A hybrid traffic flow model with considering the influence of adaptive cruise control vehicles and on-ramps

Hua Xue-Dong; Wang Wei; Wang Hao

doi:10.7498/aps.65.084503

Abstract

Recently, autonomous vehicles and the relevant studies have attracted much attention. Adaptive cruise control (ACC), which is a kind of cruise control system for vehicles, automatically adjusts the vehicle speed to maintain a safe distance from vehicles ahead. Since the vehicle with ACC (called ACC vehicles) is semi-autonomous, the performance of ACC vehicle must be quite different from that of manual vehicle. The characteristics of traffic flow with ACC vehicles should be carefully investigated, especially when the traffic system is a bit complicated, such as on-ramp system. The primary objective of this paper is to propose a traffic flow model to simulate the traffic flow with considering the influence of ACC vehicles and on-ramps. Based on the model proposed by Yuan in 2009 [Yuan Y M 2009 Ph. D. Dissertation (Hefei: University of Science and Technology of China)], a hybrid traffic flow model with considering the influence of ACC vehicles and on-ramps is developed. Considering the differences between ACC and manual vehicles, a car-following sub-model based on constant time headway principle is developed for ACC vehicles, while an MCD cellular automata sub-model is proposed for manual vehicles. Besides, a new parameter, , is introduced to show different psychologies of drivers when changing lane from on-ramp to main road. The lane-changing model for vehicles on-ramp is developed as well. At the end, numerical simulation is demonstrated to study the influence of ACC vehicles on traffic flow at on-ramp, and to reveal the influence of parameters on the proposed hybrid model (i.e., the length of merge area, the desired time headway of ACC vehicle and ) on model performance. The results of this paper are as follows. 1) When the ACC vehicles exist in a traffic system, the performance of traffic flow in a on-ramp area is improved: the influence of merged vehicles on main road is reduced, and the average speed and volume are increased. 2) The increase of ACC vehicles can help to alleviate traffic congestion in both congestion duration and scope aspects. 3) The newly proposed hybrid model is sensitive to the length of merge area lw, the desired time headway of ACC vehicle Hd and lane-changing psychology parameter : the decrease of Hd and the increase of can both improve the average speed and volume of traffic flow. In addition, when the volume of on-ramp is small, the speed and volume of main road can be improved by enlarging lw. When the volume of on-ramp is large, a small lw will be better for traffic flow.

Keywords:

Authors and contacts

1.
Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 210096, China;
2.
Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 210096, China

Corresponding author: Wang Wei, wangwei@seu.edu.cn

Funds: Project supported by the National Basic Research Program of China (Grant No. 2012CB725402), the Key Program of the National Natural Science Foundation of China (Grant No. 51338003), the National Natural Science Foundation of China (Grant No. 51478113), and the Scientific Research Foundation of Graduate School of Southeast University, China (Grant No. YBJJ1345).

