一种时空路径支持下的车辆油耗与排放估计方法

摘要

交通运输中能耗与污染物排放给人类环境带来了严峻挑战.本文提出了一种时空路径支持下的油耗、排放估计新方法.该方法首先在时空集成的三维坐标系下建立个体车辆的时空路径并从中识别移动/停留行为,然后根据时空路径段与提取的运动参数利用COPERT模型估计车辆的油耗和排放,最后提出一种时空路径的N维表达模型,将车辆的运动特征与时空路径段的油耗与排放统一进行可视化.试验中利用武汉市GPS轨迹大数据估计并分析了单辆车与路网片区的油耗与排放,结果显示本文提出的时空路径支持下的车辆油耗与排放估计方法在估计精度与可视化方面优于传统的基于平均速度估计方法,能够更加准确地估计和表达车辆油耗与排放.%The fuel-consumption and emissions from transportation present severe challenges to the human environment.This article proposes a novel approach of space-time path supported estimation for vehicles' fuel-consumption and emissions.In the proposed approach,space-time paths of vehicles are built under space-time integrated 3-dimensions coordinate firstly and mobile activities (MA) and stationary activities (SA) are extracted from these space-time paths.Then the approach estimates the fuel-consumption and emissions from each Space-Time Path Segment (STPS) and the moving parameters with COPERT model.Finally this article presents an N-Dimensional model for visualizing the moving characteristics,fuel-consumption and emissions of each STPS in an integrated frame.In the case study,fuel-consumption and emissions of a single vehicle and an area of road network are estimated and analyzed using GPS trace data.The results show that the space-time path supported approach is superior to the traditional average speed based approach in the aspects of precision and visualization.The proposed fuel-consumption and emissions estimating approach is effective in energy and emissions information acquisition.