中文摘要：

针对交通系统易于收集到的平均速度,以及排放模型计算所需的运行模式分布参数,建立基于平均速度的运行模式分布模型,并采用遗传算法对模型进行优化.对比所建立模型、MOVES模型中的行驶周期所获取数据与真实数据之间的排放结果差异,发现本模型有82.5%的区间平均排放率预测误差低于MOVES,本模型的最大误差为50.0%,而MOVES模型为304.2%.使用本模型评价了北京市限行前后污染物排放情况,发现限行后二环路高峰小时HC、CO、NOx总体排放依次减少了9.58%、11.41%、0.49%.与真实值相比,预测值R2方高于0.700,预测误差大幅度低于MOVES模型预测误差,并实现对交通策略下路网排放的动态评价应用.

英文摘要：

In view of the widely available data of the average speed in traffic systems and the parameter of operating modedistribution needed in emission models,a model was developed for generating operating mode distribution based on theaverage speed.Genetic Algorithm was used further for optimizing the model.After a comparison with the real-world data,it was found that the average emission rates estimated based on the proposed model exhibited less errors than thoseestimated based on MOVES in82.5%of the speed bins.The highest error based on the proposed model was50%while304.2%based on MOVES.Finally,the proposed model was used to estimate emissions in Beijing for pre-and after-theimplementation of the vehicle restriction policy.It was found that the2nd Ring Road has experienced a reduction of totalemissions of HC,CO,NOx by9.58%,11.41%,0.49%respectively.Compare with the test values,the R2with the modelwere higher than0.700and errors of the model were much lower than that of the MOVES.Further a modal applicationwas proposed,which can calculate the traffic exhaust emissions of dynamic network.