Evaluation of vehicle emissions models for micro-simulation modelling: Using CO_2 as a case study

摘要

There is a need to match emissions estimation to the accuracy levels of confidence in the outputs of transport models. The overall error in 20 year traffic forecasts resulting from strategic transport models is likely to be at least 20% to 25%. Micro-simulation models, although more detailed in nature, may have similar measurement errors if they use the outputs of strategic models to obtain traffic demand predictions. Macro-level models based on average vehicle speeds may not be appropriate for use at a more localised and detailed level at whichvehicle speed profiles may change significantly. Emission rates for a number of vehicles were compared using Australian data based on dynamometer testing. The results revealed that only CO_2 showed a strong correlation with average speed. All other pollutants showed very low levels of correlation. An evaluation of several micro-level emissions models has been undertaken by applying them to the results of Australian vehicle emissions measured in the field. In total, six different models have been analysed and the results compared. Power-based models have some significant shortcomings, and their use is not consistent with our finding that there are significant variations in emissions for small changes in vehicle power. The results highlight the need to model acceleration, deceleration and cruising stages of the urban cycle separately. A speed-based approach, such as that followed by the AIMSUN traffic simulation model, was found to have merit based on the evaluation results discussed here.