[1]秦严严,王昊,王炜.网联辅助驾驶混合交通流稳定性及安全性分析[J].东南大学学报(自然科学版),2018,48(1):188-194.[doi:10.3969/j.issn.1001-0505.2018.01.029]
 Qin Yanyan,Wang Hao,Wang Wei.Analysis on stability and safety for mixed traffic flow with connected auxiliary driving[J].Journal of Southeast University (Natural Science Edition),2018,48(1):188-194.[doi:10.3969/j.issn.1001-0505.2018.01.029]
点击复制

网联辅助驾驶混合交通流稳定性及安全性分析()
分享到:

《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
48
期数:
2018年第1期
页码:
188-194
栏目:
交通运输工程
出版日期:
2018-01-20

文章信息/Info

Title:
Analysis on stability and safety for mixed traffic flow with connected auxiliary driving
作者:
秦严严王昊王炜
东南大学交通学院, 南京 210096; 东南大学城市智能交通江苏省重点实验室, 南京 210096; 东南大学现代城市交通技术江苏高校协同创新中心, 南京 210096
Author(s):
Qin Yanyan Wang Hao Wang Wei
School of Transportation, Southeast University, Nanjing 210096, China
Jiangsu Key Laboratory of Urban ITS, Southeast University, Nanjing 210096, China
Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 210096, China
关键词:
混合交通流 稳定性分析 交通安全 网联辅助驾驶
Keywords:
mixed traffic flow stability analysis traffic safety connected auxiliary driving
分类号:
U491
DOI:
10.3969/j.issn.1001-0505.2018.01.029
摘要:
针对常规人工驾驶车辆和网联辅助驾驶车辆随机混合的交通流,分析其稳定性与安全性.基于紧跟常规车的网联车退化为常规车的跟驰特性,提出了网联车随机退化为常规车情形的数学期望表达式,进而建立网联车混合交通流稳定性的一般性分析方法.选取全速度差模型和智能驾驶员模型分别作为常规车和网联车跟驰模型,进行混合交通流稳定性案例分析,考虑常规车与网联车相对数量及相对空间位置的随机性,设计上匝道瓶颈交通安全影响的数值仿真实验.研究结果表明,网联车有助于提升交通流稳定性与安全性,平衡态速度越接近9.8~10.6 m/s速度范围,混合交通流满足稳定状态所需的网联车市场率临界值越大;当网联车市场率大于0.37时,混合交通流可在任意平衡态速度下稳定;相比于常规车交通流,网联车交通流的交通安全水平可提高54.29%~71.36%.
Abstract:
Focusing on the traffic flow randomly mixed with regular manual driven vehicles and connected auxiliary driven vehicles, the stability and the safety are analyzed. A mathematical expectation is proposed for the case of degeneration from the connected vehicles to regular vehicles, based on the car-following characteristics of connected vehicles that follow regular vehicles and degenerate to regular vehicles. Then, a generalized method for stability analysis of the mixed traffic flow with connected vehicles is built. The full velocity difference model and the intelligent driver model are selected as the car-following models of regular and connected vehicles, respectively. Based on this, a case study of stability of the mixed traffic flow is analyzed. Additionally, numerical simulations are designed for the traffic safety impacts on the on-ramp bottleneck, considering the randomness of relative numbers and spatial locations of regular and connected vehicles. Research results show that the connected vehicles are helpful to improve traffic flow stability and safety. The critical value of the connected vehicle market rate, which must satisfy the needs of stable state of the mixed traffic flow, is larger when the equilibrium speed is closer to the speed range from 9.8 to 10.6 m/s. Moreover, the mixed traffic flow can be stable at any equilibrium speed if the connected vehicle market rate is greater than 0.37. Besides, the traffic flow of the connected vehicles can promote the safety level by 54.29% to 71.36%, compared with the traffic flow of regular vehicles.

