References
[1] Sun P, Wang X, Zhu M. Modeling Car-Following Behavior on Freeways Considering Driving Style. Journal of Transportation Engineering, Part A: Systems. 2021;147(12). DOI: 10.1061/JTEPBS.0000584.
[2] Suh J, Yeo H. An empirical study on the traffic state evolution and stop-and-go traffic development on freeways. Transportmetrica A: Transport Science. 2016;12(1): 80-97. DOI: 10.1080/23249935.2015.1101508.
[3] Kordani AA, Saffarzadeh M, Salehikalam A. Identifying and analyzing stop and go traffic based on asymmetric theory of driving behavior in acceleration and deceleration. International Journal of Transportation Engineering. 2016;3(4): 237-252. DOI: 10.22119/IJTE.2016.16170.
[4] Park M, Kim Y, Yeo H. Development of an Asymmetric car-following model and simulation validation. IEEE Transactions on Intelligent Transportation Systems. 2020;21(8): 3513-3524. DOI: 10.1109/tits.2019.2930320.
[5] Newell GF. Instability in dense highway traffic: A review. 1965; p. 9-54.
[6] Hao Xu, et al. Modeling the asymmetry in traffic flow (a): Microscopic approach. Applied Mathematical Modelling. 2013;37(22). DOI: 10.1016/j.apm.2013.04.037.
[7] Wang K, et al. Research on Car-Following Model considering Driving Style. Mathematical Problems in Engineering. 2022;2022. DOI: 10.1155/2022/7215697.
[8] Suh J, Yeo H. A study on the wave development and evolution characteristics of stop-and-go traffic. Proceedings of the Eastern Asia Society for Transportation Studies. 2011.
[9] Li X-C. Modeling and analysis of car-following behavior considering the asymmetry [考虑非对称特性的车辆跟驰行为建模与分析]. Master Degree Thesis. Southwest Jiaotong University; 2019.
[10] Qian, et al. Using asymmetric theory to identify heterogeneous drivers’ behavior characteristics through traffic oscillation. IEEE Access. 2019;7: 106284-106294. DOI: 10.1109/ACCESS.2019.2930762.
[11] Chen D, et al. Microscopic traffic hysteresis in traffic oscillations: A behavioral perspective. Transportation Research Part B: Methodological. 2012;46(10): 1440-1453. DOI: 10.1016/j.trb.2012.07.002.
[12] Wei D, Liu H. Analysis of asymmetric driving behavior using a self-learning approach. Transportation Research Part B: Methodological. 2013;47: 1-14. DOI: 10.1016/j.trb.2012.09.003.
[13] Newell GF. Theories of instability in dense highway traffic. Journal of the Operations Research Society of Japan. 1962;1(5): 9-54.
[14] Yeo H, Skabardonis A. Understanding stop-and-go traffic in view of asymmetric traffic theory. Transportation & Traffic Theory. 1970.
[15] Wong GCK, Wong SC. A multi-class traffic flow model – an extension of LWR model with heterogeneous drivers. Transportation Research Part A: Policy and Practice. 2002;36(9): 827-841. DOI: 10.1016/s0965-8564(01)00042-8.
[16] Ahn S, et al. A method to account for non-steady state conditions in measuring traffic hysteresis. Transportation Research Part C: Emerging Technologies. 2013;34: 138-147. DOI: 10.1016/j.trc.2011.05.020.
[17] Laval JA. Hysteresis in traffic flow revisited: An improved measurement method. Transportation Research Part B: Methodological. 2011;45(2): 385-391. DOI: 10.1016/j.trb.2010.07.006.
[18] Li X, et al. An improved car-following model considering the influence of space gap to the response. Physical A: Statistical Mechanics and Its Applications. 2018;509: 536-545. DOI: 10.1016/j.physa.2018.06.069.
[19] Chen D, et al. A behavioral car-following model that captures traffic oscillations. Transportation Research Part B: Methodological. 2012;46(6): 744-761. DOI: 10.1016/j.trb.2012.01.009.
[20] Chen D, et al. On the periodicity of traffic oscillations and capacity drop: the role of driver characteristics. Transportation Research Part B: Methodological. 2014;59: 117-136. DOI: 10.1016/j.trb.2013.11.005.
[21] Yang X, et al. Biomechanics analysis of human walking with load carriage. Technology and Health Care. 2015;23(s2). DOI: 10.3233/THC-150995.
[22] Lajunen T, Summala H. Can we trust self-reports of driving? Effects of impression management on driver behaviour questionnaire responses. Transportation Research Part F: Psychology and Behaviour. 2003;6(2): 97-107. DOI: 10.1016/S1369-8478(03)00008-1.
[23] Pesti G, et al. Simulation of weaving traffic between freeway ramps. Transportation Research Board 90th Annual Meeting, 23-27 Jan. 2011, Washington DC, United States. 2011.
[24] Rong J, Mao K, Ma J. Effects of individual differences on driving behavior and traffic flow characteristics. Transportation Research Record. 2011;2248:1-9. DOI: 10.3141/2248-01.
[25] Mirbaha B, Kordani AA, Salehikalam A, Zarei M. Analyzing stop time phase leading to congestion based on drivers' behavior patterns. Tarrahan Parseh Transportation Research Institute. 2018;(4). doi: 10.22119/IJTE.2018.49734.
[26] Wang J, Chai R, Xue X. The effects of stop-and-go wave on the immediate follower and change in driver characteristics. Procedia Engineering. 2016;137: 289-298. DOI: 10.1016/j.proeng.2016.01.261.
[27] Saifuzzaman M, Zheng Z, Haque MM, Washington S. Understanding the mechanism of traffic hysteresis and traffic oscillations through the change in task difficulty level. Transportation Research Part B: Methodological. 2017;105: 523-538. DOI: 10.1016/j.trb.2017.09.023.
[28] Deng H, Zhang HM. On traffic relaxation, anticipation, and hysteresis. Transportation Research Record. 2015;2491(1): 90-97. DOI: 10.3141/2491-10.
[29] Laval JA. Hysteresis in traffic flow revisited: An improved measurement method. Transportation Research Part B: Methodological. 2010;45(2): 385-391. DOI: 10.1016/j.trb.2010.07.006.
[30] Chen D, Ahn S. Capacity-drop at extended bottlenecks: Merge, diverge, and weave. Transportation Research Part B: Methodological. 2018;108(2): 1-20. DOI: 10.1016/j.trb.2017.12.006.