为评估交通管控策略的环境效益,提出有效融合微观交通仿真模型和微观车辆排放模型的方法.利用VISSIM平台构建案例微观交通仿真模型,提出基于轨迹数据的不同速度区间的加减速特征,应用K-means聚类方法划分4种驾驶行为,通过驾驶特性标定仿真模型全局参数,描述了参数总敏感度以及参数之间相互作用的敏感度.利用DBSCAN(density-based spatial clustering of applications with noise)聚类分析并标定局部参数值,优化了参数标定流程.计算仿真轨迹工况,本地化MOVES(motor vehicle emission simulator)微观排放模型,得到交叉口不同流向和不同驾驶行为下的HC、CO、NOx、CO2排放.研究表明:仿真模型优化效果显著,所提方法可精确识别高排放的空间位置,解析排放与驾驶行为之间的联系.应用DBSCAN聚类分析参数寻优值有助于实现自动化标定流程,全局参数标定将速度分布χ2 误差由0.632 7降至0.130 6,加速度分布χ2 误差由0.144 1降至0.052 8,对于环境视角下仿真模型构建至关重要.
Optimization of Urban Traffic Microsimulation Model for Carbon Emission Reduction
To assess the environmental benefits of transportation management or control strategies,a method to effectively integrate the micro-traffic simulation model and the micro-vehicle emission model is proposed.VISSIM platform is used to build a case micro traffic simulation model.K-means clustering method is used to divide the driving behavior into 4 types based on the acceleration and deceleration characteristics of different speed intervals of the trajectory data,and the global parameters of the simulation model are calibrated based on the driving characteristics,which quantitatively describe the total sensitivity of the parameters and the sensitivity of the interactions between the parameters.The local parameter values are analyzed and calibrated by density-based spatial clustering of applications with noise(DBSCAN)clustering,which optimize the parameter calibration process.The simulated trajectory conditions are calculated,and motor vehicle emission simulator(MOVES)micro-emission model is localized.The emissions of HC,CO,NOx,and CO2 pollutants under different flow directions and different driving behaviors at the intersection are obtained.Research results show that the optimization effect of the simulation model is remarkable.The proposed method can accurately identify the high-emission spatial locations and resolve the link between emissions and driving behavior.The application of DBSCAN cluster analysis parameter optimization value is conducive to the realization of the automatic calibration process.The calibration of global parameters reduces the χ2 of velocity distribution from 0.632 7 to 0.130 6,and the χ2 of acceleration distribution from 0.144 1 to 0.052 8,which is very important for the construction of simulation model from the environmental perspective.
NETL
NSTL
万方数据