References

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Cited By

[1]	Hua X D, Wang W, Wang H 2011 Acta Phys. Sin. 60 084502 (in Chinese) [华雪东, 王炜, 王昊 2011 物理学报 60 084502]
[2]	Yuan Y M 2009 Ph. D. Dissertation (Hefei: University of Science and Technology of China) (in Chinese) [袁耀明 2009 博士学位论文 (合肥: 中国科学技术大学)]
[3]	Lighthill M J, Whitham G B 1955 Proc. Roy. Soc. Ser. A 22 317
[4]	Richards P I 1956 Oper. Res. 4 42
[5]	Pipes L A 1969 Transp. Res. 3 229
[6]	Payne H J 1971 Math. Meth. Pub. Sys. 28 51
[7]	Kuhne R D 1984 Proceeding 9th International Symposium on Transportation and Traffic Theory Delft, Netherlands, July 11-13, 1984 p21
[8]	Jiang R, Wu Q S, Zhu Z J 2002 Transp. Res. B 36 405
[9]	Xue Y, Dai S Q 2003 Phys. Rev. E 68 066123
[10]	Tang T Q, Caccetta L, Wu Y H, Huang H J, Yang X B 2014 J. Adv. Transport. 48 304
[11]	Tang T Q, Shi W F, Yang X B, Wang Y P, Lu G Q 2013 Physica A 392 6300
[12]	Peng G H, Song W, Peng Y J, Wang S H 2014 Physica A 398 76
[13]	Redhu P, Gupta A K 2015 Physica A 421 249
[14]	Gupta A K, Sharma S 2010 Chin. Phys. B 19 110503
[15]	Gupta A K, Sharma S 2012 Chin. Phys. B 21 015201
[16]	Peng G H, Cai X H, Cao B F, Liu C Q 2012 Physica A 391 656
[17]	Treiber M, Henneeke A, Helbing D 1999 Phys. Rev. E 59 239
[18]	Herbing D, Treiber M 1998 Granular Matter 1 21
[19]	Herbing D 1996 Physica A 233 253
[20]	Herbing D 1996 Phys. Rev. E 53 2366
[21]	Li L, Shi P F 2005 Chin. Phys. 14 576
[22]	Tang T Q, He J, Yang S C, Shang H Y 2014 Physica A 413 583
[23]	Zeng Y Z, Zhang N, Liu L J 2014 Acta Phys. Sin. 63 068901 (in Chinese) [曾友志, 张宁, 刘利娟 2014 物理学报 63 068901]
[24]	Ge H X, Meng X P, Zhu H B, Li Z P 2014 Physica A 408 28
[25]	Koutsopoulos H N, Farah H 2012 Trans. Res. B 46 563
[26]	Ge H X, Yu J, Lo S M 2012 Chin. Phys. Lett. 29 50502
[27]	Ge H X 2011 Chin. Phys. B 20 090502
[28]	Zhou T, Sun L H, Zhao M, Li H M 2013 Chin. Phys. B 22 090205
[29]	Punzo V, Ciuffo B, Montanino M 2012 Transp. Res. Rec. 2315 11
[30]	Lakouari N, Bentaleb K, Ez-Zahraouy H, Benyoussef A 2015 Physica A 439 132
[31]	Yang D, Qiu X P, Yu D, Sun R X, Pu Y 2015 Physica A 424 62
[32]	Jing M, Deng W, Wang H, Ji Y J 2012 Acta Phys. Sin. 61 244502 (in Chinese) [敬明, 邓卫, 王昊, 季彦婕 2012 物理学报 61 244502]
[33]	Lrraga M E, Alvarez-Icaza L 2014 Chin. Phys. B 23 050701
[34]	Qian Y S, Shi P J, Zeng Q, Ma C X, Lin F, Sun P 2010 Chin. Phys. B 19 048201
[35]	Ez-Zahraouyt H, Jetto K, Benyoussef A 2006 Chin. J. Phys. 44 486
[36]	Siebert F W, Oehl M, Pfister H R 2014 Trans. Res. F 25 65
[37]	Zhao D B, Hu Z H, Xia Z P, Alippi C, Zhu Y H, Wang D 2014 Neurocomputing 125 57
[38]	Bishop R 2005 Intelligent Vehicle Technology and Trends (Boston: Artech House) pp127-134
[39]	Mark V, Schleicher S, Gelau C 2011 Accident Anal. Prev. 43 1134
[40]	Bato J 2011 Ph. D. Dissertation (Seattle: University of Washington)
[41]	Orosz G, Moehlis J, Bullo F 2010 Phys. Rev. E 81 025204
[42]	Xiao L Y, Gao F 2011 IEEE Trans. Intell. Transp. 12 1184
[43]	Davis L C 2012 Phys. Lett. A 376 2658
[44]	Werf J V, Shladover S, Miller M, Kourjanskaia N 2002 Transp. Res. Rec. 1800 78
[45]	Yuan Y M, Jiang R, Hu M B, Wu Q S, Wang R 2009 Physica A 388 2483
[46]	Davis L C 2004 Phys. Rev. E 69 066110
[47]	Kesting A, Treiber M, Schonhof M, Helbing D 2008 Transp. Res. C 16 668
[48]	Jiang R, Hu M B, Jia B, Wang R, Wu Q S 2007 Eur. Phys. J. B 58 197
[49]	Jiang R, Wu Q S 2006 Phys. Lett. A 359 99
[50]	Jiang R, Wu Q S 2005 Eur. Phys. J. B 46 581

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Vol. 65, Issue 8 - 2016-04-20

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