面向排放测算的随机性对跟驰模型车队稳定性的影响研究
Impact of stochasticity on platoon stability of car-following models for emissions estimation
孟冬利 1宋国华 1鲁洪语 2吴亦政 1翟志强 1于雷3
作者信息
- 1. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport,Beijing Jiaotong University,Beijing 100044,China
- 2. School of Civil and Environmental Engineering,Georgia Institute of Technology,Atlanta,GA 30332,USA
- 3. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport,Beijing Jiaotong University,Beijing 100044,China;Department of Transportation Studies,Texas Southern University,Houston,TX 77004,USA
- 折叠
摘要
在基于微观交通仿真模型进行交通能耗排放评估时,跟驰模型生成的车辆轨迹无法代表实际交通环境的驾驶特性,从而导致显著的排放测算误差,同时车辆排放在车队中的稳定性未被充分考虑.本文基于真实的车队轨迹比较了Gipps跟驰模型、全速差模型(FVDM)、智能驾驶员模型(IDM)和Wiedemann模型的面向排放测算的车队稳定性,分析了参数敏感性和随机性对跟驰模型的影响,提出了考虑随机参数的Gipps跟驰模型.结果表明,与Wiedemann模型相比,FVD模型和IDM模型在排放测算方面的误差较小,并且上述三个模型的排放测算误差沿车队是稳定的.Gipps模型能够真实地刻画车队中第一辆跟驰车的车辆动力学,但排放测算误差沿车队逐渐增大.参数敏感性分析表明模型参数标定难以提高Gipps模型的车队稳定性.结合随机参数对Gipps跟驰模型进行优化后,加速度分布均方根误差、VSP分布均方根误差和排放因子相对误差分别降低了5.00%、2.52%和11.04%,车队误差的标准差分别为0.18%、0.08%和0.86%,这表明随机参数能够提高Gipps跟驰模型面向排放测算的车队稳定性,提升仿真轨迹用于车辆能耗排放评估的准确性.
Abstract
In the application of microscopic traffic simulations for vehicle emissions modeling,the reality and platoon stability of vehicle trajectories derived from the car-following component have been questioned.This study compared the platoon stability of the Gipps car-following model,the full velocity difference model(FVDM),the intelligent driver model(IDM),and the Wiedemann model for emissions modeling and proposed the modified Gipps model by incorporating stochastic parameters.The results indicated the superior performance of the FVDM and IDM for emissions estimation compared with the Wiedemann model,and the emissions estimation errors were stable along the platoon for the above models.Gipps model generated realistic vehicle dynamics of the first following vehicle;however,the emissions estimation errors increased along the platoon.After the optimization of the Gipps model by incorporating stochastic parameters,the root-mean-square error(RMSE)of acceleration distribution,RMSE of vehicle specific power(VSP)distribution and relative error of emission factor were reduced by 5.00%,2.52%and 11.04%,respectively,and the standard deviations of the errors in the platoon were 0.18%,0.08%and 0.86%,respectively.The stochastic parameters were proven to potentially improve the reality of simulated trajectory and the platoon stability of the Gipps model for accurate emissions modeling.
关键词
跟驰模型/车队稳定性/随机性/排放测算/VSP分布Key words
car-following model/platoon stability/stochasticity/emissions estimation/VSP distribution引用本文复制引用
基金项目
National Natural Science Foundation of China(71871015)
National Natural Science Foundation of China(71901018)
出版年
2023
NETL
NSTL
维普
万方数据