深圳大学学报（理工版）2024，Vol.41Issue(4)：415-422,8.DOI:10.3724/SP.J.1249.2024.04415
考虑异质交通流的随机参数优化速度跟驰模型
Stochastic parameter-optimized car-following model considering heterogeneous traffic flow
摘要
Abstract
In order to examine the impact of traffic flow heterogeneity on vehicle following behavior,we propose an improved optimized speed function based on the stochastic parametric linear regression method.The speed-density data for traffic flow are categorized using quantile regression.Random parameter linear regression is then applied to each data category,resulting in improved optimal velocity function and hypothesis testing for each category.The stochastic optimal velocity car-following model is developed by integrating the enhanced optimal velocity function with full velocity difference car-following model.The stability of the car-following model is analyzed by applying Fourier transform theory.Numerical experiments on the car-following model are conducted through a simulation platform for circular lanes.The results indicate that categorization reduces the error of the random parameter model by 28% compared to the model without categorization.Additionally,the speed of the random parameter car-following fleet increases with the addition of 0.5 quantile vehicles.The random parameter car-following model fleet is better suited to reflect the impact of traffic flow heterogeneity on the fleet than the fixed parameter car-following model fleet.The model can enhance the simulation aspect and accurately depict the intricate functioning of traffic flow.关键词
交通工程/交通流理论/分位数回归/随机参数线性回归/优化速度函数/跟驰模型/稳定性分析Key words
traffic engineering/traffic flow theory/quantile regression/random parameter linear regression/optimal velocity function/car-following model/stability analysis分类
交通工程引用本文复制引用
潘义勇,全勇俊,管星宇..考虑异质交通流的随机参数优化速度跟驰模型[J].深圳大学学报（理工版）,2024,41(4):415-422,8.基金项目
National Natural Science Foundation of China(51508280) （51508280）
High Education Talents Foundation of Nanjing Forestry University(GXL2014031) 国家自然科学基金资助项目(51508280) （GXL2014031）
南京林业大学高学历人才基金资助项目(GXL2014031) （GXL2014031）
