吉林大学学报(工学版) ›› 2022, Vol. 52 ›› Issue (11): 2549-2557.doi: 10.13229/j.cnki.jdxbgxb20210395

• 交通运输工程·土木工程 • 上一篇    

基于Lennard-Jones势的车辆跟驰动力学特性及模型

曲大义1(),赵梓旭1,贾彦峰1,王韬1,刘琼辉2   

  1. 1.青岛理工大学 机械与汽车工程学院,山东 青岛 266520
    2.山东公路技师学院,济南 250217
  • 收稿日期:2021-05-06 出版日期:2022-11-01 发布日期:2022-11-16
  • 作者简介:曲大义(1973-),男,教授,博士. 研究方向:交通系统优化. E-mail:dyqu@263.net
  • 基金资助:
    国家自然科学基金项目(52272311)

Car⁃following dynamics characteristics and model based on Lennard⁃Jones potential

Da-yi QU1(),Zi-xu ZHAO1,Yan-feng JIA1,Tao WANG1,Qiong-hui LIU2   

  1. 1.School of Mechanical and Automotive Engineering,Qingdao University of Technology,Qingdao 266520,China
    2.Shandong Institute of Highway Technican,Jinan 250217,China
  • Received:2021-05-06 Online:2022-11-01 Published:2022-11-16

摘要:

为更准确描述道路中前后相邻车辆的跟驰交互行为,利用其与某些微观粒子的热力学表现的相似性,构建车辆跟驰模型。通过系统相似性分析,将车辆类比为狭长管道中的微观粒子,将复杂的车辆跟驰交互行为简化为后车不断寻求与前车保持需求安全距离的动态过程,建立不同情况下的需求安全距离表达式。通过对适用于惰性气体体系热力学分析的Lennard-Jones势函数的数学推导,明确其各变量对势能的影响关系,分析了现有的分子跟驰模型存在的问题。参考Lennard-Jones势函数构建了车辆相互作用势函数,考虑了车道边界产生的道路壁面势的影响,提出了基于Lennard-Jones势的车辆跟驰模型。仿真测试结果表明:对比已有的分子跟驰模型和IDM模型,该模型得出的车辆加速度结果与实际数据的平均绝对误差与均方根误差更低,证明基于Lennard-Jones势的车辆跟驰模型对真实车辆的跟驰行为具有更好的拟合效果。

关键词: 交通工程, 跟驰模型, 分子热力学, Lennard-Jones势, 需求安全距离, 壁面作用势

Abstract:

In order to more accurately describe the car-following interaction behavior of adjacent vehicles on the road, a car-following model is constructed by using its similarity with the thermodynamic performance of some microscopic particles. Through the system similarity analysis, the vehicle is likened to a microscopic particle in a long and narrow pipeline, and the complex vehicle following interaction is simplified into a dynamic process in which the following vehicle constantly seeks to keep a safe distance from the preceding vehicle. The expressions of the safe distance under different conditions are established. Through the mathematical derivation of Lennard-Jones potential function which is suitable for the thermodynamic analysis of inert gas system, the influence of its variables on the potential energy is clarified, and the problems existing in the existing molecular following model are analyzed. The vehicle interaction potential function was constructed by referring to the Lennard-Jones potential function, and the influence of the road wall potential generated by the lane boundary was considered. The vehicle following model based on the Lennard-Jones potential was proposed. The simulation test results show that: Compared with the existing molecular car-following model and IDM model, the mean absolute error and root mean square error of the vehicle acceleration results obtained by this model are lower than the actual data, which proves that the car-following model based on Lennard-Jones potential has a better fitting effect on the real vehicle's car-following behavior

Key words: traffic engineering, car-following model, molecular thermodynamics, Lennard-Jones potential, demand safety distance, wall potential

中图分类号: 

  • U491

图1

分子间距与其相互作用力"

图2

跟驰车辆的受力状况"

图3

狭长管道中的气体分子"

图4

Lennard-Jones势函数"

表1

GLM模型参数标定结果"

参数标定值
m0.7103
n1.6754
λ129.2322
λ244.4901

表2

M-MD模型参数标定结果"

运动状态λ1λ2
常规行驶1.34019.4095
起动加速0.954817.3827
减速停车66.50290.0141

表3

IDM模型参数标定结果"

参数标定值
a/(m·s-21
b/(m·s-22
v0/(m·s-133.3
s0/m10
T/s1.5

图5

模型仿真时间-轨迹图"

图6

模型仿真时间-轨迹图"

表4

模型误差对比"

