic is established to quantitatively describe how the capacity changes with the penetration rate and platoon length of connected automated vehicles under various road conditions. The parameters of road traffic characteristics, road structure, and part of the traffic state before the ramp merge are calibrated according to the actual traffic condition, which improves versatility and transferability of the model. A Vissim simulation platform with an embedded vehicle dynamics module is developed to evaluate the model. The results show that the accuracy of the model is generally over 80%. The model performed well under various penetration rates and platoon lengths of connected automated vehicles.
- intelligent transportation,
- cooperative adaptive cruise control,
- capacity,
- penetration rate,
- platoon length

FullText(HTML)

References(21)

References

[1]	李克强, 戴一凡, 李升波, 等. 智能网联汽车(ICV)技术的发展现状及趋势[J]. 汽车安全与节能学报, 2017, 8(1): 1-14. doi: 10.3969/j.issn.1674-8484.2017.01.001 LI Keqiang, DAI Yifan, LI Shengbo, et al. State-of-the art and technical trends of intelligent and connected vehicles[J]. Automotive Safety and Energy, 2017, 8(1): 1-14. (in Chinese) doi: 10.3969/j.issn.1674-8484.2017.01.001
[2]	张耀伟, 李振龙, 赵晓华, 等. 车路协同下HMI对跟驰行为与视觉特性的影响[J]. 交通信息与安全, 2020, 38(2): 9-15. https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS202002005.htm ZHANG Yaowei, LI Zhenlong, ZHAO Xiaohua, et al. Influences of HMI on car following behaviors and visualcharacteristics in cooperative vehicle infrastructure system[J]. Journal of Transport Information and Safety, 2020, 38(2): 9-15. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JTJS202002005.htm
[3]	HILL C J, GARRETT J K. AASHTO connected vehicle infrastructure deployment analysis[R]. United States: Joint Program Office for Intelligent Transportation Systems, 2011.
[4]	李秀文, 荣建, 刘小明, 等. 快速路分、合流影响区交通特性及通行能力研究[J]. 公路交通科技, 2006, 23(1): 101-104. doi: 10.3969/j.issn.1002-0268.2006.01.026 LI Xiuwen, RONG Jian, LIU Xiaoming, et al. Analysis of traffic flow characteristics and capacities of diverging and merging influence areas[J]. Journal of Highway and Transportation Research and Development, 2006, 23(1): 101-104. (in Chinese) doi: 10.3969/j.issn.1002-0268.2006.01.026
[5]	孙剑, 殷炬元, 黎淘宁. 快速路入口匝道瓶颈宏观交通流模型[J]. 交通运输工程学报, 2019, 19(3): 122-133. doi: 10.3969/j.issn.1671-1637.2019.03.013 SUN Jian, YIN Juyuan, LI Taoning. Macroscopic traffic flow model of expressway on-ramp bottlenecks[J]. Journal of Traffic and Transportation Engineering, 2019, 19(3): 122-133. (in Chinese) doi: 10.3969/j.issn.1671-1637.2019.03.013
[6]	魏中华, 李志, 周晨静, 等. 城市快速路合流区汇入角度对合流区通行能力的影响[J]. 公路交通科技, 2017, 34(5): 116-121. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201705016.htm WEI Zhonghua, LI Zhi, ZHOU Chenjing, et al. Effect of merge angle on capacity of urban expressway merge area[J]. Journal of Highway and Transportation Research and Development, 2017, 34(5): 116-121. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201705016.htm
[7]	VAN AREM B, VAN DRIEL C J, VISSER R. The impact of cooperative adaptive cruise control on traffic-flow characteristics[J]. IEEE Transactions on Intelligent Transportation Systems, 2006, 7(4): 429-436. doi: 10.1109/TITS.2006.884615
[8]	SHLADOVER S E, SU D, LU X Y. Impacts of cooperative adaptive cruise control on freeway traffic flow[J]. Transportation Research Record, 2012, 2324(1): 63-70. doi: 10.3141/2324-08
[9]	XIAO L, WANG M, SCHAKEL W, et al. Unravelling effects of cooperative adaptive cruise control deactivation on traffic flow characteristics at merging bottlenecks[J]. Transportation Research Part C: Emerging Technologies, 2018(96): 380-397. http://www.sciencedirect.com/science/article/pii/S0968090X1830528X
