智能网联客货混合交通流特性及集聚换道策略

doi:10.13229/j.cnki.jdxbgxb.20231205

Abstract

Abstract:

To study the characteristics of passenger-cargo mixed traffic flow in vehicle-connected environment and the lane change strategy suitable for the mixed traffic flow environment， the relative entropy is introduced to quantify the order of passenger-cargo mixed traffic flow， and on this basis， conditional agglomeration lane change strategy is proposed. The effect of conditional lane change strategy on the capacity and order of mixed traffic flow was studied by cellular automata simulation. The results show that compared with non-agglomeration lane change strategy， CDA（Conditional aggregation） lane change strategy can improve the maximum road capacity by 5.5%~10.5% in mixed traffic flow with different CAV（Connected and autonomous vehicle） penetration rate and passenger-cargo ratio. It can significantly reduce the relative entropy of traffic flow， increase the number of vehicles in CACC（Cooperative adaptive cruise control） queue and improve the orderliness of traffic flow. When the CACC minimum queue size of the conditional lane change strategy is 4~5 vehicles， the road capacity can be improved the most.

Key words: intelligent transportation, connected and autonomous vehicle, lane change strategy, heterogeneous traffic flow, numerical simulation, relative entropy

CLC Number:

U495

De-hua WU,Rong-feng CHEN. Characteristics of passenger-cargo mixed traffic flow in intelligent network and agglomeration lane-change strategy[J].Journal of Jilin University(Engineering and Technology Edition), 2025, 55(8): 2588-2596.

Figures/Tables 10

Fig.1

Fig.2

Fig.3

Table 1

Values of IDM parameters"

参数	取值
$a m a x / (m · s - 2)$	1
$v f / (m · s - 1)$	33.3
$s 0 / m$	2
$b / (m · s - 2)$	2

Table 1

Fig.4

Fig.5

Table 2

Fig.6

Fig.7

Fig.8

References 19

[1]	单肖年, 万长薪, 李志斌, 等. 智能网联环境下多车道异质交通流建模与仿真[J]. 交通运输系统工程与信息, 2022, 22(6): 74-84.
	Shan Xiao-nian, Wan Chang-xin, Li Zhi-bin, et al. Modeling and simulation of multi-lane heterogeneous traffic flow in intelligent and connected vehicle environment[J]. Journal of Transportation Systems Engineering and Information Technology, 2022, 22(6): 74-84.
[2]	Qin Y Y, Tang H H, Yang J Y, et al. Analysis on road capacity of connected vehicle platoon on mixed traffic flow[J]. Journal of Beijing Jiaotong University, 2022, 46(1): 79-87.
[3]	Vranken T, Sliwa B, Wietfeld C, et al. Adapting a cellular automata model to describe heterogeneous traffic with human-driven, automated, and communicating automated vehicles[J]. Physica A: Statistical Mechanics and its Applications, 2021, 570: No. 125792.
[4]	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: No. 102874.
[5]	Zheng Y, Ran B, Qu X, et al. Cooperative lane changing strategies to improve traffic operation and safety nearby freeway off-ramps in a connected and automated vehicles environment[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(11): 4605-4614.
[6]	严永俊, 彭林, 王金湘, 等. 混驾环境下基于主从博弈的多车协同决策规划[J]. 中国公路学报, 2024, 37(3): 117-133.
	Yan Yong-jun, Peng Lin, Wang Jin-xiang, et al. Multi-vehicle cooperative decision-making and trajectory planning based on stackelberg game theory in mixed driving environments[J]. China Journal of Highway and Transport, 2024, 37(3): 117-133.
[7]	杜思雨, 赵清海, 何田. 基于博弈论的智能网联汽车换道决策模型研究[J/OL]. 复杂系统与复杂性科学: 1-9[2025-06-06]..
[8]	梁军, 李燕青, 王文飒, 等. 智能网联环境下CAV混行车流集聚策略及分析[J]. 华中科技大学学报: 自然科学版, 2024, 52(1): 118-125.
	Liang Jun, Li Yan-qing, Wang Wen-sa, et al. Agglomeration strategy and analysis of CAV mixed traffic flow in intelligent and connected environment [J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2024, 52(1): 118-125.
[9]	梁军, 耿浩然, 陈龙, 等. 融入公交车与自动驾驶车队的异质交通流模型[J]. 西南交通大学学报, 2023, 58(5): 1090-1099.
	Liang Jun, Geng Hao-ran, Chen Long, et al. Integrated heterogeneous traffic flow model of bus and autonomous vehicle platoon[J]. Journal of Southwest Jiaotong University, 2023, 58(5): 1090-1099.
[10]	曹丹妮, 吴建军, 屈云超, 等. 考虑自动车队强度的高速公路非常规瓶颈交通流控制策略研究 [J]. 中国公路学报, 2022, 35(3): 78-88.
	Cao Dan-ni, Wu Jian-jun, Qu Yun-chao, et al. Analysis of traffic flow control strategy at non-recurrent bottleneck on freeway considering platoon intensity of connected and automated vehicles[J]. China Journal of Highway and Transport, 2022, 35(3): 78-88.
[11]	Zhou Y J, Zhu H B, Guo M M, et al. Impact of CACC vehicles' cooperative driving strategy on mixed four-lane highway traffic flow[J]. Physica A: Statistical Mechanics and its Applications, 2020, 540: No. 122721.
[12]	梁军, 杨程灿, 王文飒, 等. 自动驾驶车辆混行集聚MAS控制模型[J]. 中国公路学报, 2021, 34(6): 172-183.
	Liang Jun, Yang Cheng-can, Wang Wen-sa, et al. Agglomeration control model based on multi-agents for autonomous vehicles in mixed traffic environment [J]. China Journal of Highway and Transport, 2021, 34(6): 172-183.
[13]	吴德华, 彭锐, 陈荣峰. 异质流网联车的不同换道集聚策略[J]. 西南交通大学学报, 2023, 58(2): 348-356.
	Wu De-hua, Peng Rui, Chen Rong-feng. Hybrid characteristics of heterogeneous traffic flow in intelligent network[J]. Journal of Southwest Jiaotong University, 2023, 58(2): 348-356.
[14]	Liu Z P, Xu C X, Chen L J, et al. Dynamic traffic flow entropy calculation based on vehicle spacing[J]. IOP Conference Series: Earth and Environmental Science, 2019, 252(5): No. 052073.
[15]	吴德华, 彭锐, 林熙玲. 智能网联异质交通流混合特性[J]. 西南交通大学学报, 2022, 57(4): 761-768.
	Wu De-hua, Peng Rui, Lin Xi-ling. Hybrid characteristics of heterogeneous traffic flow in intelligent network[J]. Journal of Southwest Jiaotong University, 2022, 57(4): 761-768.
[16]	Nagel K, Schreckenberg M. A cellular automaton model for freeway traffic[J]. Journal De Physique I, 1992, 2: 2221-2229.
[17]	Treiber M, Hennecke A, Helbing D. Congested traffic states in empirical observations and microscopic simulations[J]. Physical Review E, Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, 2000, 62: 1805-1824.
[18]	Milanés V, Shladover S E. Modeling cooperative and autonomous adaptive cruise control dynamic responses using experimental data[J]. Transportation Research Part C. Emerging Technologies, 2014, 48: 285-300.
[19]	李瑞杰, 李林波, 李杨, 等. 跟驰模型场景基准分析 [J]. 同济大学学报: 自然科学版, 2021, 49(7): 922-932.
	Li Rui-jie, Li Lin-bo, Li Yang, et al. Scenario-based benchmark analysis for car-following models [J]. Journal of Tongji University (Natural Science), 2021, 49(7): 922-932.

