论文标题
揭示基于现实世界数据的二氧化碳排放减少及其决定因素
Revealing the CO2 emission reduction of ridesplitting and its determinants based on real-world data
论文作者
论文摘要
Ridesplitting是一种合并的骑乘服务形式，具有减轻骑行对环境的负面影响的巨大潜力。但是，大多数现有研究仅根据优化模型和仿真探讨其理论环境益处。相比之下，这项研究旨在揭示基于观察到的中国骑车数据的数据及其决定因素的现实世界排放减少。本研究将TRIP数据与Copert模型集成在一起，计算了共享乘车（骑乘）的CO2排放及其取代的单骑行（常规乘车），以估计每次骑行旅行的二氧化碳排放降低。结果表明，并非所有的骑行旅行都减少了现实世界中的骑车的排放。二氧化碳的降低速度降低速率因行程到旅行而异，平均为43.15g/km。然后，应用可解释的机器学习模型，梯度提升机，用于探索二氧化碳排放率降低速度的关系及其决定因素之间的关系。基于Shapley添加性解释（SHAP）方法，共享乘车的重叠率和弯路速率被确定为确定二氧化碳排放减少乘车率的最重要因素。增加重叠速率，共享乘车的数量，平均速度和行驶距离比，同时降低弯路率，实际行程距离和行驶距离差距可以增加二氧化碳的降低骑行率。另外，通过部分依赖图研究了决定因素的非线性效应和相互作用。综上所述，这项研究为政府和骑车公司提供了一种科学方法，以更好地评估和优化乘车的环境利益。
Ridesplitting, which is a form of pooled ridesourcing service, has great potential to alleviate the negative impacts of ridesourcing on the environment. However, most existing studies only explored its theoretical environmental benefits based on optimization models and simulations. By contrast, this study aims to reveal the real-world emission reduction of ridesplitting and its determinants based on the observed data of ridesourcing in Chengdu, China. Integrating the trip data with the COPERT model, this study calculates the CO2 emissions of shared rides (ridesplitting) and their substituted single rides (regular ridesourcing) to estimate the CO2 emission reduction of each ridesplitting trip. The results show that not all ridesplitting trips reduce emissions from ridesourcing in the real world. The CO2 emission reduction rate of ridesplitting varies from trip to trip, averaging at 43.15g/km. Then, interpretable machine learning models, gradient boosting machines, are applied to explore the relationship between the CO2 emission reduction rate of ridesplitting and its determinants. Based on the SHapley Additive exPlanations (SHAP) method, the overlap rate and detour rate of shared rides are identified to be the most important factors that determine the CO2 emission reduction rate of ridesplitting. Increasing the overlap rate, the number of shared rides, average speed, and ride distance ratio while decreasing the detour rate, actual trip distance, and ride distance gap can increase the CO2 emission reduction rate of ridesplitting. In addition, nonlinear effects and interactions of the determinants are examined through the partial dependence plots. To sum up, this study provides a scientific method for the government and ridesourcing companies to better assess and optimize the environmental benefits of ridesplitting.
