面向CPS的单车排放配额协同动态分配方法研究

建立个体车辆的排放配额管理机制可以低成本实现道路交通行业污染物和碳排放的减排目标。这需要面向车辆个体的全域全量的动态感知、计算、决策、执行的闭环信息化体系进行支撑，而信息物理系统（cyber-physical system，CPS）技术为此提供了基础条件。但现有道路交通排放配额分配相关研究未研究车辆的污染物与碳排放的协同控制问题，忽略了车辆排放的个体排放差异性与时空动态性；交通信息物理系统相关研究缺少集成精细化的排放量化模型和排放配额管理模型。针对上述研究局限，提出了一种面向信息物理系统的个体车辆污染物与碳排放配额协同动态分配方法，构建了集成个体车辆身份识别及出行行为模型、污染物及二氧化碳排放量化模型、排放配额管理模型的交通信息物理系统框架，并提出了核心流程算法。以宣城市的真实数据进行实验分析，结果表明：提出的交通信息物理系统框架可实现个体车辆污染物和碳排放量及配额量的协同动态计算，配额分配方法与传统方法相比，配额分配颗粒度更加精细，分配对象的确定更加精准，可实现配额分配的动态调整以应对减排目标的时变性，配额分配激励先进、惩罚落后的引导效果更加显著。

Collaborative dynamic allocation method of individual vehicle emissions allowance for cyber-physical system

An emissions trading scheme by allocating allowances to individual vehicles can achieve the pollutant and carbon emissions reduction target of the road transportation industry at a low cost. This requires the support of a closed-loop system with dynamic perception, calculation, decision-making, and execution, which covers the whole region, all time, and all vehicles. The CPS technology can provide the primary conditions for the above system. However, the existing related studies lack the synergistic consideration of carbon and pollutant emissions, ignore the differences in the emissions and spatiotemporal dynamics of individual vehicles, and lack integration of precise emissions quantification model and emissions allowance management model in the traffic CPS. This study proposed a collaborative, dynamic allocation method of individual vehicle emissions allowances for the cyber-physical system. Moreover, it constructed a traffic cyber-physical system framework with integrating the individual vehicle identification model, individual vehicle travel behavior model, pollutant and carbon emissions quantification model, and emissions allowance management model(TCPS-E). Further, it proposed the algorithms of core process. Taking the actual data of Xuancheng city as a case study, the results show that the TCPS-E can achieve the collaborative, dynamic calculation of emissions and allowances of pollutants and carbon dioxide for individual vehicles. Compared with the traditional allowances allocation method, the granularity of the proposed allowances allocation method is more refined, and the determination of allocation objects is more accurate. Therefore, the dynamic adjustment of allowances allocation to cope with the time-varying limit of the allowances cap can be achieved. Furthermore, the effect of the proposed method on promoting individual emission reduction is more significant.