模 型MAERMSE
M-MD1.48670.7473
IDM0.80040.5982
GLM0.37720.5240
1 Gazis D C, Herman R, Rothery R W. Nonliner following-the-leader models of traffic flow[J]. Operations Research, 1961, 9(4): 545-567.
2 Bando M, Hasebe K, Nakayama A, et al. Dynamical model of traffic congestion and numerical simulation[J]. Physical Review E, 1995, 51(2): 1035-1042.
3 Helbing D, Tilch B. Generalized force model of traffic dynamics[J]. Physical Review E, 1998, 58(1): 133-138.
4 Jiang R, Wu Q S, Zhu Z J. Full velocity difference model for a car-following theory[J]. Physical Review E, 2001, 64(12): 017101.
5 曲昭伟,潘昭天,陈永恒, 等. 基于最优速度模型的改进安全距离跟驰模型[J]. 吉林大学学报: 工学版, 2019, 49(4): 1092-1099.
Qu Zhao-wei, Pan Zhao-tian, Chen Yong-heng, et al. Car-following model with improving safety distance based on optimal velocity model[J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(4): 1092-1099.
6 陈秀锋. 基于分子动力学的车辆运行安全特性研究[D]. 长春: 吉林大学交通学院, 2013.
Chen Xiu-feng. A study on vehicle operating safety characteristics based on molecular dynamics[D]. Changchun: College of Transportation, Jilin University, 2013.
7 曲大义,杨建,陈秀锋,等.车辆跟驰的分子动力学特性及其模型[J]. 吉林大学学报: 工学版, 2012, 42(5): 1198-1202.
Qu Da-yi, Yang Jian, Chen Xiu-feng, et al. Molecular kinetics behavior of car-following and its model[J]. Journal of Jilin University(Engineering and Technology Edition), 2012, 42(5) :1198-1202.
8 曲大义, 邴其春, 贾彦峰, 等. 基于分子动力学的车辆换道交互行为特性及其模型[J]. 交通运输系统工程与信息, 2019, 19(3): 68-74.
Qu Da-yi, Bing Qi-chun, Jia Yan-feng, et al. Molecular dynamics characteristics and models of vehicle lane changing interaction behavior[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(3) :68-74.
9 Wolf M T, Burdick J W. Artificial potential functions for highway driving with collision avoidance[C]∥IEEE International Conference on Robotics and Automation, California, America, 2008: 3731-3736.
10 李林恒, 甘婧, 曲栩, 等. 智能网联环境下基于安全势场理论的车辆跟驰模型[J]. 中国公路学报, 2019, 32(12): 76-87.
Li Lin-heng, Gan Jing, Qu Xu, et al. Car-following model based on safety potential field theory under connected and automated vehicle environment[J]. China Journal of Highway and Transport, 2019, 32(12): 76-87.
11 李娟,曲大义,刘聪,等.基于分子动力学的跟驰特性及其模型[J].公路交通科技, 2018, 35(3): 126-131.
Li Juan, Qu Da-yi, Liu Cong, et al. Car-following characteristics and its models based on molecular dynamics[J]. Journal of Highway and Transportation Research and Development, 2018, 35(3): 126-131.
12 杨龙海,王晖,李帅, 等. 改进分子动力学的车辆跟驰模型[J]. 重庆大学学报, 2021, 44(7): 26-33.
Yang Long-hai, Wang Hui, Li Shuai, et al. Improved molecular dynamics car-following model[J]. Journal of Chongqing University,2021,44(7): 26-33.
13 曹炳阳, 陈民, 过增元. 纳米通道滑移流动的分子动力学研究[J]. 工程热物理学报, 2003(4): 670-672.
Cao Bing-yang, Chen Min, Guo Zeng-yuan. Molecular dynamics studies of slip flow in nanochannel[J] Journal of Engineering Thermophysics, 2003(4): 670-672.
14 Lennard-Jones J E. Cohesion[J]. Proceedings of the Physical Society, 1931, 43(5): 461-482.
15 Wang X, Ramírez-Hinestrosa S, Dobnikar J, et al. The Lennard-Jones potential: when (not) to use it[J]. Physical Chemistry Chemical Physics, 2020, 22(19): 10624-10633.
16 Ferguson D M, Kollman P A. Can the Lennard-Jones 6‐12 function replace the 10‐12 form in molecular mechanics calculations [J]. Journal of Computational Chemistry, 1991, 12(5): 620-626.
17 王涛, 高自友, 赵小梅. 多速度差模型及稳定性分析[J]. 物理学报, 2006(2): 634-640.
Wang Tao, Gao Zi-you, Zhao Xiao-mei. Multiple velocity difference model and its stability analysis[J]. Acta Physica Sinica, 2006(2): 634-640.
18 王殿海, 陶鹏飞, 金盛, 等. 跟驰模型参数标定及验证方法[J]. 吉林大学学报: 工学版, 2011, 41(): 59-65.
Wang Dian-hai, Tao Peng-fei, Jin Sheng, et al. Method of calibrating and validating car-following model[J]. Journal of Jilin University(Engineering and Technology Edition), 2011, 41(Sup.1): 59-65.
19 Montanino M, Punzo V. Making NGSIM data usable for studies on traffic flow theory: multistep method for vehicle trajectory reconstruction[J]. Transportation Research Record, 2013(1): 99-111.
20 鲁斌. 基于数据驱动方法的车辆跟驰行为建模与分析[D]. 成都: 西南交通大学交通运输与物流学院, 2017.
Lu Bin. Modeling and analysis of car-following behavior using data-driven methods[D]. Chengdu: College of Transportation and Logistics, Southwest Jiaotong University, 2017.
21 罗亚中, 袁端才, 唐国金. 求解非线性方程组的混合遗传算法[J]. 计算力学学报, 2005(1): 109-114.
Luo Ya-zhong, Yuan Duan-cai, Tang Guo-jin. Hybrid genetic algorithm for solving systems of nonlinear equations[J]. Chinese Journal of Computational Mechanics, 2005(1): 109-114.
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