双碳场景下机动车管控单元识别及碳减排模型——以苏州古城为例

VEHICLE CONTROL UNIT IDENTIFICATION AND DE-CARBONIZATION MODEL UNDER CARBON PEAK AND CARBON NEUTRALITY SCENARIO: TAKING SUZHOU OLD TOWN AS AN EXAMPLE

研究以苏州古城为例,基于现状街坊的管控单元的识别,以街坊交通供需比为指标,以区域平衡和全区域最小交通供需比为约束条件,基于贪心算法,提出了低碳场景下的机动车管控单元识别和碳减排模型。管控单元的识别改变了出行机动车交通量和速度的分布,影响交通碳排放。而碳减排模型则采用速度、车公里和车型作为传导因子,融合交通模型和碳排模型,实现各管控方案下的碳减排计算。将古城现状54个街坊聚类合并为22个机动车管控单元,在采用特定的机动车管控措施后,碳排放降低了17.76%。

Taking Suzhou Old Town as an example,the research proposes a model for vehicle control unit identification and de-carbonization under carbon peak and carbon neutrality scenario.This study is based on the identification of control unit in the existing neighborhoods,using the neighborhood traffic supply and demand ratio as an indicator and the regional equilibrium and minimum traffic supply and demand ratio as constraints,and is implemented based on greedy algorithm.The identification of control unit changes the distribution of traffic volume and speed,and affects traffic carbon emission.The carbon emission reduction model uses speed,vehicle kilometres,and vehicle type as conduction factors,and integrates the traffic model and carbon emission model to achieve carbon emission reduction calculations under each control scheme.In this example,the old town is re-divided from the current 54 neighborhood clusters into 22 vehicle control units,and the carbon emission has been reduced by 17.76% after the adoption of specific control measures.