参考文献/References:

[1] Mahmassani H S. 50th anniversary invited article—Autonomous vehicles and connected vehicle systems:Flow and operations considerations[J]. Transportation Science, 2016, 50(4): 1140-1162. DOI:10.1287/trsc.2016.0712.
[2] 郭孜政, 潘毅润, 潘雨帆, 等. 基于EEG熵值的驾驶员脑力负荷水平识别方法[J]. 东南大学学报(自然科学版), 2015, 45(5): 980-984. DOI: 10.3969/j.issn.1001-0505.2015.05.028.
Guo Zizheng, Pan Yirun, Pan Yufan, et al. Recognition method of driving mental workload based on EEG entropy[J]. Journal of Southeast University(Natural Science Edition), 2015, 45(5): 980-984. DOI:10.3969/j.issn.1001-0505.2015.05.028. (in Chinese)
[3] Liu H, Wei H, Zuo T, et al. Fine-tuning ADAS algorithm parameters for optimizing traffic safety and mobility in connected vehicle environment[J]. Transportation Research Part C: Emerging Technologies, 2017, 76: 132-149. DOI:10.1016/j.trc.2017.01.003.
[4] Shladover S E, Nowakowski C, Lu X Y, et al. Cooperative adaptive cruise control: Definitions and operating concepts[J]. Transportation Research Record: Journal of the Transportation Research Board, 2015,2489: 145-152.
[5] 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. DOI:10.1016/j.trb.2017.01.017.
[6] 秦严严, 王昊, 王炜, 等. 自适应巡航控制车辆跟驰模型综述[J]. 交通运输工程学报, 2017, 17(3): 121-130. DOI:10.3969/j.issn.1671-1637.2017.03.013.
Qin Yanyan, Wang Hao, Wang Wei, et al. Review of car-following models of adaptive cruise control[J]. Journal of Traffic and Transportation Engineering, 2017, 17(3): 121-130. DOI:10.3969/j.issn.1671-1637.2017.03.013. (in Chinese)
[7] Talebpour A, Mahmassani H S. Influence of connected and autonomous vehicles on traffic flow stability and throughput[J]. Transportation Research Part C: Emerging Technologies, 2016, 71: 143-163. DOI:10.1016/j.trc.2016.07.007.
[8] Wang J Q, Xiong C F, Lu M, et al. Longitudinal driving behaviour on different roadway categories: An instrumented-vehicle experiment, data collection and case study in China[J]. IET Intelligent Transport Systems, 2015, 9(5): 555-563. DOI:10.1049/iet-its.2014.0157.
[9] Ward J A. Heterogeneity, lane-changing and instability in traffic: a mathematical approach[D]. Bristol, UK: University of Bristol, 2009.
[10] Jiang R, Wu Q, Zhu Z. Full velocity difference model for a car-following theory[J]. Physical Review E, 2001, 64(1): 017101. DOI:10.1103/PhysRevE.64.017101.
[11] Wang H, Wang W, Chen J, et al. Estimating equilibrium speed-spacing relationship from dynamic trajectory data[C]//Transportation Research Board 91st Annual Meeting. Washington, DC, USA, 2012: 1-18.
[12] Treiber M, Hennecke A, Helbing D. Congested traffic states in empirical observations and microscopic simulations[J]. Physical Review E, 2000, 62(2): 1805-1824. DOI:10.1103/physreve.62.1805.
[13] Minderhoud M M, Bovy P H L. Extended time-to-collision measures for road traffic safety assessment[J]. Accident Analysis & Prevention, 2001, 33(1): 89-97. DOI:10.1016/s0001-4575(00)00019-1.

相似文献/References:

[1]谭福颖,乔玲,韩晓林.基于广义梁理论的薄壁圆柱壳稳定性分析[J].东南大学学报(自然科学版),2013,43(5):1062.[doi:10.3969/j.issn.1001-0505.2013.05.027]
 Tan Fuying,Qiao Ling,Han Xiaolin.Stability analysis of thin-walled cylindrical shells based on generalised beam theory[J].Journal of Southeast University (Natural Science Edition),2013,43(1):1062.[doi:10.3969/j.issn.1001-0505.2013.05.027]

备注/Memo

备注/Memo:
收稿日期: 2017-06-14.
作者简介: 秦严严(1989—),男,博士生;王昊(联系人),男,博士,教授,博士生导师,haowang@seu.edu.cn.
基金项目: 国家自然科学基金面上资助项目(51478113)、江苏省研究生科研与实践创新计划资助项目(KYCX17-0146).
引用本文: 秦严严,王昊,王炜.网联辅助驾驶混合交通流稳定性及安全性分析[J].东南大学学报(自然科学版),2018,48(1):188-194. DOI:10.3969/j.issn.1001-0505.2018.01.029.
更新日期/Last Update: 2018-01-20