[10]	LIU H, KAN X D, SHLADOVER S E, et al. Modeling impacts of cooperative adaptive cruise control on mixed traffic flow in multi-lane freeway facilities[J]. Transportation Research Part C: Emerging Technologies, 2018(95): 261-279. http://www.sciencedirect.com/science/article/pii/S0968090X18310313
[11]	CHEN D, AHN S, CHITTURI M, et al. Towards vehicle automation: Roadway capacity formulation for traffic mixed with regular and automated vehicles[J]. Transportation Research Part B: Methodological, 2017(100): 196-221. http://smartsearch.nstl.gov.cn/paper_detail.html?id=3a51b2453c855cd82a6d750b7ff3bf26
[12]	GHIASI A, HUSSAIN O, QIAN Z S, et al. A mixed traffic capacity analysis and lane management model for connected automated vehicles: A Markov chain method[J]. Transportation Research Part B: Methodological, 2017(106): 266-292.
[13]	秦严严, 王昊, 王炜, 等. 混有协同自适应巡航控制车辆的异质交通流稳定性解析与基本图模型[J]. 物理学报, 2017, 66(9): 257-265. https://www.cnki.com.cn/Article/CJFDTOTAL-WLXB201709027.htm QIN Yanyan, WANG Hao, WANG Wei, et al. Stability analysis and fundamental diagram ofheterogeneous traffic flow mixed with cooperativeadaptive cruise control vehicles[J]. Acta Physica Sinica, 2017, 66(9): 257-265. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-WLXB201709027.htm
[14]	VANDER WERF J, SHLADOVER S E, MILLER M A, et al. Effects of adaptive cruise control systems on highway traffic flow capacity[J]. Transportation Research Record, 2002(1): 78-84. http://www.researchgate.net/publication/239438678_Effects_of_Adaptive_Cruise_Control_Systems_on_Highway_Traffic_Flow_Capacity
[15]	National Research Council highway capacity manual[M]. 5^th Ed. Washington D. C: Transportation Research Board, 2010.
[16]	ARNAOUT G M, BOWLING S. A progressive deployment strategy for cooperative adaptive cruise control to improve traffic dynamics[J]. International Journal of Automation and Computing, 2014, 11(1): 10-18. doi: 10.1007/s11633-014-0760-2
[17]	PUEBOOBPAPHAN R, PARK D, KIM Y, et al. Time headway distribution of probe vehicles on single and multiple lane highways[J]. Ksce Journal of Civil Engineering, 2013, 17(4): 824-836. doi: 10.1007/s12205-013-0212-5
[18]	LAI J T, HU J, CUI L, et al. A generic simulation platform for cooperative adaptive cruise control under partially connected and automated environment[J]. Transportation Research Part C: Emerging Technologies, 2020(121): 102874. http://www.sciencedirect.com/science/article/pii/s0968090x20307749
[19]	TREIBER M, KESTING A. Traffic flow dynamics[M]. New York: Springer, 2013.
[20]	MILANÚS V, SHLADOVER S E, SPRING J, et al. Cooperative adaptive cruise control in real traffic situations[J]. IEEE Transactions on Intelligent Transportation Systems, 2013, 15(1): 296-305. http://smartsearch.nstl.gov.cn/paper_detail.html?id=92aaed0531520f273c3984b5ee42ddbb
[21]	CUI L, HU J, PARK B B, et al. Development of a simulation platform for safety impact analysis considering vehicle dynamics, sensor errors, and communication latencies: assessing cooperative adaptive cruise control under cyber attack[J]. Transportation Research Part C: Emerging Technologies, 2018(97): 1-22. http://www.sciencedirect.com/science/article/pii/S0968090X18305990

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

Figures(5) / Tables(1)

Get Citation

PDF

XML

Article Metrics

Article views (976) PDF downloads(57)

A Capacity Model of Freeway Merging Areas with Partially Connected Automated Traffic

doi: 10.3963/j.jssn.1674-4861.2021.01.016

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Proportional views

Related

A Capacity Model of Freeway Merging Areas with Partially Connected Automated Traffic

doi: 10.3963/j.jssn.1674-4861.2021.01.016

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Proportional views

Related

Export File

Citation

Format

Content