Abstract With the increasing maturity of automatic driving technology, the homogeneous traffic flow will gradually evolve into the heterogeneous traffic flow, which consists of human-driving and autonomous vehicles. To better study the characteristics of the heterogeneous traffic system, this paper proposes a new car-following model for autonomous vehicles and heterogeneous traffic flow, which considers the self-stabilizing effect of vehicles. Through linear and nonlinear methods, this paper deduces and analyzes the stability of such a car-following model with the self-stabilizing effect. Finally, the model is verified by numerical simulation. Numerical results show that the self-stabilizing effect can make the heterogeneous traffic flow more stable, and that increasing the self-stabilizing coefficient or historical time length can strengthen the stability of heterogeneous traffic flow and alleviate traffic congestion effectively. In addition, the heterogeneous traffic flow can also be stabilized with a higher proportion of autonomous vehicles.
Fund: Project supported by the National Natural Science Foundation of China (Grant No. 61773243), the Major Technology Innovation Project of Shandong Province, China (Grant No. 2019TSLH0203), and the National Key Research and Development Program of China (Grant No. 2020YFB1600501).
Yuan Gong(公元) and Wen-Xing Zhu(朱文兴) Modeling the heterogeneous traffic flow considering the effect of self-stabilizing and autonomous vehicles 2022 Chin. Phys. B 31 024502
[1] Pipes L A 1953 J. Appl. Phys.24 274 [2] Bando M, Hasebe K, Nakayama A, Shibata A and Sugiyama Y 1995 Phys. Rev. E51 1035 [3] Nagatani T 1999 Phys. Rev. E60 6395 [4] Sawada S 2001 J. Phys. Math. Gen.34 11253 [5] Jiang R, Wu Q and Zhu Z 2001 Phys. Rev. E64 017101 [6] Ge H X, Zhu H B and Dai S Q 2006 Eur. Phys. J. B54 503 [7] Li Z P and Liu Y C 2006 Eur. Phys. J. B53 367 [8] Peng G H, Cai X H, Liu C Q, Cao B F and Tuo M X 2011 Phys. Lett. A375 3973 [9] Liu Y J, Zhang H L and He L 2012 Chin. Phys. Lett.29 104502 [10] Yu S, Liu Q and Li X 2013 Commun. Nonlinear Sci. Numer. Simul.18 1229 [11] Tang T, Shi W, Shang H and Wang Y 2014 Nonlinear Dyn.76 2017 [12] Tang T Q, Li J G, Huang H J and Yang X B 2014 Measurement48 63 [13] Li Z, Li W, Xu S and Qian Y 2015 Nonlinear Dyn.80 529 [14] Li Z, Qin Q, Li W, Xu S, Qian Y and Sun J 2018 Nonlinear Dyn.91 1113 [15] Peng G, Lu W, He H and Gu Z 2016 Commun. Nonlinear Sci. Numer. Simul.40 197 [16] Liu F, Cheng R, Ge H and Yu C 2016 Physica A464 267 [17] Ou H, Tang T Q, Zhang J and Zhou J M 2018 Physica A505 105 [18] Zhang J, Tang T Q and Yu S W 2018 Physica A492 1831 [19] Chen C, Ge H and Cheng R 2019 Physica A535 122423 [20] Sun Y, Ge H and Cheng R 2019 Physica A521 752 [21] Liao P, Tang T Q, Wang T and Zhang J 2019 Physica A525 108 [22] Kuang H, Wang M T, Lu F H, Bai K Z and Li X L 2019 Physica A527 121268 [23] An S, Xu L, Chen G and Shi Z 2020 Mod. Phys. Lett. B34 2050182 [24] Li S, Cheng R and Ge H 2020 Physica A558 125015 [25] Peng G H 2020 Chin. Phys. B29 084501 [26] Peng Y, Liu S and Yu D Z 2020 Physica A538 122967 [27] Ma M, Ma G and Liang S 2021 Appl. Math. Model.94 1 [28] Cheng R, Li S and Ge H 2021 Mod. Phys. Lett. B35 2150238 [29] Kuang H, Lu F H, Yang F L, Peng G H and Li X L 2021 Int. J. Mod. Phys. C32 2150095 [30] Zhou Y and Ahn S 2019 Transp. Res. Part B125 175 [31] Xu S and Peng H 2020 IEEE Trans. Intell. Transp. Syst.21 48 [32] Xu C, Zhao W and Wang C 2020 IEEE Trans. Intell. Transp. Syst.21 2510 [33] Xia Y, Qu Z, Sun Z and Li Z 2021 IEEE Trans. Veh. Technol.70 4178 [34] Tang T Q, Gui Y and Zhang J 2021 IEEE Trans. Intell. Transp. Syst. [35] Bose A and Ioannou P A 2003 IEEE Trans. Intell. Transp. Syst.4 173 [36] Ngoduy D 2013 Commun. Nonlinear Sci. Numer. Simul.18 2699 [37] Zhu W X and Zhang H M 2018 Physica A496 274 [38] Gong S and Du L 2018 Transp. Res. Part B116 25 [39] Navas F and Milanés V 2019 Transp. Res. Part C108 167 [40] Xie D F, Zhao X M and He Z 2019 IEEE Trans. Intell. Transp. Syst.20 2060 [41] Di Vaio M, Fiengo G, Petrillo A, Salvi A, Santini S and Tufo M 2019 IEEE Trans. Intell. Transp. Syst.20 4339 [42] An S, Xu L, Qian L, Chen G, Luo H and Li F 2020 Physica A560 125246 [43] Wang J, Zheng Y, Xu Q, Wang J and Li K 2021 IEEE Trans. Intell. Transp. Syst.22 7445 [44] Zheng F, Liu C, Liu X, Jabari S E and Lu L 2020 Transp. Res. Part C112 203 [45] Wang S, Yu B and Wu M 2021 IEEE Trans. Intell. Transp. Syst. [46] Montanino M and Punzo V 2021 Transp. Res. Part B144 133 [47] Yao Z, Xu T, Jiang Y and Hu R 2021 Physica A561 125218 [48] Guo J, Cheng S and Liu Y 2021 IEEE Trans. Intell. Transp. Syst.22 1639 [49] Cui S, Cao F, Yu B and Yao B 2021 IEEE Trans. Intell. Transp. Syst. [50] Chen C, Xu Z and Kuang H 2017 J. Guangxi Normal University (Natural Science Edition) 35 14 (in Chinese) [51] Zhu W X and Zhang L D 2014 Int. J. Mod. Phys. C25 1450018
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention. The number in the centre is the Altmetric score. Social media and mainstream news media are the main sources that calculate the score. Reference managers such as Mendeley are also tracked but do not contribute to the score. Older articles often score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for other articles of a similar age.