Related Articles 15

[1]	Yong ZHAO,Wen-ming JIN,Qi-feng ZHENG,Shu-qing KOU. Influence of cracking groove depth on cracking performance of bearing seat of reducer housing [J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(5): 1552-1558.
[2]	Yue HOU,Jin-song GUO,Wei LIN,Di ZHANG,Yue WU,Xin ZHANG. Multi-view video speed extraction method that can be segmented across lane demarcation lines [J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(5): 1692-1704.
[3]	Sheng JIANG,Yi-di WANG,Rui-lin XIE,Miao-lei XIA. Traffic accident anticipation baed on spatial-temporal relational learning and convolutional gated recurrent network [J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(3): 954-962.
[4]	Qi-liang ZHU,Xue-ting YU. k⁃prototype clustering algorithm and privacy protection for sensitive data republishing under relative entropy [J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(3): 1009-1014.
[5]	Li LI,Yu-jian BAO,Wen-chen YANG,Qing-ling CHU,Gui-ping WANG. Standardized constructing method of a roadside multi-source sensing dataset [J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(2): 529-536.
[6]	Chang-shuai WANG,Cheng-cheng XU,Wei-lin REN,Chang PENG,Hao TONG. Impacts of driving ability recovery state on characteristics of traffic oscillation in automated driving takeover process [J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(1): 150-161.
[7]	Jin-xing WU,Yu-xiang MA,Jia-bang XIAO,Yao XU,Song-ge LI. Numerical simulation of erosion characteristics of H-type finned elliptical tubes [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(9): 2495-2501.
[8]	Nan YANG,Jun XIAO. Energy saving optimization control of urban intelligent transportation under sequential quadratic programming algorithm [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(8): 2223-2228.
[9]	Li LI,Xiao-qiang WU,Wen-chen YANG,Rui-jie ZHOU,Gui-ping WANG. Target recognition and tracking of group vehicles based on roadside millimeter-wave radar [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(7): 2104-2114.
[10]	Hua-fei HE,Zhao-ping LI,Rui-an FU,Shao-lin MA,Ming-li HUANG. Experiment on seismic performance of prefabricated sidewall joints considering strata restraint effect [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(6): 1601-1611.
[11]	Shu-mei LOU,Yi-ming LI,Xin LI,Peng CHEN,Xue-feng BAI,Bao-jia CHENG. Thermal deformation behavior of graphene nanosheets reinforced 7075Al based on BP neural network and Arrhenius constitutive equation [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(5): 1237-1245.
[12]	Xiu-jian YANG,Xiao-han JIA,Sheng-bin ZHANG. Characteristics of mixed traffic flow taking account effect of dynamics of vehicular platoon [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(4): 947-958.
[13]	Qiu ZHAO,Peng CHEN,Yu-wei ZHAO,Ao YU. Overall mechanical performance of jointless bridges with arch structure behind abutment [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(4): 1016-1027.
[14]	Wei-hua ZHANG,Jia-ming LIU,Li-peng XIE,Heng DING. Lane⁃changing model of autonomous vehicle in weaving area of expressway in intelligent and connected mixed environment [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(2): 469-477.
[15]	Yi-gang WANG,Yu-peng WANG,Hao ZHANG,Si-an ZHAO. Identification and analysis of aerodynamic noise sources in the bogie area of high⁃speed trains [J]. Journal of Jilin University(Engineering and Technology Edition), 2024, 54(2): 346-355.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

换道策略	p=0.2	p=0.4	p=0.6	p=0.8
CVA	-1.0	1.3	2.6	1.8
CDA	-0.1	5.7	7.3	7.0

Characteristics of passenger-cargo mixed traffic flow in intelligent network and agglomeration lane-change strategy

RICH HTML

PDF (PC)